mirror of
https://github.com/KwaiVGI/LivePortrait.git
synced 2024-12-22 20:42:38 +00:00
fix: remove face3d and fix gradio version (#26)
* feat: gradio sticthing option * fix: face3d * chore: add gradio
This commit is contained in:
ZhizhouZhong
GitHub
parent
420b4a08c7
commit
2f808ca1d6
14
app.py
14
app.py
@ -35,11 +35,11 @@ title_md = "assets/gradio_title.md"
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example_portrait_dir = "assets/examples/source"
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example_video_dir = "assets/examples/driving"
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data_examples = [
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[osp.join(example_portrait_dir, "s1.jpg"), osp.join(example_video_dir, "d1.mp4"), True, True, True],
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[osp.join(example_portrait_dir, "s2.jpg"), osp.join(example_video_dir, "d2.mp4"), True, True, True],
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[osp.join(example_portrait_dir, "s3.jpg"), osp.join(example_video_dir, "d5.mp4"), True, True, True],
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[osp.join(example_portrait_dir, "s5.jpg"), osp.join(example_video_dir, "d6.mp4"), True, True, True],
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[osp.join(example_portrait_dir, "s7.jpg"), osp.join(example_video_dir, "d7.mp4"), True, True, True],
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[osp.join(example_portrait_dir, "s9.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, True],
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[osp.join(example_portrait_dir, "s6.jpg"), osp.join(example_video_dir, "d0.mp4"), True, True, True, True],
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[osp.join(example_portrait_dir, "s10.jpg"), osp.join(example_video_dir, "d5.mp4"), True, True, True, True],
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[osp.join(example_portrait_dir, "s5.jpg"), osp.join(example_video_dir, "d6.mp4"), True, True, True, True],
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[osp.join(example_portrait_dir, "s7.jpg"), osp.join(example_video_dir, "d7.mp4"), True, True, True, True],
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]
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#################### interface logic ####################
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@ -65,8 +65,8 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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with gr.Accordion(open=True, label="Animation Options"):
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with gr.Row():
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flag_relative_input = gr.Checkbox(value=True, label="relative pose")
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flag_remap_input = gr.Checkbox(value=True, label="paste-back")
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flag_do_crop_input = gr.Checkbox(value=True, label="do crop")
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flag_remap_input = gr.Checkbox(value=True, label="paste-back")
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with gr.Row():
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with gr.Column():
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process_button_animation = gr.Button("🚀 Animate", variant="primary")
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@ -144,7 +144,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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inputs=image_input,
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outputs=[eye_retargeting_slider, lip_retargeting_slider, retargeting_input_image]
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)
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##########################################################
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demo.launch(
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@ -105,7 +105,6 @@ python inference.py -h
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We also provide a Gradio interface for a better experience. Please install `gradio` and then run `app.py`:
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```bash
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pip install gradio==4.37.1
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python app.py
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```
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@ -20,3 +20,4 @@ albumentations==1.4.10
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matplotlib==3.9.0
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imageio-ffmpeg==0.5.1
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tyro==0.8.5
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gradio==4.37.1
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@ -43,7 +43,7 @@ class GradioPipeline(LivePortraitPipeline):
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input_video_path,
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flag_relative_input,
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flag_do_crop_input,
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flag_remap_input
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flag_remap_input,
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):
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""" for video driven potrait animation
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"""
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@ -53,7 +53,7 @@ class GradioPipeline(LivePortraitPipeline):
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'driving_info': input_video_path,
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'flag_relative': flag_relative_input,
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'flag_do_crop': flag_do_crop_input,
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'flag_pasteback': flag_remap_input
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'flag_pasteback': flag_remap_input,
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}
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# update config from user input
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self.args = update_args(self.args, args_user)
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@ -17,5 +17,4 @@ from . import model_zoo
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from . import utils
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from . import app
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from . import data
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from . import thirdparty
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@ -1,2 +1 @@
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from .face_analysis import *
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from .mask_renderer import *
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@ -15,9 +15,11 @@ import onnxruntime
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from numpy.linalg import norm
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from ..model_zoo import model_zoo
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from ..utils import DEFAULT_MP_NAME, ensure_available
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from ..utils import ensure_available
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from .common import Face
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DEFAULT_MP_NAME = 'buffalo_l'
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__all__ = ['FaceAnalysis']
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class FaceAnalysis:
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@ -1,232 +0,0 @@
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import os, sys, datetime
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import numpy as np
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import os.path as osp
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import albumentations as A
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from albumentations.core.transforms_interface import ImageOnlyTransform
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from .face_analysis import FaceAnalysis
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from ..utils import get_model_dir
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from ..thirdparty import face3d
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from ..data import get_image as ins_get_image
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from ..utils import DEFAULT_MP_NAME
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import cv2
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class MaskRenderer:
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def __init__(self, name=DEFAULT_MP_NAME, root='~/.insightface', insfa=None):
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#if insfa is None, enter render_only mode
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self.mp_name = name
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self.root = root
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self.insfa = insfa
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model_dir = get_model_dir(name, root)
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bfm_file = osp.join(model_dir, 'BFM.mat')
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assert osp.exists(bfm_file), 'should contains BFM.mat in your model directory'
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self.bfm = face3d.morphable_model.MorphabelModel(bfm_file)
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self.index_ind = self.bfm.kpt_ind
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bfm_uv_file = osp.join(model_dir, 'BFM_UV.mat')
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assert osp.exists(bfm_uv_file), 'should contains BFM_UV.mat in your model directory'
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uv_coords = face3d.morphable_model.load.load_uv_coords(bfm_uv_file)
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self.uv_size = (224,224)
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self.mask_stxr = 0.1
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self.mask_styr = 0.33
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self.mask_etxr = 0.9
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self.mask_etyr = 0.7
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self.tex_h , self.tex_w, self.tex_c = self.uv_size[1] , self.uv_size[0],3
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texcoord = np.zeros_like(uv_coords)
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texcoord[:, 0] = uv_coords[:, 0] * (self.tex_h - 1)
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texcoord[:, 1] = uv_coords[:, 1] * (self.tex_w - 1)
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texcoord[:, 1] = self.tex_w - texcoord[:, 1] - 1
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self.texcoord = np.hstack((texcoord, np.zeros((texcoord.shape[0], 1))))
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self.X_ind = self.bfm.kpt_ind
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self.mask_image_names = ['mask_white', 'mask_blue', 'mask_black', 'mask_green']
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self.mask_aug_probs = [0.4, 0.4, 0.1, 0.1]
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#self.mask_images = []
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#self.mask_images_rgb = []
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#for image_name in mask_image_names:
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# mask_image = ins_get_image(image_name)
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# self.mask_images.append(mask_image)
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# mask_image_rgb = mask_image[:,:,::-1]
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# self.mask_images_rgb.append(mask_image_rgb)
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def prepare(self, ctx_id=0, det_thresh=0.5, det_size=(128, 128)):
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self.pre_ctx_id = ctx_id
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self.pre_det_thresh = det_thresh
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self.pre_det_size = det_size
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def transform(self, shape3D, R):
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s = 1.0
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shape3D[:2, :] = shape3D[:2, :]
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shape3D = s * np.dot(R, shape3D)
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return shape3D
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def preprocess(self, vertices, w, h):
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R1 = face3d.mesh.transform.angle2matrix([0, 180, 180])
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t = np.array([-w // 2, -h // 2, 0])
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vertices = vertices.T
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vertices += t
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vertices = self.transform(vertices.T, R1).T
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return vertices
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def project_to_2d(self,vertices,s,angles,t):
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transformed_vertices = self.bfm.transform(vertices, s, angles, t)
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projected_vertices = transformed_vertices.copy() # using stantard camera & orth projection
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return projected_vertices[self.bfm.kpt_ind, :2]
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def params_to_vertices(self,params , H , W):
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fitted_sp, fitted_ep, fitted_s, fitted_angles, fitted_t = params
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fitted_vertices = self.bfm.generate_vertices(fitted_sp, fitted_ep)
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transformed_vertices = self.bfm.transform(fitted_vertices, fitted_s, fitted_angles,
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fitted_t)
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transformed_vertices = self.preprocess(transformed_vertices.T, W, H)
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image_vertices = face3d.mesh.transform.to_image(transformed_vertices, H, W)
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return image_vertices
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def draw_lmk(self, face_image):
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faces = self.insfa.get(face_image, max_num=1)
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if len(faces)==0:
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return face_image
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return self.insfa.draw_on(face_image, faces)
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def build_params(self, face_image):
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#landmark = self.if3d68_handler.get(face_image)
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#if landmark is None:
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# return None #face not found
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if self.insfa is None:
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self.insfa = FaceAnalysis(name=self.mp_name, root=self.root, allowed_modules=['detection', 'landmark_3d_68'])
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self.insfa.prepare(ctx_id=self.pre_ctx_id, det_thresh=self.pre_det_thresh, det_size=self.pre_det_size)
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faces = self.insfa.get(face_image, max_num=1)
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if len(faces)==0:
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return None
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landmark = faces[0].landmark_3d_68[:,:2]
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fitted_sp, fitted_ep, fitted_s, fitted_angles, fitted_t = self.bfm.fit(landmark, self.X_ind, max_iter = 3)
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return [fitted_sp, fitted_ep, fitted_s, fitted_angles, fitted_t]
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def generate_mask_uv(self,mask, positions):
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uv_size = (self.uv_size[1], self.uv_size[0], 3)
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h, w, c = uv_size
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uv = np.zeros(shape=(self.uv_size[1],self.uv_size[0], 3), dtype=np.uint8)
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stxr, styr = positions[0], positions[1]
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etxr, etyr = positions[2], positions[3]
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stx, sty = int(w * stxr), int(h * styr)
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etx, ety = int(w * etxr), int(h * etyr)
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height = ety - sty
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width = etx - stx
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mask = cv2.resize(mask, (width, height))
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uv[sty:ety, stx:etx] = mask
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return uv
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def render_mask(self,face_image, mask_image, params, input_is_rgb=False, auto_blend = True, positions=[0.1, 0.33, 0.9, 0.7]):
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if isinstance(mask_image, str):
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to_rgb = True if input_is_rgb else False
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mask_image = ins_get_image(mask_image, to_rgb=to_rgb)
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uv_mask_image = self.generate_mask_uv(mask_image, positions)
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h,w,c = face_image.shape
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image_vertices = self.params_to_vertices(params ,h,w)
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output = (1-face3d.mesh.render.render_texture(image_vertices, self.bfm.full_triangles , uv_mask_image, self.texcoord, self.bfm.full_triangles, h , w ))*255
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output = output.astype(np.uint8)
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if auto_blend:
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mask_bd = (output==255).astype(np.uint8)
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final = face_image*mask_bd + (1-mask_bd)*output
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return final
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return output
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#def mask_augmentation(self, face_image, label, input_is_rgb=False, p=0.1):
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# if np.random.random()<p:
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# assert isinstance(label, (list, np.ndarray)), 'make sure the rec dataset includes mask params'
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# assert len(label)==237 or len(lable)==235, 'make sure the rec dataset includes mask params'
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# if len(label)==237:
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# if label[1]<0.0: #invalid label for mask aug
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# return face_image
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# label = label[2:]
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# params = self.decode_params(label)
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# mask_image_name = np.random.choice(self.mask_image_names, p=self.mask_aug_probs)
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# pos = np.random.uniform(0.33, 0.5)
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# face_image = self.render_mask(face_image, mask_image_name, params, input_is_rgb=input_is_rgb, positions=[0.1, pos, 0.9, 0.7])
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# return face_image
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@staticmethod
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def encode_params(params):
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p0 = list(params[0])
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p1 = list(params[1])
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p2 = [float(params[2])]
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p3 = list(params[3])
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p4 = list(params[4])
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return p0+p1+p2+p3+p4
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@staticmethod
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def decode_params(params):
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p0 = params[0:199]
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p0 = np.array(p0, dtype=np.float32).reshape( (-1, 1))
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p1 = params[199:228]
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p1 = np.array(p1, dtype=np.float32).reshape( (-1, 1))
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p2 = params[228]
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p3 = tuple(params[229:232])
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p4 = params[232:235]
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p4 = np.array(p4, dtype=np.float32).reshape( (-1, 1))
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return p0, p1, p2, p3, p4
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class MaskAugmentation(ImageOnlyTransform):
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def __init__(
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self,
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mask_names=['mask_white', 'mask_blue', 'mask_black', 'mask_green'],
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mask_probs=[0.4,0.4,0.1,0.1],
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h_low = 0.33,
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h_high = 0.35,
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always_apply=False,
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p=1.0,
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):
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super(MaskAugmentation, self).__init__(always_apply, p)
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self.renderer = MaskRenderer()
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assert len(mask_names)>0
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assert len(mask_names)==len(mask_probs)
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self.mask_names = mask_names
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self.mask_probs = mask_probs
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self.h_low = h_low
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self.h_high = h_high
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#self.hlabel = None
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def apply(self, image, hlabel, mask_name, h_pos, **params):
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#print(params.keys())
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#hlabel = params.get('hlabel')
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assert len(hlabel)==237 or len(hlabel)==235, 'make sure the rec dataset includes mask params'
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if len(hlabel)==237:
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if hlabel[1]<0.0:
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return image
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hlabel = hlabel[2:]
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#print(len(hlabel))
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mask_params = self.renderer.decode_params(hlabel)
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image = self.renderer.render_mask(image, mask_name, mask_params, input_is_rgb=True, positions=[0.1, h_pos, 0.9, 0.7])
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return image
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@property
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def targets_as_params(self):
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return ["image", "hlabel"]
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def get_params_dependent_on_targets(self, params):
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hlabel = params['hlabel']
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mask_name = np.random.choice(self.mask_names, p=self.mask_probs)
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h_pos = np.random.uniform(self.h_low, self.h_high)
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return {'hlabel': hlabel, 'mask_name': mask_name, 'h_pos': h_pos}
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def get_transform_init_args_names(self):
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#return ("hlabel", 'mask_names', 'mask_probs', 'h_low', 'h_high')
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return ('mask_names', 'mask_probs', 'h_low', 'h_high')
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if __name__ == "__main__":
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tool = MaskRenderer('antelope')
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tool.prepare(det_size=(128,128))
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image = cv2.imread("Tom_Hanks_54745.png")
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params = tool.build_params(image)
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#out = tool.draw_lmk(image)
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#cv2.imwrite('output_lmk.jpg', out)
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#mask_image = cv2.imread("masks/mask1.jpg")
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#mask_image = cv2.imread("masks/black-mask.png")
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#mask_image = cv2.imread("masks/mask2.jpg")
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mask_out = tool.render_mask(image, 'mask_blue', params)# use single thread to test the time cost
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cv2.imwrite('output_mask.jpg', mask_out)
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@ -1,13 +0,0 @@
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from abc import ABC, abstractmethod
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from argparse import ArgumentParser
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class BaseInsightFaceCLICommand(ABC):
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@staticmethod
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@abstractmethod
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def register_subcommand(parser: ArgumentParser):
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raise NotImplementedError()
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@abstractmethod
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def run(self):
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raise NotImplementedError()
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@ -1,29 +0,0 @@
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#!/usr/bin/env python
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from argparse import ArgumentParser
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from .model_download import ModelDownloadCommand
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from .rec_add_mask_param import RecAddMaskParamCommand
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def main():
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parser = ArgumentParser("InsightFace CLI tool", usage="insightface-cli <command> [<args>]")
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commands_parser = parser.add_subparsers(help="insightface-cli command-line helpers")
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# Register commands
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ModelDownloadCommand.register_subcommand(commands_parser)
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RecAddMaskParamCommand.register_subcommand(commands_parser)
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args = parser.parse_args()
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if not hasattr(args, "func"):
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parser.print_help()
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exit(1)
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# Run
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service = args.func(args)
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service.run()
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if __name__ == "__main__":
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main()
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@ -1,36 +0,0 @@
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from argparse import ArgumentParser
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from . import BaseInsightFaceCLICommand
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import os
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import os.path as osp
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import zipfile
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import glob
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from ..utils import download
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def model_download_command_factory(args):
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return ModelDownloadCommand(args.model, args.root, args.force)
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class ModelDownloadCommand(BaseInsightFaceCLICommand):
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#_url_format = '{repo_url}models/{file_name}.zip'
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@staticmethod
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def register_subcommand(parser: ArgumentParser):
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download_parser = parser.add_parser("model.download")
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download_parser.add_argument(
|
||||
"--root", type=str, default='~/.insightface', help="Path to location to store the models"
|
||||
)
|
||||
download_parser.add_argument(
|
||||
"--force", action="store_true", help="Force the model to be download even if already in root-dir"
|
||||
)
|
||||
download_parser.add_argument("model", type=str, help="Name of the model to download")
|
||||
download_parser.set_defaults(func=model_download_command_factory)
|
||||
|
||||
def __init__(self, model: str, root: str, force: bool):
|
||||
self._model = model
|
||||
self._root = root
|
||||
self._force = force
|
||||
|
||||
def run(self):
|
||||
download('models', self._model, force=self._force, root=self._root)
|
||||
|
||||
@ -1,94 +0,0 @@
|
||||
|
||||
import numbers
|
||||
import os
|
||||
from argparse import ArgumentParser, Namespace
|
||||
|
||||
import mxnet as mx
|
||||
import numpy as np
|
||||
|
||||
from ..app import MaskRenderer
|
||||
from ..data.rec_builder import RecBuilder
|
||||
from . import BaseInsightFaceCLICommand
|
||||
|
||||
|
||||
def rec_add_mask_param_command_factory(args: Namespace):
|
||||
|
||||
return RecAddMaskParamCommand(
|
||||
args.input, args.output
|
||||
)
|
||||
|
||||
|
||||
class RecAddMaskParamCommand(BaseInsightFaceCLICommand):
|
||||
@staticmethod
|
||||
def register_subcommand(parser: ArgumentParser):
|
||||
_parser = parser.add_parser("rec.addmaskparam")
|
||||
_parser.add_argument("input", type=str, help="input rec")
|
||||
_parser.add_argument("output", type=str, help="output rec, with mask param")
|
||||
_parser.set_defaults(func=rec_add_mask_param_command_factory)
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
input: str,
|
||||
output: str,
|
||||
):
|
||||
self._input = input
|
||||
self._output = output
|
||||
|
||||
|
||||
def run(self):
|
||||
tool = MaskRenderer()
|
||||
tool.prepare(ctx_id=0, det_size=(128,128))
|
||||
root_dir = self._input
|
||||
path_imgrec = os.path.join(root_dir, 'train.rec')
|
||||
path_imgidx = os.path.join(root_dir, 'train.idx')
|
||||
imgrec = mx.recordio.MXIndexedRecordIO(path_imgidx, path_imgrec, 'r')
|
||||
save_path = self._output
|
||||
wrec=RecBuilder(path=save_path)
|
||||
s = imgrec.read_idx(0)
|
||||
header, _ = mx.recordio.unpack(s)
|
||||
if header.flag > 0:
|
||||
if len(header.label)==2:
|
||||
imgidx = np.array(range(1, int(header.label[0])))
|
||||
else:
|
||||
imgidx = np.array(list(self.imgrec.keys))
|
||||
else:
|
||||
imgidx = np.array(list(self.imgrec.keys))
|
||||
stat = [0, 0]
|
||||
print('total:', len(imgidx))
|
||||
for iid, idx in enumerate(imgidx):
|
||||
#if iid==500000:
|
||||
# break
|
||||
if iid%1000==0:
|
||||
print('processing:', iid)
|
||||
s = imgrec.read_idx(idx)
|
||||
header, img = mx.recordio.unpack(s)
|
||||
label = header.label
|
||||
if not isinstance(label, numbers.Number):
|
||||
label = label[0]
|
||||
sample = mx.image.imdecode(img).asnumpy()
|
||||
bgr = sample[:,:,::-1]
|
||||
params = tool.build_params(bgr)
|
||||
#if iid<10:
|
||||
# mask_out = tool.render_mask(bgr, 'mask_blue', params)
|
||||
# cv2.imwrite('maskout_%d.jpg'%iid, mask_out)
|
||||
stat[1] += 1
|
||||
if params is None:
|
||||
wlabel = [label] + [-1.0]*236
|
||||
stat[0] += 1
|
||||
else:
|
||||
#print(0, params[0].shape, params[0].dtype)
|
||||
#print(1, params[1].shape, params[1].dtype)
|
||||
#print(2, params[2])
|
||||
#print(3, len(params[3]), params[3][0].__class__)
|
||||
#print(4, params[4].shape, params[4].dtype)
|
||||
mask_label = tool.encode_params(params)
|
||||
wlabel = [label, 0.0]+mask_label # 237 including idlabel, total mask params size is 235
|
||||
if iid==0:
|
||||
print('param size:', len(mask_label), len(wlabel), label)
|
||||
assert len(wlabel)==237
|
||||
wrec.add_image(img, wlabel)
|
||||
#print(len(params))
|
||||
|
||||
wrec.close()
|
||||
print('finished on', self._output, ', failed:', stat[0])
|
||||
|
||||
@ -1,4 +0,0 @@
|
||||
#import mesh
|
||||
#import morphable_model
|
||||
from . import mesh
|
||||
from . import morphable_model
|
||||
@ -1,15 +0,0 @@
|
||||
#from __future__ import absolute_import
|
||||
#from cython import mesh_core_cython
|
||||
#import io
|
||||
#import vis
|
||||
#import transform
|
||||
#import light
|
||||
#import render
|
||||
|
||||
from .cython import mesh_core_cython
|
||||
from . import io
|
||||
from . import vis
|
||||
from . import transform
|
||||
from . import light
|
||||
from . import render
|
||||
|
||||
@ -1,375 +0,0 @@
|
||||
/*
|
||||
functions that can not be optimazed by vertorization in python.
|
||||
1. rasterization.(need process each triangle)
|
||||
2. normal of each vertex.(use one-ring, need process each vertex)
|
||||
3. write obj(seems that it can be verctorized? anyway, writing it in c++ is simple, so also add function here. --> however, why writting in c++ is still slow?)
|
||||
|
||||
Author: Yao Feng
|
||||
Mail: yaofeng1995@gmail.com
|
||||
*/
|
||||
|
||||
#include "mesh_core.h"
|
||||
|
||||
|
||||
/* Judge whether the point is in the triangle
|
||||
Method:
|
||||
http://blackpawn.com/texts/pointinpoly/
|
||||
Args:
|
||||
point: [x, y]
|
||||
tri_points: three vertices(2d points) of a triangle. 2 coords x 3 vertices
|
||||
Returns:
|
||||
bool: true for in triangle
|
||||
*/
|
||||
bool isPointInTri(point p, point p0, point p1, point p2)
|
||||
{
|
||||
// vectors
|
||||
point v0, v1, v2;
|
||||
v0 = p2 - p0;
|
||||
v1 = p1 - p0;
|
||||
v2 = p - p0;
|
||||
|
||||
// dot products
|
||||
float dot00 = v0.dot(v0); //v0.x * v0.x + v0.y * v0.y //np.dot(v0.T, v0)
|
||||
float dot01 = v0.dot(v1); //v0.x * v1.x + v0.y * v1.y //np.dot(v0.T, v1)
|
||||
float dot02 = v0.dot(v2); //v0.x * v2.x + v0.y * v2.y //np.dot(v0.T, v2)
|
||||
float dot11 = v1.dot(v1); //v1.x * v1.x + v1.y * v1.y //np.dot(v1.T, v1)
|
||||
float dot12 = v1.dot(v2); //v1.x * v2.x + v1.y * v2.y//np.dot(v1.T, v2)
|
||||
|
||||
// barycentric coordinates
|
||||
float inverDeno;
|
||||
if(dot00*dot11 - dot01*dot01 == 0)
|
||||
inverDeno = 0;
|
||||
else
|
||||
inverDeno = 1/(dot00*dot11 - dot01*dot01);
|
||||
|
||||
float u = (dot11*dot02 - dot01*dot12)*inverDeno;
|
||||
float v = (dot00*dot12 - dot01*dot02)*inverDeno;
|
||||
|
||||
// check if point in triangle
|
||||
return (u >= 0) && (v >= 0) && (u + v < 1);
|
||||
}
|
||||
|
||||
|
||||
void get_point_weight(float* weight, point p, point p0, point p1, point p2)
|
||||
{
|
||||
// vectors
|
||||
point v0, v1, v2;
|
||||
v0 = p2 - p0;
|
||||
v1 = p1 - p0;
|
||||
v2 = p - p0;
|
||||
|
||||
// dot products
|
||||
float dot00 = v0.dot(v0); //v0.x * v0.x + v0.y * v0.y //np.dot(v0.T, v0)
|
||||
float dot01 = v0.dot(v1); //v0.x * v1.x + v0.y * v1.y //np.dot(v0.T, v1)
|
||||
float dot02 = v0.dot(v2); //v0.x * v2.x + v0.y * v2.y //np.dot(v0.T, v2)
|
||||
float dot11 = v1.dot(v1); //v1.x * v1.x + v1.y * v1.y //np.dot(v1.T, v1)
|
||||
float dot12 = v1.dot(v2); //v1.x * v2.x + v1.y * v2.y//np.dot(v1.T, v2)
|
||||
|
||||
// barycentric coordinates
|
||||
float inverDeno;
|
||||
if(dot00*dot11 - dot01*dot01 == 0)
|
||||
inverDeno = 0;
|
||||
else
|
||||
inverDeno = 1/(dot00*dot11 - dot01*dot01);
|
||||
|
||||
float u = (dot11*dot02 - dot01*dot12)*inverDeno;
|
||||
float v = (dot00*dot12 - dot01*dot02)*inverDeno;
|
||||
|
||||
// weight
|
||||
weight[0] = 1 - u - v;
|
||||
weight[1] = v;
|
||||
weight[2] = u;
|
||||
}
|
||||
|
||||
|
||||
void _get_normal_core(
|
||||
float* normal, float* tri_normal, int* triangles,
|
||||
int ntri)
|
||||
{
|
||||
int i, j;
|
||||
int tri_p0_ind, tri_p1_ind, tri_p2_ind;
|
||||
|
||||
for(i = 0; i < ntri; i++)
|
||||
{
|
||||
tri_p0_ind = triangles[3*i];
|
||||
tri_p1_ind = triangles[3*i + 1];
|
||||
tri_p2_ind = triangles[3*i + 2];
|
||||
|
||||
for(j = 0; j < 3; j++)
|
||||
{
|
||||
normal[3*tri_p0_ind + j] = normal[3*tri_p0_ind + j] + tri_normal[3*i + j];
|
||||
normal[3*tri_p1_ind + j] = normal[3*tri_p1_ind + j] + tri_normal[3*i + j];
|
||||
normal[3*tri_p2_ind + j] = normal[3*tri_p2_ind + j] + tri_normal[3*i + j];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
void _rasterize_triangles_core(
|
||||
float* vertices, int* triangles,
|
||||
float* depth_buffer, int* triangle_buffer, float* barycentric_weight,
|
||||
int nver, int ntri,
|
||||
int h, int w)
|
||||
{
|
||||
int i;
|
||||
int x, y, k;
|
||||
int tri_p0_ind, tri_p1_ind, tri_p2_ind;
|
||||
point p0, p1, p2, p;
|
||||
int x_min, x_max, y_min, y_max;
|
||||
float p_depth, p0_depth, p1_depth, p2_depth;
|
||||
float weight[3];
|
||||
|
||||
for(i = 0; i < ntri; i++)
|
||||
{
|
||||
tri_p0_ind = triangles[3*i];
|
||||
tri_p1_ind = triangles[3*i + 1];
|
||||
tri_p2_ind = triangles[3*i + 2];
|
||||
|
||||
p0.x = vertices[3*tri_p0_ind]; p0.y = vertices[3*tri_p0_ind + 1]; p0_depth = vertices[3*tri_p0_ind + 2];
|
||||
p1.x = vertices[3*tri_p1_ind]; p1.y = vertices[3*tri_p1_ind + 1]; p1_depth = vertices[3*tri_p1_ind + 2];
|
||||
p2.x = vertices[3*tri_p2_ind]; p2.y = vertices[3*tri_p2_ind + 1]; p2_depth = vertices[3*tri_p2_ind + 2];
|
||||
|
||||
x_min = max((int)ceil(min(p0.x, min(p1.x, p2.x))), 0);
|
||||
x_max = min((int)floor(max(p0.x, max(p1.x, p2.x))), w - 1);
|
||||
|
||||
y_min = max((int)ceil(min(p0.y, min(p1.y, p2.y))), 0);
|
||||
y_max = min((int)floor(max(p0.y, max(p1.y, p2.y))), h - 1);
|
||||
|
||||
if(x_max < x_min || y_max < y_min)
|
||||
{
|
||||
continue;
|
||||
}
|
||||
|
||||
for(y = y_min; y <= y_max; y++) //h
|
||||
{
|
||||
for(x = x_min; x <= x_max; x++) //w
|
||||
{
|
||||
p.x = x; p.y = y;
|
||||
if(p.x < 2 || p.x > w - 3 || p.y < 2 || p.y > h - 3 || isPointInTri(p, p0, p1, p2))
|
||||
{
|
||||
get_point_weight(weight, p, p0, p1, p2);
|
||||
p_depth = weight[0]*p0_depth + weight[1]*p1_depth + weight[2]*p2_depth;
|
||||
|
||||
if((p_depth > depth_buffer[y*w + x]))
|
||||
{
|
||||
depth_buffer[y*w + x] = p_depth;
|
||||
triangle_buffer[y*w + x] = i;
|
||||
for(k = 0; k < 3; k++)
|
||||
{
|
||||
barycentric_weight[y*w*3 + x*3 + k] = weight[k];
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
void _render_colors_core(
|
||||
float* image, float* vertices, int* triangles,
|
||||
float* colors,
|
||||
float* depth_buffer,
|
||||
int nver, int ntri,
|
||||
int h, int w, int c)
|
||||
{
|
||||
int i;
|
||||
int x, y, k;
|
||||
int tri_p0_ind, tri_p1_ind, tri_p2_ind;
|
||||
point p0, p1, p2, p;
|
||||
int x_min, x_max, y_min, y_max;
|
||||
float p_depth, p0_depth, p1_depth, p2_depth;
|
||||
float p_color, p0_color, p1_color, p2_color;
|
||||
float weight[3];
|
||||
|
||||
for(i = 0; i < ntri; i++)
|
||||
{
|
||||
tri_p0_ind = triangles[3*i];
|
||||
tri_p1_ind = triangles[3*i + 1];
|
||||
tri_p2_ind = triangles[3*i + 2];
|
||||
|
||||
p0.x = vertices[3*tri_p0_ind]; p0.y = vertices[3*tri_p0_ind + 1]; p0_depth = vertices[3*tri_p0_ind + 2];
|
||||
p1.x = vertices[3*tri_p1_ind]; p1.y = vertices[3*tri_p1_ind + 1]; p1_depth = vertices[3*tri_p1_ind + 2];
|
||||
p2.x = vertices[3*tri_p2_ind]; p2.y = vertices[3*tri_p2_ind + 1]; p2_depth = vertices[3*tri_p2_ind + 2];
|
||||
|
||||
x_min = max((int)ceil(min(p0.x, min(p1.x, p2.x))), 0);
|
||||
x_max = min((int)floor(max(p0.x, max(p1.x, p2.x))), w - 1);
|
||||
|
||||
y_min = max((int)ceil(min(p0.y, min(p1.y, p2.y))), 0);
|
||||
y_max = min((int)floor(max(p0.y, max(p1.y, p2.y))), h - 1);
|
||||
|
||||
if(x_max < x_min || y_max < y_min)
|
||||
{
|
||||
continue;
|
||||
}
|
||||
|
||||
for(y = y_min; y <= y_max; y++) //h
|
||||
{
|
||||
for(x = x_min; x <= x_max; x++) //w
|
||||
{
|
||||
p.x = x; p.y = y;
|
||||
if(p.x < 2 || p.x > w - 3 || p.y < 2 || p.y > h - 3 || isPointInTri(p, p0, p1, p2))
|
||||
{
|
||||
get_point_weight(weight, p, p0, p1, p2);
|
||||
p_depth = weight[0]*p0_depth + weight[1]*p1_depth + weight[2]*p2_depth;
|
||||
|
||||
if((p_depth > depth_buffer[y*w + x]))
|
||||
{
|
||||
for(k = 0; k < c; k++) // c
|
||||
{
|
||||
p0_color = colors[c*tri_p0_ind + k];
|
||||
p1_color = colors[c*tri_p1_ind + k];
|
||||
p2_color = colors[c*tri_p2_ind + k];
|
||||
|
||||
p_color = weight[0]*p0_color + weight[1]*p1_color + weight[2]*p2_color;
|
||||
image[y*w*c + x*c + k] = p_color;
|
||||
}
|
||||
|
||||
depth_buffer[y*w + x] = p_depth;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
void _render_texture_core(
|
||||
float* image, float* vertices, int* triangles,
|
||||
float* texture, float* tex_coords, int* tex_triangles,
|
||||
float* depth_buffer,
|
||||
int nver, int tex_nver, int ntri,
|
||||
int h, int w, int c,
|
||||
int tex_h, int tex_w, int tex_c,
|
||||
int mapping_type)
|
||||
{
|
||||
int i;
|
||||
int x, y, k;
|
||||
int tri_p0_ind, tri_p1_ind, tri_p2_ind;
|
||||
int tex_tri_p0_ind, tex_tri_p1_ind, tex_tri_p2_ind;
|
||||
point p0, p1, p2, p;
|
||||
point tex_p0, tex_p1, tex_p2, tex_p;
|
||||
int x_min, x_max, y_min, y_max;
|
||||
float weight[3];
|
||||
float p_depth, p0_depth, p1_depth, p2_depth;
|
||||
float xd, yd;
|
||||
float ul, ur, dl, dr;
|
||||
for(i = 0; i < ntri; i++)
|
||||
{
|
||||
// mesh
|
||||
tri_p0_ind = triangles[3*i];
|
||||
tri_p1_ind = triangles[3*i + 1];
|
||||
tri_p2_ind = triangles[3*i + 2];
|
||||
|
||||
p0.x = vertices[3*tri_p0_ind]; p0.y = vertices[3*tri_p0_ind + 1]; p0_depth = vertices[3*tri_p0_ind + 2];
|
||||
p1.x = vertices[3*tri_p1_ind]; p1.y = vertices[3*tri_p1_ind + 1]; p1_depth = vertices[3*tri_p1_ind + 2];
|
||||
p2.x = vertices[3*tri_p2_ind]; p2.y = vertices[3*tri_p2_ind + 1]; p2_depth = vertices[3*tri_p2_ind + 2];
|
||||
|
||||
// texture
|
||||
tex_tri_p0_ind = tex_triangles[3*i];
|
||||
tex_tri_p1_ind = tex_triangles[3*i + 1];
|
||||
tex_tri_p2_ind = tex_triangles[3*i + 2];
|
||||
|
||||
tex_p0.x = tex_coords[3*tex_tri_p0_ind]; tex_p0.y = tex_coords[3*tri_p0_ind + 1];
|
||||
tex_p1.x = tex_coords[3*tex_tri_p1_ind]; tex_p1.y = tex_coords[3*tri_p1_ind + 1];
|
||||
tex_p2.x = tex_coords[3*tex_tri_p2_ind]; tex_p2.y = tex_coords[3*tri_p2_ind + 1];
|
||||
|
||||
|
||||
x_min = max((int)ceil(min(p0.x, min(p1.x, p2.x))), 0);
|
||||
x_max = min((int)floor(max(p0.x, max(p1.x, p2.x))), w - 1);
|
||||
|
||||
y_min = max((int)ceil(min(p0.y, min(p1.y, p2.y))), 0);
|
||||
y_max = min((int)floor(max(p0.y, max(p1.y, p2.y))), h - 1);
|
||||
|
||||
|
||||
if(x_max < x_min || y_max < y_min)
|
||||
{
|
||||
continue;
|
||||
}
|
||||
|
||||
for(y = y_min; y <= y_max; y++) //h
|
||||
{
|
||||
for(x = x_min; x <= x_max; x++) //w
|
||||
{
|
||||
p.x = x; p.y = y;
|
||||
if(p.x < 2 || p.x > w - 3 || p.y < 2 || p.y > h - 3 || isPointInTri(p, p0, p1, p2))
|
||||
{
|
||||
get_point_weight(weight, p, p0, p1, p2);
|
||||
p_depth = weight[0]*p0_depth + weight[1]*p1_depth + weight[2]*p2_depth;
|
||||
|
||||
if((p_depth > depth_buffer[y*w + x]))
|
||||
{
|
||||
// -- color from texture
|
||||
// cal weight in mesh tri
|
||||
get_point_weight(weight, p, p0, p1, p2);
|
||||
// cal coord in texture
|
||||
tex_p = tex_p0*weight[0] + tex_p1*weight[1] + tex_p2*weight[2];
|
||||
tex_p.x = max(min(tex_p.x, float(tex_w - 1)), float(0));
|
||||
tex_p.y = max(min(tex_p.y, float(tex_h - 1)), float(0));
|
||||
|
||||
yd = tex_p.y - floor(tex_p.y);
|
||||
xd = tex_p.x - floor(tex_p.x);
|
||||
for(k = 0; k < c; k++)
|
||||
{
|
||||
if(mapping_type==0)// nearest
|
||||
{
|
||||
image[y*w*c + x*c + k] = texture[int(round(tex_p.y))*tex_w*tex_c + int(round(tex_p.x))*tex_c + k];
|
||||
}
|
||||
else//bilinear interp
|
||||
{
|
||||
ul = texture[(int)floor(tex_p.y)*tex_w*tex_c + (int)floor(tex_p.x)*tex_c + k];
|
||||
ur = texture[(int)floor(tex_p.y)*tex_w*tex_c + (int)ceil(tex_p.x)*tex_c + k];
|
||||
dl = texture[(int)ceil(tex_p.y)*tex_w*tex_c + (int)floor(tex_p.x)*tex_c + k];
|
||||
dr = texture[(int)ceil(tex_p.y)*tex_w*tex_c + (int)ceil(tex_p.x)*tex_c + k];
|
||||
|
||||
image[y*w*c + x*c + k] = ul*(1-xd)*(1-yd) + ur*xd*(1-yd) + dl*(1-xd)*yd + dr*xd*yd;
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
depth_buffer[y*w + x] = p_depth;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
// ------------------------------------------------- write
|
||||
// obj write
|
||||
// Ref: https://github.com/patrikhuber/eos/blob/master/include/eos/core/Mesh.hpp
|
||||
void _write_obj_with_colors_texture(string filename, string mtl_name,
|
||||
float* vertices, int* triangles, float* colors, float* uv_coords,
|
||||
int nver, int ntri, int ntexver)
|
||||
{
|
||||
int i;
|
||||
|
||||
ofstream obj_file(filename.c_str());
|
||||
|
||||
// first line of the obj file: the mtl name
|
||||
obj_file << "mtllib " << mtl_name << endl;
|
||||
|
||||
// write vertices
|
||||
for (i = 0; i < nver; ++i)
|
||||
{
|
||||
obj_file << "v " << vertices[3*i] << " " << vertices[3*i + 1] << " " << vertices[3*i + 2] << colors[3*i] << " " << colors[3*i + 1] << " " << colors[3*i + 2] << endl;
|
||||
}
|
||||
|
||||
// write uv coordinates
|
||||
for (i = 0; i < ntexver; ++i)
|
||||
{
|
||||
//obj_file << "vt " << uv_coords[2*i] << " " << (1 - uv_coords[2*i + 1]) << endl;
|
||||
obj_file << "vt " << uv_coords[2*i] << " " << uv_coords[2*i + 1] << endl;
|
||||
}
|
||||
|
||||
obj_file << "usemtl FaceTexture" << endl;
|
||||
// write triangles
|
||||
for (i = 0; i < ntri; ++i)
|
||||
{
|
||||
// obj_file << "f " << triangles[3*i] << "/" << triangles[3*i] << " " << triangles[3*i + 1] << "/" << triangles[3*i + 1] << " " << triangles[3*i + 2] << "/" << triangles[3*i + 2] << endl;
|
||||
obj_file << "f " << triangles[3*i + 2] << "/" << triangles[3*i + 2] << " " << triangles[3*i + 1] << "/" << triangles[3*i + 1] << " " << triangles[3*i] << "/" << triangles[3*i] << endl;
|
||||
}
|
||||
|
||||
}
|
||||
@ -1,83 +0,0 @@
|
||||
#ifndef MESH_CORE_HPP_
|
||||
#define MESH_CORE_HPP_
|
||||
|
||||
#include <stdio.h>
|
||||
#include <cmath>
|
||||
#include <algorithm>
|
||||
#include <string>
|
||||
#include <iostream>
|
||||
#include <fstream>
|
||||
|
||||
using namespace std;
|
||||
|
||||
class point
|
||||
{
|
||||
public:
|
||||
float x;
|
||||
float y;
|
||||
|
||||
float dot(point p)
|
||||
{
|
||||
return this->x * p.x + this->y * p.y;
|
||||
}
|
||||
|
||||
point operator-(const point& p)
|
||||
{
|
||||
point np;
|
||||
np.x = this->x - p.x;
|
||||
np.y = this->y - p.y;
|
||||
return np;
|
||||
}
|
||||
|
||||
point operator+(const point& p)
|
||||
{
|
||||
point np;
|
||||
np.x = this->x + p.x;
|
||||
np.y = this->y + p.y;
|
||||
return np;
|
||||
}
|
||||
|
||||
point operator*(float s)
|
||||
{
|
||||
point np;
|
||||
np.x = s * this->x;
|
||||
np.y = s * this->y;
|
||||
return np;
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
bool isPointInTri(point p, point p0, point p1, point p2, int h, int w);
|
||||
void get_point_weight(float* weight, point p, point p0, point p1, point p2);
|
||||
|
||||
void _get_normal_core(
|
||||
float* normal, float* tri_normal, int* triangles,
|
||||
int ntri);
|
||||
|
||||
void _rasterize_triangles_core(
|
||||
float* vertices, int* triangles,
|
||||
float* depth_buffer, int* triangle_buffer, float* barycentric_weight,
|
||||
int nver, int ntri,
|
||||
int h, int w);
|
||||
|
||||
void _render_colors_core(
|
||||
float* image, float* vertices, int* triangles,
|
||||
float* colors,
|
||||
float* depth_buffer,
|
||||
int nver, int ntri,
|
||||
int h, int w, int c);
|
||||
|
||||
void _render_texture_core(
|
||||
float* image, float* vertices, int* triangles,
|
||||
float* texture, float* tex_coords, int* tex_triangles,
|
||||
float* depth_buffer,
|
||||
int nver, int tex_nver, int ntri,
|
||||
int h, int w, int c,
|
||||
int tex_h, int tex_w, int tex_c,
|
||||
int mapping_type);
|
||||
|
||||
void _write_obj_with_colors_texture(string filename, string mtl_name,
|
||||
float* vertices, int* triangles, float* colors, float* uv_coords,
|
||||
int nver, int ntri, int ntexver);
|
||||
|
||||
#endif
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
Binary file not shown.
@ -1,109 +0,0 @@
|
||||
import numpy as np
|
||||
cimport numpy as np
|
||||
from libcpp.string cimport string
|
||||
|
||||
# use the Numpy-C-API from Cython
|
||||
np.import_array()
|
||||
|
||||
# cdefine the signature of our c function
|
||||
cdef extern from "mesh_core.h":
|
||||
void _rasterize_triangles_core(
|
||||
float* vertices, int* triangles,
|
||||
float* depth_buffer, int* triangle_buffer, float* barycentric_weight,
|
||||
int nver, int ntri,
|
||||
int h, int w)
|
||||
|
||||
void _render_colors_core(
|
||||
float* image, float* vertices, int* triangles,
|
||||
float* colors,
|
||||
float* depth_buffer,
|
||||
int nver, int ntri,
|
||||
int h, int w, int c)
|
||||
|
||||
void _render_texture_core(
|
||||
float* image, float* vertices, int* triangles,
|
||||
float* texture, float* tex_coords, int* tex_triangles,
|
||||
float* depth_buffer,
|
||||
int nver, int tex_nver, int ntri,
|
||||
int h, int w, int c,
|
||||
int tex_h, int tex_w, int tex_c,
|
||||
int mapping_type)
|
||||
|
||||
void _get_normal_core(
|
||||
float* normal, float* tri_normal, int* triangles,
|
||||
int ntri)
|
||||
|
||||
void _write_obj_with_colors_texture(string filename, string mtl_name,
|
||||
float* vertices, int* triangles, float* colors, float* uv_coords,
|
||||
int nver, int ntri, int ntexver)
|
||||
|
||||
def get_normal_core(np.ndarray[float, ndim=2, mode = "c"] normal not None,
|
||||
np.ndarray[float, ndim=2, mode = "c"] tri_normal not None,
|
||||
np.ndarray[int, ndim=2, mode="c"] triangles not None,
|
||||
int ntri
|
||||
):
|
||||
_get_normal_core(
|
||||
<float*> np.PyArray_DATA(normal), <float*> np.PyArray_DATA(tri_normal), <int*> np.PyArray_DATA(triangles),
|
||||
ntri)
|
||||
|
||||
def rasterize_triangles_core(
|
||||
np.ndarray[float, ndim=2, mode = "c"] vertices not None,
|
||||
np.ndarray[int, ndim=2, mode="c"] triangles not None,
|
||||
np.ndarray[float, ndim=2, mode = "c"] depth_buffer not None,
|
||||
np.ndarray[int, ndim=2, mode = "c"] triangle_buffer not None,
|
||||
np.ndarray[float, ndim=2, mode = "c"] barycentric_weight not None,
|
||||
int nver, int ntri,
|
||||
int h, int w
|
||||
):
|
||||
_rasterize_triangles_core(
|
||||
<float*> np.PyArray_DATA(vertices), <int*> np.PyArray_DATA(triangles),
|
||||
<float*> np.PyArray_DATA(depth_buffer), <int*> np.PyArray_DATA(triangle_buffer), <float*> np.PyArray_DATA(barycentric_weight),
|
||||
nver, ntri,
|
||||
h, w)
|
||||
|
||||
def render_colors_core(np.ndarray[float, ndim=3, mode = "c"] image not None,
|
||||
np.ndarray[float, ndim=2, mode = "c"] vertices not None,
|
||||
np.ndarray[int, ndim=2, mode="c"] triangles not None,
|
||||
np.ndarray[float, ndim=2, mode = "c"] colors not None,
|
||||
np.ndarray[float, ndim=2, mode = "c"] depth_buffer not None,
|
||||
int nver, int ntri,
|
||||
int h, int w, int c
|
||||
):
|
||||
_render_colors_core(
|
||||
<float*> np.PyArray_DATA(image), <float*> np.PyArray_DATA(vertices), <int*> np.PyArray_DATA(triangles),
|
||||
<float*> np.PyArray_DATA(colors),
|
||||
<float*> np.PyArray_DATA(depth_buffer),
|
||||
nver, ntri,
|
||||
h, w, c)
|
||||
|
||||
def render_texture_core(np.ndarray[float, ndim=3, mode = "c"] image not None,
|
||||
np.ndarray[float, ndim=2, mode = "c"] vertices not None,
|
||||
np.ndarray[int, ndim=2, mode="c"] triangles not None,
|
||||
np.ndarray[float, ndim=3, mode = "c"] texture not None,
|
||||
np.ndarray[float, ndim=2, mode = "c"] tex_coords not None,
|
||||
np.ndarray[int, ndim=2, mode="c"] tex_triangles not None,
|
||||
np.ndarray[float, ndim=2, mode = "c"] depth_buffer not None,
|
||||
int nver, int tex_nver, int ntri,
|
||||
int h, int w, int c,
|
||||
int tex_h, int tex_w, int tex_c,
|
||||
int mapping_type
|
||||
):
|
||||
_render_texture_core(
|
||||
<float*> np.PyArray_DATA(image), <float*> np.PyArray_DATA(vertices), <int*> np.PyArray_DATA(triangles),
|
||||
<float*> np.PyArray_DATA(texture), <float*> np.PyArray_DATA(tex_coords), <int*> np.PyArray_DATA(tex_triangles),
|
||||
<float*> np.PyArray_DATA(depth_buffer),
|
||||
nver, tex_nver, ntri,
|
||||
h, w, c,
|
||||
tex_h, tex_w, tex_c,
|
||||
mapping_type)
|
||||
|
||||
def write_obj_with_colors_texture_core(string filename, string mtl_name,
|
||||
np.ndarray[float, ndim=2, mode = "c"] vertices not None,
|
||||
np.ndarray[int, ndim=2, mode="c"] triangles not None,
|
||||
np.ndarray[float, ndim=2, mode = "c"] colors not None,
|
||||
np.ndarray[float, ndim=2, mode = "c"] uv_coords not None,
|
||||
int nver, int ntri, int ntexver
|
||||
):
|
||||
_write_obj_with_colors_texture(filename, mtl_name,
|
||||
<float*> np.PyArray_DATA(vertices), <int*> np.PyArray_DATA(triangles), <float*> np.PyArray_DATA(colors), <float*> np.PyArray_DATA(uv_coords),
|
||||
nver, ntri, ntexver)
|
||||
@ -1,20 +0,0 @@
|
||||
'''
|
||||
python setup.py build_ext -i
|
||||
to compile
|
||||
'''
|
||||
|
||||
# setup.py
|
||||
from distutils.core import setup, Extension
|
||||
from Cython.Build import cythonize
|
||||
from Cython.Distutils import build_ext
|
||||
import numpy
|
||||
|
||||
setup(
|
||||
name = 'mesh_core_cython',
|
||||
cmdclass={'build_ext': build_ext},
|
||||
ext_modules=[Extension("mesh_core_cython",
|
||||
sources=["mesh_core_cython.pyx", "mesh_core.cpp"],
|
||||
language='c++',
|
||||
include_dirs=[numpy.get_include()])],
|
||||
)
|
||||
|
||||
@ -1,142 +0,0 @@
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import numpy as np
|
||||
import os
|
||||
from skimage import io
|
||||
from time import time
|
||||
|
||||
from .cython import mesh_core_cython
|
||||
|
||||
## TODO
|
||||
## TODO: c++ version
|
||||
def read_obj(obj_name):
|
||||
''' read mesh
|
||||
'''
|
||||
return 0
|
||||
|
||||
# ------------------------- write
|
||||
def write_asc(path, vertices):
|
||||
'''
|
||||
Args:
|
||||
vertices: shape = (nver, 3)
|
||||
'''
|
||||
if path.split('.')[-1] == 'asc':
|
||||
np.savetxt(path, vertices)
|
||||
else:
|
||||
np.savetxt(path + '.asc', vertices)
|
||||
|
||||
def write_obj_with_colors(obj_name, vertices, triangles, colors):
|
||||
''' Save 3D face model with texture represented by colors.
|
||||
Args:
|
||||
obj_name: str
|
||||
vertices: shape = (nver, 3)
|
||||
triangles: shape = (ntri, 3)
|
||||
colors: shape = (nver, 3)
|
||||
'''
|
||||
triangles = triangles.copy()
|
||||
triangles += 1 # meshlab start with 1
|
||||
|
||||
if obj_name.split('.')[-1] != 'obj':
|
||||
obj_name = obj_name + '.obj'
|
||||
|
||||
# write obj
|
||||
with open(obj_name, 'w') as f:
|
||||
|
||||
# write vertices & colors
|
||||
for i in range(vertices.shape[0]):
|
||||
# s = 'v {} {} {} \n'.format(vertices[0,i], vertices[1,i], vertices[2,i])
|
||||
s = 'v {} {} {} {} {} {}\n'.format(vertices[i, 0], vertices[i, 1], vertices[i, 2], colors[i, 0], colors[i, 1], colors[i, 2])
|
||||
f.write(s)
|
||||
|
||||
# write f: ver ind/ uv ind
|
||||
[k, ntri] = triangles.shape
|
||||
for i in range(triangles.shape[0]):
|
||||
# s = 'f {} {} {}\n'.format(triangles[i, 0], triangles[i, 1], triangles[i, 2])
|
||||
s = 'f {} {} {}\n'.format(triangles[i, 2], triangles[i, 1], triangles[i, 0])
|
||||
f.write(s)
|
||||
|
||||
## TODO: c++ version
|
||||
def write_obj_with_texture(obj_name, vertices, triangles, texture, uv_coords):
|
||||
''' Save 3D face model with texture represented by texture map.
|
||||
Ref: https://github.com/patrikhuber/eos/blob/bd00155ebae4b1a13b08bf5a991694d682abbada/include/eos/core/Mesh.hpp
|
||||
Args:
|
||||
obj_name: str
|
||||
vertices: shape = (nver, 3)
|
||||
triangles: shape = (ntri, 3)
|
||||
texture: shape = (256,256,3)
|
||||
uv_coords: shape = (nver, 3) max value<=1
|
||||
'''
|
||||
if obj_name.split('.')[-1] != 'obj':
|
||||
obj_name = obj_name + '.obj'
|
||||
mtl_name = obj_name.replace('.obj', '.mtl')
|
||||
texture_name = obj_name.replace('.obj', '_texture.png')
|
||||
|
||||
triangles = triangles.copy()
|
||||
triangles += 1 # mesh lab start with 1
|
||||
|
||||
# write obj
|
||||
with open(obj_name, 'w') as f:
|
||||
# first line: write mtlib(material library)
|
||||
s = "mtllib {}\n".format(os.path.abspath(mtl_name))
|
||||
f.write(s)
|
||||
|
||||
# write vertices
|
||||
for i in range(vertices.shape[0]):
|
||||
s = 'v {} {} {}\n'.format(vertices[i, 0], vertices[i, 1], vertices[i, 2])
|
||||
f.write(s)
|
||||
|
||||
# write uv coords
|
||||
for i in range(uv_coords.shape[0]):
|
||||
s = 'vt {} {}\n'.format(uv_coords[i,0], 1 - uv_coords[i,1])
|
||||
f.write(s)
|
||||
|
||||
f.write("usemtl FaceTexture\n")
|
||||
|
||||
# write f: ver ind/ uv ind
|
||||
for i in range(triangles.shape[0]):
|
||||
s = 'f {}/{} {}/{} {}/{}\n'.format(triangles[i,2], triangles[i,2], triangles[i,1], triangles[i,1], triangles[i,0], triangles[i,0])
|
||||
f.write(s)
|
||||
|
||||
# write mtl
|
||||
with open(mtl_name, 'w') as f:
|
||||
f.write("newmtl FaceTexture\n")
|
||||
s = 'map_Kd {}\n'.format(os.path.abspath(texture_name)) # map to image
|
||||
f.write(s)
|
||||
|
||||
# write texture as png
|
||||
imsave(texture_name, texture)
|
||||
|
||||
# c++ version
|
||||
def write_obj_with_colors_texture(obj_name, vertices, triangles, colors, texture, uv_coords):
|
||||
''' Save 3D face model with texture.
|
||||
Ref: https://github.com/patrikhuber/eos/blob/bd00155ebae4b1a13b08bf5a991694d682abbada/include/eos/core/Mesh.hpp
|
||||
Args:
|
||||
obj_name: str
|
||||
vertices: shape = (nver, 3)
|
||||
triangles: shape = (ntri, 3)
|
||||
colors: shape = (nver, 3)
|
||||
texture: shape = (256,256,3)
|
||||
uv_coords: shape = (nver, 3) max value<=1
|
||||
'''
|
||||
if obj_name.split('.')[-1] != 'obj':
|
||||
obj_name = obj_name + '.obj'
|
||||
mtl_name = obj_name.replace('.obj', '.mtl')
|
||||
texture_name = obj_name.replace('.obj', '_texture.png')
|
||||
|
||||
triangles = triangles.copy()
|
||||
triangles += 1 # mesh lab start with 1
|
||||
|
||||
# write obj
|
||||
vertices, colors, uv_coords = vertices.astype(np.float32).copy(), colors.astype(np.float32).copy(), uv_coords.astype(np.float32).copy()
|
||||
mesh_core_cython.write_obj_with_colors_texture_core(str.encode(obj_name), str.encode(os.path.abspath(mtl_name)), vertices, triangles, colors, uv_coords, vertices.shape[0], triangles.shape[0], uv_coords.shape[0])
|
||||
|
||||
# write mtl
|
||||
with open(mtl_name, 'w') as f:
|
||||
f.write("newmtl FaceTexture\n")
|
||||
s = 'map_Kd {}\n'.format(os.path.abspath(texture_name)) # map to image
|
||||
f.write(s)
|
||||
|
||||
# write texture as png
|
||||
io.imsave(texture_name, texture)
|
||||
@ -1,213 +0,0 @@
|
||||
'''
|
||||
Functions about lighting mesh(changing colors/texture of mesh).
|
||||
1. add light to colors/texture (shade each vertex)
|
||||
2. fit light according to colors/texture & image.
|
||||
'''
|
||||
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import numpy as np
|
||||
from .cython import mesh_core_cython
|
||||
|
||||
def get_normal(vertices, triangles):
|
||||
''' calculate normal direction in each vertex
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
triangles: [ntri, 3]
|
||||
Returns:
|
||||
normal: [nver, 3]
|
||||
'''
|
||||
pt0 = vertices[triangles[:, 0], :] # [ntri, 3]
|
||||
pt1 = vertices[triangles[:, 1], :] # [ntri, 3]
|
||||
pt2 = vertices[triangles[:, 2], :] # [ntri, 3]
|
||||
tri_normal = np.cross(pt0 - pt1, pt0 - pt2) # [ntri, 3]. normal of each triangle
|
||||
|
||||
normal = np.zeros_like(vertices, dtype = np.float32).copy() # [nver, 3]
|
||||
# for i in range(triangles.shape[0]):
|
||||
# normal[triangles[i, 0], :] = normal[triangles[i, 0], :] + tri_normal[i, :]
|
||||
# normal[triangles[i, 1], :] = normal[triangles[i, 1], :] + tri_normal[i, :]
|
||||
# normal[triangles[i, 2], :] = normal[triangles[i, 2], :] + tri_normal[i, :]
|
||||
mesh_core_cython.get_normal_core(normal, tri_normal.astype(np.float32).copy(), triangles.copy(), triangles.shape[0])
|
||||
|
||||
# normalize to unit length
|
||||
mag = np.sum(normal**2, 1) # [nver]
|
||||
zero_ind = (mag == 0)
|
||||
mag[zero_ind] = 1;
|
||||
normal[zero_ind, 0] = np.ones((np.sum(zero_ind)))
|
||||
|
||||
normal = normal/np.sqrt(mag[:,np.newaxis])
|
||||
|
||||
return normal
|
||||
|
||||
# TODO: test
|
||||
def add_light_sh(vertices, triangles, colors, sh_coeff):
|
||||
'''
|
||||
In 3d face, usually assume:
|
||||
1. The surface of face is Lambertian(reflect only the low frequencies of lighting)
|
||||
2. Lighting can be an arbitrary combination of point sources
|
||||
--> can be expressed in terms of spherical harmonics(omit the lighting coefficients)
|
||||
I = albedo * (sh(n) x sh_coeff)
|
||||
|
||||
albedo: n x 1
|
||||
sh_coeff: 9 x 1
|
||||
Y(n) = (1, n_x, n_y, n_z, n_xn_y, n_xn_z, n_yn_z, n_x^2 - n_y^2, 3n_z^2 - 1)': n x 9
|
||||
# Y(n) = (1, n_x, n_y, n_z)': n x 4
|
||||
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
triangles: [ntri, 3]
|
||||
colors: [nver, 3] albedo
|
||||
sh_coeff: [9, 1] spherical harmonics coefficients
|
||||
|
||||
Returns:
|
||||
lit_colors: [nver, 3]
|
||||
'''
|
||||
assert vertices.shape[0] == colors.shape[0]
|
||||
nver = vertices.shape[0]
|
||||
normal = get_normal(vertices, triangles) # [nver, 3]
|
||||
sh = np.array((np.ones(nver), n[:,0], n[:,1], n[:,2], n[:,0]*n[:,1], n[:,0]*n[:,2], n[:,1]*n[:,2], n[:,0]**2 - n[:,1]**2, 3*(n[:,2]**2) - 1)) # [nver, 9]
|
||||
ref = sh.dot(sh_coeff) #[nver, 1]
|
||||
lit_colors = colors*ref
|
||||
return lit_colors
|
||||
|
||||
|
||||
def add_light(vertices, triangles, colors, light_positions = 0, light_intensities = 0):
|
||||
''' Gouraud shading. add point lights.
|
||||
In 3d face, usually assume:
|
||||
1. The surface of face is Lambertian(reflect only the low frequencies of lighting)
|
||||
2. Lighting can be an arbitrary combination of point sources
|
||||
3. No specular (unless skin is oil, 23333)
|
||||
|
||||
Ref: https://cs184.eecs.berkeley.edu/lecture/pipeline
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
triangles: [ntri, 3]
|
||||
light_positions: [nlight, 3]
|
||||
light_intensities: [nlight, 3]
|
||||
Returns:
|
||||
lit_colors: [nver, 3]
|
||||
'''
|
||||
nver = vertices.shape[0]
|
||||
normals = get_normal(vertices, triangles) # [nver, 3]
|
||||
|
||||
# ambient
|
||||
# La = ka*Ia
|
||||
|
||||
# diffuse
|
||||
# Ld = kd*(I/r^2)max(0, nxl)
|
||||
direction_to_lights = vertices[np.newaxis, :, :] - light_positions[:, np.newaxis, :] # [nlight, nver, 3]
|
||||
direction_to_lights_n = np.sqrt(np.sum(direction_to_lights**2, axis = 2)) # [nlight, nver]
|
||||
direction_to_lights = direction_to_lights/direction_to_lights_n[:, :, np.newaxis]
|
||||
normals_dot_lights = normals[np.newaxis, :, :]*direction_to_lights # [nlight, nver, 3]
|
||||
normals_dot_lights = np.sum(normals_dot_lights, axis = 2) # [nlight, nver]
|
||||
diffuse_output = colors[np.newaxis, :, :]*normals_dot_lights[:, :, np.newaxis]*light_intensities[:, np.newaxis, :]
|
||||
diffuse_output = np.sum(diffuse_output, axis = 0) # [nver, 3]
|
||||
|
||||
# specular
|
||||
# h = (v + l)/(|v + l|) bisector
|
||||
# Ls = ks*(I/r^2)max(0, nxh)^p
|
||||
# increasing p narrows the reflectionlob
|
||||
|
||||
lit_colors = diffuse_output # only diffuse part here.
|
||||
lit_colors = np.minimum(np.maximum(lit_colors, 0), 1)
|
||||
return lit_colors
|
||||
|
||||
|
||||
|
||||
## TODO. estimate light(sh coeff)
|
||||
## -------------------------------- estimate. can not use now.
|
||||
def fit_light(image, vertices, colors, triangles, vis_ind, lamb = 10, max_iter = 3):
|
||||
[h, w, c] = image.shape
|
||||
|
||||
# surface normal
|
||||
norm = get_normal(vertices, triangles)
|
||||
|
||||
nver = vertices.shape[1]
|
||||
|
||||
# vertices --> corresponding image pixel
|
||||
pt2d = vertices[:2, :]
|
||||
|
||||
pt2d[0,:] = np.minimum(np.maximum(pt2d[0,:], 0), w - 1)
|
||||
pt2d[1,:] = np.minimum(np.maximum(pt2d[1,:], 0), h - 1)
|
||||
pt2d = np.round(pt2d).astype(np.int32) # 2 x nver
|
||||
|
||||
image_pixel = image[pt2d[1,:], pt2d[0,:], :] # nver x 3
|
||||
image_pixel = image_pixel.T # 3 x nver
|
||||
|
||||
# vertices --> corresponding mean texture pixel with illumination
|
||||
# Spherical Harmonic Basis
|
||||
harmonic_dim = 9
|
||||
nx = norm[0,:];
|
||||
ny = norm[1,:];
|
||||
nz = norm[2,:];
|
||||
harmonic = np.zeros((nver, harmonic_dim))
|
||||
|
||||
pi = np.pi
|
||||
harmonic[:,0] = np.sqrt(1/(4*pi)) * np.ones((nver,));
|
||||
harmonic[:,1] = np.sqrt(3/(4*pi)) * nx;
|
||||
harmonic[:,2] = np.sqrt(3/(4*pi)) * ny;
|
||||
harmonic[:,3] = np.sqrt(3/(4*pi)) * nz;
|
||||
harmonic[:,4] = 1/2. * np.sqrt(3/(4*pi)) * (2*nz**2 - nx**2 - ny**2);
|
||||
harmonic[:,5] = 3 * np.sqrt(5/(12*pi)) * (ny*nz);
|
||||
harmonic[:,6] = 3 * np.sqrt(5/(12*pi)) * (nx*nz);
|
||||
harmonic[:,7] = 3 * np.sqrt(5/(12*pi)) * (nx*ny);
|
||||
harmonic[:,8] = 3/2. * np.sqrt(5/(12*pi)) * (nx*nx - ny*ny);
|
||||
|
||||
'''
|
||||
I' = sum(albedo * lj * hj) j = 0:9 (albedo = tex)
|
||||
set A = albedo*h (n x 9)
|
||||
alpha = lj (9 x 1)
|
||||
Y = I (n x 1)
|
||||
Y' = A.dot(alpha)
|
||||
|
||||
opt function:
|
||||
||Y - A*alpha|| + lambda*(alpha'*alpha)
|
||||
result:
|
||||
A'*(Y - A*alpha) + lambda*alpha = 0
|
||||
==>
|
||||
(A'*A*alpha - lambda)*alpha = A'*Y
|
||||
left: 9 x 9
|
||||
right: 9 x 1
|
||||
'''
|
||||
n_vis_ind = len(vis_ind)
|
||||
n = n_vis_ind*c
|
||||
|
||||
Y = np.zeros((n, 1))
|
||||
A = np.zeros((n, 9))
|
||||
light = np.zeros((3, 1))
|
||||
|
||||
for k in range(c):
|
||||
Y[k*n_vis_ind:(k+1)*n_vis_ind, :] = image_pixel[k, vis_ind][:, np.newaxis]
|
||||
A[k*n_vis_ind:(k+1)*n_vis_ind, :] = texture[k, vis_ind][:, np.newaxis] * harmonic[vis_ind, :]
|
||||
Ac = texture[k, vis_ind][:, np.newaxis]
|
||||
Yc = image_pixel[k, vis_ind][:, np.newaxis]
|
||||
light[k] = (Ac.T.dot(Yc))/(Ac.T.dot(Ac))
|
||||
|
||||
for i in range(max_iter):
|
||||
|
||||
Yc = Y.copy()
|
||||
for k in range(c):
|
||||
Yc[k*n_vis_ind:(k+1)*n_vis_ind, :] /= light[k]
|
||||
|
||||
# update alpha
|
||||
equation_left = np.dot(A.T, A) + lamb*np.eye(harmonic_dim); # why + ?
|
||||
equation_right = np.dot(A.T, Yc)
|
||||
alpha = np.dot(np.linalg.inv(equation_left), equation_right)
|
||||
|
||||
# update light
|
||||
for k in range(c):
|
||||
Ac = A[k*n_vis_ind:(k+1)*n_vis_ind, :].dot(alpha)
|
||||
Yc = Y[k*n_vis_ind:(k+1)*n_vis_ind, :]
|
||||
light[k] = (Ac.T.dot(Yc))/(Ac.T.dot(Ac))
|
||||
|
||||
appearance = np.zeros_like(texture)
|
||||
for k in range(c):
|
||||
tmp = np.dot(harmonic*texture[k, :][:, np.newaxis], alpha*light[k])
|
||||
appearance[k,:] = tmp.T
|
||||
|
||||
appearance = np.minimum(np.maximum(appearance, 0), 1)
|
||||
|
||||
return appearance
|
||||
|
||||
@ -1,135 +0,0 @@
|
||||
'''
|
||||
functions about rendering mesh(from 3d obj to 2d image).
|
||||
only use rasterization render here.
|
||||
Note that:
|
||||
1. Generally, render func includes camera, light, raterize. Here no camera and light(I write these in other files)
|
||||
2. Generally, the input vertices are normalized to [-1,1] and cetered on [0, 0]. (in world space)
|
||||
Here, the vertices are using image coords, which centers on [w/2, h/2] with the y-axis pointing to oppisite direction.
|
||||
Means: render here only conducts interpolation.(I just want to make the input flexible)
|
||||
|
||||
Author: Yao Feng
|
||||
Mail: yaofeng1995@gmail.com
|
||||
'''
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import numpy as np
|
||||
from time import time
|
||||
|
||||
from .cython import mesh_core_cython
|
||||
|
||||
def rasterize_triangles(vertices, triangles, h, w):
|
||||
'''
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
triangles: [ntri, 3]
|
||||
h: height
|
||||
w: width
|
||||
Returns:
|
||||
depth_buffer: [h, w] saves the depth, here, the bigger the z, the fronter the point.
|
||||
triangle_buffer: [h, w] saves the tri id(-1 for no triangle).
|
||||
barycentric_weight: [h, w, 3] saves corresponding barycentric weight.
|
||||
|
||||
# Each triangle has 3 vertices & Each vertex has 3 coordinates x, y, z.
|
||||
# h, w is the size of rendering
|
||||
'''
|
||||
|
||||
# initial
|
||||
depth_buffer = np.zeros([h, w]) - 999999. #set the initial z to the farest position
|
||||
triangle_buffer = np.zeros([h, w], dtype = np.int32) - 1 # if tri id = -1, the pixel has no triangle correspondance
|
||||
barycentric_weight = np.zeros([h, w, 3], dtype = np.float32) #
|
||||
|
||||
vertices = vertices.astype(np.float32).copy()
|
||||
triangles = triangles.astype(np.int32).copy()
|
||||
|
||||
mesh_core_cython.rasterize_triangles_core(
|
||||
vertices, triangles,
|
||||
depth_buffer, triangle_buffer, barycentric_weight,
|
||||
vertices.shape[0], triangles.shape[0],
|
||||
h, w)
|
||||
|
||||
def render_colors(vertices, triangles, colors, h, w, c = 3, BG = None):
|
||||
''' render mesh with colors
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
triangles: [ntri, 3]
|
||||
colors: [nver, 3]
|
||||
h: height
|
||||
w: width
|
||||
c: channel
|
||||
BG: background image
|
||||
Returns:
|
||||
image: [h, w, c]. rendered image./rendering.
|
||||
'''
|
||||
|
||||
# initial
|
||||
if BG is None:
|
||||
image = np.zeros((h, w, c), dtype = np.float32)
|
||||
else:
|
||||
assert BG.shape[0] == h and BG.shape[1] == w and BG.shape[2] == c
|
||||
image = BG
|
||||
depth_buffer = np.zeros([h, w], dtype = np.float32, order = 'C') - 999999.
|
||||
|
||||
# change orders. --> C-contiguous order(column major)
|
||||
vertices = vertices.astype(np.float32).copy()
|
||||
triangles = triangles.astype(np.int32).copy()
|
||||
colors = colors.astype(np.float32).copy()
|
||||
###
|
||||
st = time()
|
||||
mesh_core_cython.render_colors_core(
|
||||
image, vertices, triangles,
|
||||
colors,
|
||||
depth_buffer,
|
||||
vertices.shape[0], triangles.shape[0],
|
||||
h, w, c)
|
||||
return image
|
||||
|
||||
|
||||
def render_texture(vertices, triangles, texture, tex_coords, tex_triangles, h, w, c = 3, mapping_type = 'nearest', BG = None):
|
||||
''' render mesh with texture map
|
||||
Args:
|
||||
vertices: [3, nver]
|
||||
triangles: [3, ntri]
|
||||
texture: [tex_h, tex_w, 3]
|
||||
tex_coords: [ntexcoords, 3]
|
||||
tex_triangles: [ntri, 3]
|
||||
h: height of rendering
|
||||
w: width of rendering
|
||||
c: channel
|
||||
mapping_type: 'bilinear' or 'nearest'
|
||||
'''
|
||||
# initial
|
||||
if BG is None:
|
||||
image = np.zeros((h, w, c), dtype = np.float32)
|
||||
else:
|
||||
assert BG.shape[0] == h and BG.shape[1] == w and BG.shape[2] == c
|
||||
image = BG
|
||||
|
||||
depth_buffer = np.zeros([h, w], dtype = np.float32, order = 'C') - 999999.
|
||||
|
||||
tex_h, tex_w, tex_c = texture.shape
|
||||
if mapping_type == 'nearest':
|
||||
mt = int(0)
|
||||
elif mapping_type == 'bilinear':
|
||||
mt = int(1)
|
||||
else:
|
||||
mt = int(0)
|
||||
|
||||
# -> C order
|
||||
vertices = vertices.astype(np.float32).copy()
|
||||
triangles = triangles.astype(np.int32).copy()
|
||||
texture = texture.astype(np.float32).copy()
|
||||
tex_coords = tex_coords.astype(np.float32).copy()
|
||||
tex_triangles = tex_triangles.astype(np.int32).copy()
|
||||
|
||||
mesh_core_cython.render_texture_core(
|
||||
image, vertices, triangles,
|
||||
texture, tex_coords, tex_triangles,
|
||||
depth_buffer,
|
||||
vertices.shape[0], tex_coords.shape[0], triangles.shape[0],
|
||||
h, w, c,
|
||||
tex_h, tex_w, tex_c,
|
||||
mt)
|
||||
return image
|
||||
|
||||
@ -1,383 +0,0 @@
|
||||
'''
|
||||
Functions about transforming mesh(changing the position: modify vertices).
|
||||
1. forward: transform(transform, camera, project).
|
||||
2. backward: estimate transform matrix from correspondences.
|
||||
|
||||
Author: Yao Feng
|
||||
Mail: yaofeng1995@gmail.com
|
||||
'''
|
||||
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import numpy as np
|
||||
import math
|
||||
from math import cos, sin
|
||||
|
||||
def angle2matrix(angles):
|
||||
''' get rotation matrix from three rotation angles(degree). right-handed.
|
||||
Args:
|
||||
angles: [3,]. x, y, z angles
|
||||
x: pitch. positive for looking down.
|
||||
y: yaw. positive for looking left.
|
||||
z: roll. positive for tilting head right.
|
||||
Returns:
|
||||
R: [3, 3]. rotation matrix.
|
||||
'''
|
||||
x, y, z = np.deg2rad(angles[0]), np.deg2rad(angles[1]), np.deg2rad(angles[2])
|
||||
# x
|
||||
Rx=np.array([[1, 0, 0],
|
||||
[0, cos(x), -sin(x)],
|
||||
[0, sin(x), cos(x)]])
|
||||
# y
|
||||
Ry=np.array([[ cos(y), 0, sin(y)],
|
||||
[ 0, 1, 0],
|
||||
[-sin(y), 0, cos(y)]])
|
||||
# z
|
||||
Rz=np.array([[cos(z), -sin(z), 0],
|
||||
[sin(z), cos(z), 0],
|
||||
[ 0, 0, 1]])
|
||||
|
||||
R=Rz.dot(Ry.dot(Rx))
|
||||
return R.astype(np.float32)
|
||||
|
||||
def angle2matrix_3ddfa(angles):
|
||||
''' get rotation matrix from three rotation angles(radian). The same as in 3DDFA.
|
||||
Args:
|
||||
angles: [3,]. x, y, z angles
|
||||
x: pitch.
|
||||
y: yaw.
|
||||
z: roll.
|
||||
Returns:
|
||||
R: 3x3. rotation matrix.
|
||||
'''
|
||||
# x, y, z = np.deg2rad(angles[0]), np.deg2rad(angles[1]), np.deg2rad(angles[2])
|
||||
x, y, z = angles[0], angles[1], angles[2]
|
||||
|
||||
# x
|
||||
Rx=np.array([[1, 0, 0],
|
||||
[0, cos(x), sin(x)],
|
||||
[0, -sin(x), cos(x)]])
|
||||
# y
|
||||
Ry=np.array([[ cos(y), 0, -sin(y)],
|
||||
[ 0, 1, 0],
|
||||
[sin(y), 0, cos(y)]])
|
||||
# z
|
||||
Rz=np.array([[cos(z), sin(z), 0],
|
||||
[-sin(z), cos(z), 0],
|
||||
[ 0, 0, 1]])
|
||||
R = Rx.dot(Ry).dot(Rz)
|
||||
return R.astype(np.float32)
|
||||
|
||||
|
||||
## ------------------------------------------ 1. transform(transform, project, camera).
|
||||
## ---------- 3d-3d transform. Transform obj in world space
|
||||
def rotate(vertices, angles):
|
||||
''' rotate vertices.
|
||||
X_new = R.dot(X). X: 3 x 1
|
||||
Args:
|
||||
vertices: [nver, 3].
|
||||
rx, ry, rz: degree angles
|
||||
rx: pitch. positive for looking down
|
||||
ry: yaw. positive for looking left
|
||||
rz: roll. positive for tilting head right
|
||||
Returns:
|
||||
rotated vertices: [nver, 3]
|
||||
'''
|
||||
R = angle2matrix(angles)
|
||||
rotated_vertices = vertices.dot(R.T)
|
||||
|
||||
return rotated_vertices
|
||||
|
||||
def similarity_transform(vertices, s, R, t3d):
|
||||
''' similarity transform. dof = 7.
|
||||
3D: s*R.dot(X) + t
|
||||
Homo: M = [[sR, t],[0^T, 1]]. M.dot(X)
|
||||
Args:(float32)
|
||||
vertices: [nver, 3].
|
||||
s: [1,]. scale factor.
|
||||
R: [3,3]. rotation matrix.
|
||||
t3d: [3,]. 3d translation vector.
|
||||
Returns:
|
||||
transformed vertices: [nver, 3]
|
||||
'''
|
||||
t3d = np.squeeze(np.array(t3d, dtype = np.float32))
|
||||
transformed_vertices = s * vertices.dot(R.T) + t3d[np.newaxis, :]
|
||||
|
||||
return transformed_vertices
|
||||
|
||||
|
||||
## -------------- Camera. from world space to camera space
|
||||
# Ref: https://cs184.eecs.berkeley.edu/lecture/transforms-2
|
||||
def normalize(x):
|
||||
epsilon = 1e-12
|
||||
norm = np.sqrt(np.sum(x**2, axis = 0))
|
||||
norm = np.maximum(norm, epsilon)
|
||||
return x/norm
|
||||
|
||||
def lookat_camera(vertices, eye, at = None, up = None):
|
||||
""" 'look at' transformation: from world space to camera space
|
||||
standard camera space:
|
||||
camera located at the origin.
|
||||
looking down negative z-axis.
|
||||
vertical vector is y-axis.
|
||||
Xcam = R(X - C)
|
||||
Homo: [[R, -RC], [0, 1]]
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
eye: [3,] the XYZ world space position of the camera.
|
||||
at: [3,] a position along the center of the camera's gaze.
|
||||
up: [3,] up direction
|
||||
Returns:
|
||||
transformed_vertices: [nver, 3]
|
||||
"""
|
||||
if at is None:
|
||||
at = np.array([0, 0, 0], np.float32)
|
||||
if up is None:
|
||||
up = np.array([0, 1, 0], np.float32)
|
||||
|
||||
eye = np.array(eye).astype(np.float32)
|
||||
at = np.array(at).astype(np.float32)
|
||||
z_aixs = -normalize(at - eye) # look forward
|
||||
x_aixs = normalize(np.cross(up, z_aixs)) # look right
|
||||
y_axis = np.cross(z_aixs, x_aixs) # look up
|
||||
|
||||
R = np.stack((x_aixs, y_axis, z_aixs))#, axis = 0) # 3 x 3
|
||||
transformed_vertices = vertices - eye # translation
|
||||
transformed_vertices = transformed_vertices.dot(R.T) # rotation
|
||||
return transformed_vertices
|
||||
|
||||
## --------- 3d-2d project. from camera space to image plane
|
||||
# generally, image plane only keeps x,y channels, here reserve z channel for calculating z-buffer.
|
||||
def orthographic_project(vertices):
|
||||
''' scaled orthographic projection(just delete z)
|
||||
assumes: variations in depth over the object is small relative to the mean distance from camera to object
|
||||
x -> x*f/z, y -> x*f/z, z -> f.
|
||||
for point i,j. zi~=zj. so just delete z
|
||||
** often used in face
|
||||
Homo: P = [[1,0,0,0], [0,1,0,0], [0,0,1,0]]
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
Returns:
|
||||
projected_vertices: [nver, 3] if isKeepZ=True. [nver, 2] if isKeepZ=False.
|
||||
'''
|
||||
return vertices.copy()
|
||||
|
||||
def perspective_project(vertices, fovy, aspect_ratio = 1., near = 0.1, far = 1000.):
|
||||
''' perspective projection.
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
fovy: vertical angular field of view. degree.
|
||||
aspect_ratio : width / height of field of view
|
||||
near : depth of near clipping plane
|
||||
far : depth of far clipping plane
|
||||
Returns:
|
||||
projected_vertices: [nver, 3]
|
||||
'''
|
||||
fovy = np.deg2rad(fovy)
|
||||
top = near*np.tan(fovy)
|
||||
bottom = -top
|
||||
right = top*aspect_ratio
|
||||
left = -right
|
||||
|
||||
#-- homo
|
||||
P = np.array([[near/right, 0, 0, 0],
|
||||
[0, near/top, 0, 0],
|
||||
[0, 0, -(far+near)/(far-near), -2*far*near/(far-near)],
|
||||
[0, 0, -1, 0]])
|
||||
vertices_homo = np.hstack((vertices, np.ones((vertices.shape[0], 1)))) # [nver, 4]
|
||||
projected_vertices = vertices_homo.dot(P.T)
|
||||
projected_vertices = projected_vertices/projected_vertices[:,3:]
|
||||
projected_vertices = projected_vertices[:,:3]
|
||||
projected_vertices[:,2] = -projected_vertices[:,2]
|
||||
|
||||
#-- non homo. only fovy
|
||||
# projected_vertices = vertices.copy()
|
||||
# projected_vertices[:,0] = -(near/right)*vertices[:,0]/vertices[:,2]
|
||||
# projected_vertices[:,1] = -(near/top)*vertices[:,1]/vertices[:,2]
|
||||
return projected_vertices
|
||||
|
||||
|
||||
def to_image(vertices, h, w, is_perspective = False):
|
||||
''' change vertices to image coord system
|
||||
3d system: XYZ, center(0, 0, 0)
|
||||
2d image: x(u), y(v). center(w/2, h/2), flip y-axis.
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
h: height of the rendering
|
||||
w : width of the rendering
|
||||
Returns:
|
||||
projected_vertices: [nver, 3]
|
||||
'''
|
||||
image_vertices = vertices.copy()
|
||||
if is_perspective:
|
||||
# if perspective, the projected vertices are normalized to [-1, 1]. so change it to image size first.
|
||||
image_vertices[:,0] = image_vertices[:,0]*w/2
|
||||
image_vertices[:,1] = image_vertices[:,1]*h/2
|
||||
# move to center of image
|
||||
image_vertices[:,0] = image_vertices[:,0] + w/2
|
||||
image_vertices[:,1] = image_vertices[:,1] + h/2
|
||||
# flip vertices along y-axis.
|
||||
image_vertices[:,1] = h - image_vertices[:,1] - 1
|
||||
return image_vertices
|
||||
|
||||
|
||||
#### -------------------------------------------2. estimate transform matrix from correspondences.
|
||||
def estimate_affine_matrix_3d23d(X, Y):
|
||||
''' Using least-squares solution
|
||||
Args:
|
||||
X: [n, 3]. 3d points(fixed)
|
||||
Y: [n, 3]. corresponding 3d points(moving). Y = PX
|
||||
Returns:
|
||||
P_Affine: (3, 4). Affine camera matrix (the third row is [0, 0, 0, 1]).
|
||||
'''
|
||||
X_homo = np.hstack((X, np.ones([X.shape[1],1]))) #n x 4
|
||||
P = np.linalg.lstsq(X_homo, Y)[0].T # Affine matrix. 3 x 4
|
||||
return P
|
||||
|
||||
def estimate_affine_matrix_3d22d(X, x):
|
||||
''' Using Golden Standard Algorithm for estimating an affine camera
|
||||
matrix P from world to image correspondences.
|
||||
See Alg.7.2. in MVGCV
|
||||
Code Ref: https://github.com/patrikhuber/eos/blob/master/include/eos/fitting/affine_camera_estimation.hpp
|
||||
x_homo = X_homo.dot(P_Affine)
|
||||
Args:
|
||||
X: [n, 3]. corresponding 3d points(fixed)
|
||||
x: [n, 2]. n>=4. 2d points(moving). x = PX
|
||||
Returns:
|
||||
P_Affine: [3, 4]. Affine camera matrix
|
||||
'''
|
||||
X = X.T; x = x.T
|
||||
assert(x.shape[1] == X.shape[1])
|
||||
n = x.shape[1]
|
||||
assert(n >= 4)
|
||||
|
||||
#--- 1. normalization
|
||||
# 2d points
|
||||
mean = np.mean(x, 1) # (2,)
|
||||
x = x - np.tile(mean[:, np.newaxis], [1, n])
|
||||
average_norm = np.mean(np.sqrt(np.sum(x**2, 0)))
|
||||
scale = np.sqrt(2) / average_norm
|
||||
x = scale * x
|
||||
|
||||
T = np.zeros((3,3), dtype = np.float32)
|
||||
T[0, 0] = T[1, 1] = scale
|
||||
T[:2, 2] = -mean*scale
|
||||
T[2, 2] = 1
|
||||
|
||||
# 3d points
|
||||
X_homo = np.vstack((X, np.ones((1, n))))
|
||||
mean = np.mean(X, 1) # (3,)
|
||||
X = X - np.tile(mean[:, np.newaxis], [1, n])
|
||||
m = X_homo[:3,:] - X
|
||||
average_norm = np.mean(np.sqrt(np.sum(X**2, 0)))
|
||||
scale = np.sqrt(3) / average_norm
|
||||
X = scale * X
|
||||
|
||||
U = np.zeros((4,4), dtype = np.float32)
|
||||
U[0, 0] = U[1, 1] = U[2, 2] = scale
|
||||
U[:3, 3] = -mean*scale
|
||||
U[3, 3] = 1
|
||||
|
||||
# --- 2. equations
|
||||
A = np.zeros((n*2, 8), dtype = np.float32);
|
||||
X_homo = np.vstack((X, np.ones((1, n)))).T
|
||||
A[:n, :4] = X_homo
|
||||
A[n:, 4:] = X_homo
|
||||
b = np.reshape(x, [-1, 1])
|
||||
|
||||
# --- 3. solution
|
||||
p_8 = np.linalg.pinv(A).dot(b)
|
||||
P = np.zeros((3, 4), dtype = np.float32)
|
||||
P[0, :] = p_8[:4, 0]
|
||||
P[1, :] = p_8[4:, 0]
|
||||
P[-1, -1] = 1
|
||||
|
||||
# --- 4. denormalization
|
||||
P_Affine = np.linalg.inv(T).dot(P.dot(U))
|
||||
return P_Affine
|
||||
|
||||
def P2sRt(P):
|
||||
''' decompositing camera matrix P
|
||||
Args:
|
||||
P: (3, 4). Affine Camera Matrix.
|
||||
Returns:
|
||||
s: scale factor.
|
||||
R: (3, 3). rotation matrix.
|
||||
t: (3,). translation.
|
||||
'''
|
||||
t = P[:, 3]
|
||||
R1 = P[0:1, :3]
|
||||
R2 = P[1:2, :3]
|
||||
s = (np.linalg.norm(R1) + np.linalg.norm(R2))/2.0
|
||||
r1 = R1/np.linalg.norm(R1)
|
||||
r2 = R2/np.linalg.norm(R2)
|
||||
r3 = np.cross(r1, r2)
|
||||
|
||||
R = np.concatenate((r1, r2, r3), 0)
|
||||
return s, R, t
|
||||
|
||||
#Ref: https://www.learnopencv.com/rotation-matrix-to-euler-angles/
|
||||
def isRotationMatrix(R):
|
||||
''' checks if a matrix is a valid rotation matrix(whether orthogonal or not)
|
||||
'''
|
||||
Rt = np.transpose(R)
|
||||
shouldBeIdentity = np.dot(Rt, R)
|
||||
I = np.identity(3, dtype = R.dtype)
|
||||
n = np.linalg.norm(I - shouldBeIdentity)
|
||||
return n < 1e-6
|
||||
|
||||
def matrix2angle(R):
|
||||
''' get three Euler angles from Rotation Matrix
|
||||
Args:
|
||||
R: (3,3). rotation matrix
|
||||
Returns:
|
||||
x: pitch
|
||||
y: yaw
|
||||
z: roll
|
||||
'''
|
||||
assert(isRotationMatrix)
|
||||
sy = math.sqrt(R[0,0] * R[0,0] + R[1,0] * R[1,0])
|
||||
|
||||
singular = sy < 1e-6
|
||||
|
||||
if not singular :
|
||||
x = math.atan2(R[2,1] , R[2,2])
|
||||
y = math.atan2(-R[2,0], sy)
|
||||
z = math.atan2(R[1,0], R[0,0])
|
||||
else :
|
||||
x = math.atan2(-R[1,2], R[1,1])
|
||||
y = math.atan2(-R[2,0], sy)
|
||||
z = 0
|
||||
|
||||
# rx, ry, rz = np.rad2deg(x), np.rad2deg(y), np.rad2deg(z)
|
||||
rx, ry, rz = x*180/np.pi, y*180/np.pi, z*180/np.pi
|
||||
return rx, ry, rz
|
||||
|
||||
# def matrix2angle(R):
|
||||
# ''' compute three Euler angles from a Rotation Matrix. Ref: http://www.gregslabaugh.net/publications/euler.pdf
|
||||
# Args:
|
||||
# R: (3,3). rotation matrix
|
||||
# Returns:
|
||||
# x: yaw
|
||||
# y: pitch
|
||||
# z: roll
|
||||
# '''
|
||||
# # assert(isRotationMatrix(R))
|
||||
|
||||
# if R[2,0] !=1 or R[2,0] != -1:
|
||||
# x = math.asin(R[2,0])
|
||||
# y = math.atan2(R[2,1]/cos(x), R[2,2]/cos(x))
|
||||
# z = math.atan2(R[1,0]/cos(x), R[0,0]/cos(x))
|
||||
|
||||
# else:# Gimbal lock
|
||||
# z = 0 #can be anything
|
||||
# if R[2,0] == -1:
|
||||
# x = np.pi/2
|
||||
# y = z + math.atan2(R[0,1], R[0,2])
|
||||
# else:
|
||||
# x = -np.pi/2
|
||||
# y = -z + math.atan2(-R[0,1], -R[0,2])
|
||||
|
||||
# return x, y, z
|
||||
@ -1,24 +0,0 @@
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
from skimage import measure
|
||||
from mpl_toolkits.mplot3d import Axes3D
|
||||
|
||||
def plot_mesh(vertices, triangles, subplot = [1,1,1], title = 'mesh', el = 90, az = -90, lwdt=.1, dist = 6, color = "grey"):
|
||||
'''
|
||||
plot the mesh
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
triangles: [ntri, 3]
|
||||
'''
|
||||
ax = plt.subplot(subplot[0], subplot[1], subplot[2], projection = '3d')
|
||||
ax.plot_trisurf(vertices[:, 0], vertices[:, 1], vertices[:, 2], triangles = triangles, lw = lwdt, color = color, alpha = 1)
|
||||
ax.axis("off")
|
||||
ax.view_init(elev = el, azim = az)
|
||||
ax.dist = dist
|
||||
plt.title(title)
|
||||
|
||||
### -------------- Todo: use vtk to visualize mesh? or visvis? or VisPy?
|
||||
@ -1,10 +0,0 @@
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
from . import io
|
||||
from . import vis
|
||||
from . import transform
|
||||
from . import light
|
||||
from . import render
|
||||
|
||||
@ -1,170 +0,0 @@
|
||||
''' io: read&write mesh
|
||||
1. read obj as array(TODO)
|
||||
2. write arrays to obj
|
||||
|
||||
Preparation knowledge:
|
||||
representations of 3d face: mesh, point cloud...
|
||||
storage format: obj, ply, bin, asc, mat...
|
||||
'''
|
||||
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import numpy as np
|
||||
import os
|
||||
from skimage import io
|
||||
|
||||
## TODO
|
||||
## TODO: c++ version
|
||||
def read_obj(obj_name):
|
||||
''' read mesh
|
||||
'''
|
||||
return 0
|
||||
|
||||
# ------------------------- write
|
||||
def write_asc(path, vertices):
|
||||
'''
|
||||
Args:
|
||||
vertices: shape = (nver, 3)
|
||||
'''
|
||||
if path.split('.')[-1] == 'asc':
|
||||
np.savetxt(path, vertices)
|
||||
else:
|
||||
np.savetxt(path + '.asc', vertices)
|
||||
|
||||
def write_obj_with_colors(obj_name, vertices, triangles, colors):
|
||||
''' Save 3D face model with texture represented by colors.
|
||||
Args:
|
||||
obj_name: str
|
||||
vertices: shape = (nver, 3)
|
||||
triangles: shape = (ntri, 3)
|
||||
colors: shape = (nver, 3)
|
||||
'''
|
||||
triangles = triangles.copy()
|
||||
triangles += 1 # meshlab start with 1
|
||||
|
||||
if obj_name.split('.')[-1] != 'obj':
|
||||
obj_name = obj_name + '.obj'
|
||||
|
||||
# write obj
|
||||
with open(obj_name, 'w') as f:
|
||||
|
||||
# write vertices & colors
|
||||
for i in range(vertices.shape[0]):
|
||||
# s = 'v {} {} {} \n'.format(vertices[0,i], vertices[1,i], vertices[2,i])
|
||||
s = 'v {} {} {} {} {} {}\n'.format(vertices[i, 0], vertices[i, 1], vertices[i, 2], colors[i, 0], colors[i, 1], colors[i, 2])
|
||||
f.write(s)
|
||||
|
||||
# write f: ver ind/ uv ind
|
||||
[k, ntri] = triangles.shape
|
||||
for i in range(triangles.shape[0]):
|
||||
# s = 'f {} {} {}\n'.format(triangles[i, 0], triangles[i, 1], triangles[i, 2])
|
||||
s = 'f {} {} {}\n'.format(triangles[i, 2], triangles[i, 1], triangles[i, 0])
|
||||
f.write(s)
|
||||
|
||||
## TODO: c++ version
|
||||
def write_obj_with_texture(obj_name, vertices, triangles, texture, uv_coords):
|
||||
''' Save 3D face model with texture represented by texture map.
|
||||
Ref: https://github.com/patrikhuber/eos/blob/bd00155ebae4b1a13b08bf5a991694d682abbada/include/eos/core/Mesh.hpp
|
||||
Args:
|
||||
obj_name: str
|
||||
vertices: shape = (nver, 3)
|
||||
triangles: shape = (ntri, 3)
|
||||
texture: shape = (256,256,3)
|
||||
uv_coords: shape = (nver, 3) max value<=1
|
||||
'''
|
||||
if obj_name.split('.')[-1] != 'obj':
|
||||
obj_name = obj_name + '.obj'
|
||||
mtl_name = obj_name.replace('.obj', '.mtl')
|
||||
texture_name = obj_name.replace('.obj', '_texture.png')
|
||||
|
||||
triangles = triangles.copy()
|
||||
triangles += 1 # mesh lab start with 1
|
||||
|
||||
# write obj
|
||||
with open(obj_name, 'w') as f:
|
||||
# first line: write mtlib(material library)
|
||||
s = "mtllib {}\n".format(os.path.abspath(mtl_name))
|
||||
f.write(s)
|
||||
|
||||
# write vertices
|
||||
for i in range(vertices.shape[0]):
|
||||
s = 'v {} {} {}\n'.format(vertices[i, 0], vertices[i, 1], vertices[i, 2])
|
||||
f.write(s)
|
||||
|
||||
# write uv coords
|
||||
for i in range(uv_coords.shape[0]):
|
||||
# s = 'vt {} {}\n'.format(uv_coords[i,0], 1 - uv_coords[i,1])
|
||||
s = 'vt {} {}\n'.format(uv_coords[i,0], uv_coords[i,1])
|
||||
f.write(s)
|
||||
|
||||
f.write("usemtl FaceTexture\n")
|
||||
|
||||
# write f: ver ind/ uv ind
|
||||
for i in range(triangles.shape[0]):
|
||||
s = 'f {}/{} {}/{} {}/{}\n'.format(triangles[i,2], triangles[i,2], triangles[i,1], triangles[i,1], triangles[i,0], triangles[i,0])
|
||||
f.write(s)
|
||||
|
||||
# write mtl
|
||||
with open(mtl_name, 'w') as f:
|
||||
f.write("newmtl FaceTexture\n")
|
||||
s = 'map_Kd {}\n'.format(os.path.abspath(texture_name)) # map to image
|
||||
f.write(s)
|
||||
|
||||
# write texture as png
|
||||
imsave(texture_name, texture)
|
||||
|
||||
|
||||
def write_obj_with_colors_texture(obj_name, vertices, triangles, colors, texture, uv_coords):
|
||||
''' Save 3D face model with texture.
|
||||
Ref: https://github.com/patrikhuber/eos/blob/bd00155ebae4b1a13b08bf5a991694d682abbada/include/eos/core/Mesh.hpp
|
||||
Args:
|
||||
obj_name: str
|
||||
vertices: shape = (nver, 3)
|
||||
triangles: shape = (ntri, 3)
|
||||
colors: shape = (nver, 3)
|
||||
texture: shape = (256,256,3)
|
||||
uv_coords: shape = (nver, 3) max value<=1
|
||||
'''
|
||||
if obj_name.split('.')[-1] != 'obj':
|
||||
obj_name = obj_name + '.obj'
|
||||
mtl_name = obj_name.replace('.obj', '.mtl')
|
||||
texture_name = obj_name.replace('.obj', '_texture.png')
|
||||
|
||||
triangles = triangles.copy()
|
||||
triangles += 1 # mesh lab start with 1
|
||||
|
||||
# write obj
|
||||
with open(obj_name, 'w') as f:
|
||||
# first line: write mtlib(material library)
|
||||
s = "mtllib {}\n".format(os.path.abspath(mtl_name))
|
||||
f.write(s)
|
||||
|
||||
# write vertices
|
||||
for i in range(vertices.shape[0]):
|
||||
s = 'v {} {} {} {} {} {}\n'.format(vertices[i, 0], vertices[i, 1], vertices[i, 2], colors[i, 0], colors[i, 1], colors[i, 2])
|
||||
f.write(s)
|
||||
|
||||
# write uv coords
|
||||
for i in range(uv_coords.shape[0]):
|
||||
# s = 'vt {} {}\n'.format(uv_coords[i,0], 1 - uv_coords[i,1])
|
||||
s = 'vt {} {}\n'.format(uv_coords[i,0], uv_coords[i,1])
|
||||
f.write(s)
|
||||
|
||||
f.write("usemtl FaceTexture\n")
|
||||
|
||||
# write f: ver ind/ uv ind
|
||||
for i in range(triangles.shape[0]):
|
||||
# s = 'f {}/{} {}/{} {}/{}\n'.format(triangles[i,0], triangles[i,0], triangles[i,1], triangles[i,1], triangles[i,2], triangles[i,2])
|
||||
s = 'f {}/{} {}/{} {}/{}\n'.format(triangles[i,2], triangles[i,2], triangles[i,1], triangles[i,1], triangles[i,0], triangles[i,0])
|
||||
f.write(s)
|
||||
|
||||
# write mtl
|
||||
with open(mtl_name, 'w') as f:
|
||||
f.write("newmtl FaceTexture\n")
|
||||
s = 'map_Kd {}\n'.format(os.path.abspath(texture_name)) # map to image
|
||||
f.write(s)
|
||||
|
||||
# write texture as png
|
||||
io.imsave(texture_name, texture)
|
||||
@ -1,215 +0,0 @@
|
||||
'''
|
||||
Functions about lighting mesh(changing colors/texture of mesh).
|
||||
1. add light to colors/texture (shade each vertex)
|
||||
2. fit light according to colors/texture & image.
|
||||
|
||||
Preparation knowledge:
|
||||
lighting: https://cs184.eecs.berkeley.edu/lecture/pipeline
|
||||
spherical harmonics in human face: '3D Face Reconstruction from a Single Image Using a Single Reference Face Shape'
|
||||
'''
|
||||
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import numpy as np
|
||||
|
||||
def get_normal(vertices, triangles):
|
||||
''' calculate normal direction in each vertex
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
triangles: [ntri, 3]
|
||||
Returns:
|
||||
normal: [nver, 3]
|
||||
'''
|
||||
pt0 = vertices[triangles[:, 0], :] # [ntri, 3]
|
||||
pt1 = vertices[triangles[:, 1], :] # [ntri, 3]
|
||||
pt2 = vertices[triangles[:, 2], :] # [ntri, 3]
|
||||
tri_normal = np.cross(pt0 - pt1, pt0 - pt2) # [ntri, 3]. normal of each triangle
|
||||
|
||||
normal = np.zeros_like(vertices) # [nver, 3]
|
||||
for i in range(triangles.shape[0]):
|
||||
normal[triangles[i, 0], :] = normal[triangles[i, 0], :] + tri_normal[i, :]
|
||||
normal[triangles[i, 1], :] = normal[triangles[i, 1], :] + tri_normal[i, :]
|
||||
normal[triangles[i, 2], :] = normal[triangles[i, 2], :] + tri_normal[i, :]
|
||||
|
||||
# normalize to unit length
|
||||
mag = np.sum(normal**2, 1) # [nver]
|
||||
zero_ind = (mag == 0)
|
||||
mag[zero_ind] = 1;
|
||||
normal[zero_ind, 0] = np.ones((np.sum(zero_ind)))
|
||||
|
||||
normal = normal/np.sqrt(mag[:,np.newaxis])
|
||||
|
||||
return normal
|
||||
|
||||
# TODO: test
|
||||
def add_light_sh(vertices, triangles, colors, sh_coeff):
|
||||
'''
|
||||
In 3d face, usually assume:
|
||||
1. The surface of face is Lambertian(reflect only the low frequencies of lighting)
|
||||
2. Lighting can be an arbitrary combination of point sources
|
||||
--> can be expressed in terms of spherical harmonics(omit the lighting coefficients)
|
||||
I = albedo * (sh(n) x sh_coeff)
|
||||
|
||||
albedo: n x 1
|
||||
sh_coeff: 9 x 1
|
||||
Y(n) = (1, n_x, n_y, n_z, n_xn_y, n_xn_z, n_yn_z, n_x^2 - n_y^2, 3n_z^2 - 1)': n x 9
|
||||
# Y(n) = (1, n_x, n_y, n_z)': n x 4
|
||||
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
triangles: [ntri, 3]
|
||||
colors: [nver, 3] albedo
|
||||
sh_coeff: [9, 1] spherical harmonics coefficients
|
||||
|
||||
Returns:
|
||||
lit_colors: [nver, 3]
|
||||
'''
|
||||
assert vertices.shape[0] == colors.shape[0]
|
||||
nver = vertices.shape[0]
|
||||
normal = get_normal(vertices, triangles) # [nver, 3]
|
||||
sh = np.array((np.ones(nver), n[:,0], n[:,1], n[:,2], n[:,0]*n[:,1], n[:,0]*n[:,2], n[:,1]*n[:,2], n[:,0]**2 - n[:,1]**2, 3*(n[:,2]**2) - 1)) # [nver, 9]
|
||||
ref = sh.dot(sh_coeff) #[nver, 1]
|
||||
lit_colors = colors*ref
|
||||
return lit_colors
|
||||
|
||||
|
||||
def add_light(vertices, triangles, colors, light_positions = 0, light_intensities = 0):
|
||||
''' Gouraud shading. add point lights.
|
||||
In 3d face, usually assume:
|
||||
1. The surface of face is Lambertian(reflect only the low frequencies of lighting)
|
||||
2. Lighting can be an arbitrary combination of point sources
|
||||
3. No specular (unless skin is oil, 23333)
|
||||
|
||||
Ref: https://cs184.eecs.berkeley.edu/lecture/pipeline
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
triangles: [ntri, 3]
|
||||
light_positions: [nlight, 3]
|
||||
light_intensities: [nlight, 3]
|
||||
Returns:
|
||||
lit_colors: [nver, 3]
|
||||
'''
|
||||
nver = vertices.shape[0]
|
||||
normals = get_normal(vertices, triangles) # [nver, 3]
|
||||
|
||||
# ambient
|
||||
# La = ka*Ia
|
||||
|
||||
# diffuse
|
||||
# Ld = kd*(I/r^2)max(0, nxl)
|
||||
direction_to_lights = vertices[np.newaxis, :, :] - light_positions[:, np.newaxis, :] # [nlight, nver, 3]
|
||||
direction_to_lights_n = np.sqrt(np.sum(direction_to_lights**2, axis = 2)) # [nlight, nver]
|
||||
direction_to_lights = direction_to_lights/direction_to_lights_n[:, :, np.newaxis]
|
||||
normals_dot_lights = normals[np.newaxis, :, :]*direction_to_lights # [nlight, nver, 3]
|
||||
normals_dot_lights = np.sum(normals_dot_lights, axis = 2) # [nlight, nver]
|
||||
diffuse_output = colors[np.newaxis, :, :]*normals_dot_lights[:, :, np.newaxis]*light_intensities[:, np.newaxis, :]
|
||||
diffuse_output = np.sum(diffuse_output, axis = 0) # [nver, 3]
|
||||
|
||||
# specular
|
||||
# h = (v + l)/(|v + l|) bisector
|
||||
# Ls = ks*(I/r^2)max(0, nxh)^p
|
||||
# increasing p narrows the reflectionlob
|
||||
|
||||
lit_colors = diffuse_output # only diffuse part here.
|
||||
lit_colors = np.minimum(np.maximum(lit_colors, 0), 1)
|
||||
return lit_colors
|
||||
|
||||
|
||||
|
||||
## TODO. estimate light(sh coeff)
|
||||
## -------------------------------- estimate. can not use now.
|
||||
def fit_light(image, vertices, colors, triangles, vis_ind, lamb = 10, max_iter = 3):
|
||||
[h, w, c] = image.shape
|
||||
|
||||
# surface normal
|
||||
norm = get_normal(vertices, triangles)
|
||||
|
||||
nver = vertices.shape[1]
|
||||
|
||||
# vertices --> corresponding image pixel
|
||||
pt2d = vertices[:2, :]
|
||||
|
||||
pt2d[0,:] = np.minimum(np.maximum(pt2d[0,:], 0), w - 1)
|
||||
pt2d[1,:] = np.minimum(np.maximum(pt2d[1,:], 0), h - 1)
|
||||
pt2d = np.round(pt2d).astype(np.int32) # 2 x nver
|
||||
|
||||
image_pixel = image[pt2d[1,:], pt2d[0,:], :] # nver x 3
|
||||
image_pixel = image_pixel.T # 3 x nver
|
||||
|
||||
# vertices --> corresponding mean texture pixel with illumination
|
||||
# Spherical Harmonic Basis
|
||||
harmonic_dim = 9
|
||||
nx = norm[0,:];
|
||||
ny = norm[1,:];
|
||||
nz = norm[2,:];
|
||||
harmonic = np.zeros((nver, harmonic_dim))
|
||||
|
||||
pi = np.pi
|
||||
harmonic[:,0] = np.sqrt(1/(4*pi)) * np.ones((nver,));
|
||||
harmonic[:,1] = np.sqrt(3/(4*pi)) * nx;
|
||||
harmonic[:,2] = np.sqrt(3/(4*pi)) * ny;
|
||||
harmonic[:,3] = np.sqrt(3/(4*pi)) * nz;
|
||||
harmonic[:,4] = 1/2. * np.sqrt(3/(4*pi)) * (2*nz**2 - nx**2 - ny**2);
|
||||
harmonic[:,5] = 3 * np.sqrt(5/(12*pi)) * (ny*nz);
|
||||
harmonic[:,6] = 3 * np.sqrt(5/(12*pi)) * (nx*nz);
|
||||
harmonic[:,7] = 3 * np.sqrt(5/(12*pi)) * (nx*ny);
|
||||
harmonic[:,8] = 3/2. * np.sqrt(5/(12*pi)) * (nx*nx - ny*ny);
|
||||
|
||||
'''
|
||||
I' = sum(albedo * lj * hj) j = 0:9 (albedo = tex)
|
||||
set A = albedo*h (n x 9)
|
||||
alpha = lj (9 x 1)
|
||||
Y = I (n x 1)
|
||||
Y' = A.dot(alpha)
|
||||
|
||||
opt function:
|
||||
||Y - A*alpha|| + lambda*(alpha'*alpha)
|
||||
result:
|
||||
A'*(Y - A*alpha) + lambda*alpha = 0
|
||||
==>
|
||||
(A'*A*alpha - lambda)*alpha = A'*Y
|
||||
left: 9 x 9
|
||||
right: 9 x 1
|
||||
'''
|
||||
n_vis_ind = len(vis_ind)
|
||||
n = n_vis_ind*c
|
||||
|
||||
Y = np.zeros((n, 1))
|
||||
A = np.zeros((n, 9))
|
||||
light = np.zeros((3, 1))
|
||||
|
||||
for k in range(c):
|
||||
Y[k*n_vis_ind:(k+1)*n_vis_ind, :] = image_pixel[k, vis_ind][:, np.newaxis]
|
||||
A[k*n_vis_ind:(k+1)*n_vis_ind, :] = texture[k, vis_ind][:, np.newaxis] * harmonic[vis_ind, :]
|
||||
Ac = texture[k, vis_ind][:, np.newaxis]
|
||||
Yc = image_pixel[k, vis_ind][:, np.newaxis]
|
||||
light[k] = (Ac.T.dot(Yc))/(Ac.T.dot(Ac))
|
||||
|
||||
for i in range(max_iter):
|
||||
|
||||
Yc = Y.copy()
|
||||
for k in range(c):
|
||||
Yc[k*n_vis_ind:(k+1)*n_vis_ind, :] /= light[k]
|
||||
|
||||
# update alpha
|
||||
equation_left = np.dot(A.T, A) + lamb*np.eye(harmonic_dim); # why + ?
|
||||
equation_right = np.dot(A.T, Yc)
|
||||
alpha = np.dot(np.linalg.inv(equation_left), equation_right)
|
||||
|
||||
# update light
|
||||
for k in range(c):
|
||||
Ac = A[k*n_vis_ind:(k+1)*n_vis_ind, :].dot(alpha)
|
||||
Yc = Y[k*n_vis_ind:(k+1)*n_vis_ind, :]
|
||||
light[k] = (Ac.T.dot(Yc))/(Ac.T.dot(Ac))
|
||||
|
||||
appearance = np.zeros_like(texture)
|
||||
for k in range(c):
|
||||
tmp = np.dot(harmonic*texture[k, :][:, np.newaxis], alpha*light[k])
|
||||
appearance[k,:] = tmp.T
|
||||
|
||||
appearance = np.minimum(np.maximum(appearance, 0), 1)
|
||||
|
||||
return appearance
|
||||
|
||||
@ -1,287 +0,0 @@
|
||||
'''
|
||||
functions about rendering mesh(from 3d obj to 2d image).
|
||||
only use rasterization render here.
|
||||
Note that:
|
||||
1. Generally, render func includes camera, light, raterize. Here no camera and light(I write these in other files)
|
||||
2. Generally, the input vertices are normalized to [-1,1] and cetered on [0, 0]. (in world space)
|
||||
Here, the vertices are using image coords, which centers on [w/2, h/2] with the y-axis pointing to oppisite direction.
|
||||
Means: render here only conducts interpolation.(I just want to make the input flexible)
|
||||
|
||||
Preparation knowledge:
|
||||
z-buffer: https://cs184.eecs.berkeley.edu/lecture/pipeline
|
||||
|
||||
Author: Yao Feng
|
||||
Mail: yaofeng1995@gmail.com
|
||||
'''
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import numpy as np
|
||||
from time import time
|
||||
|
||||
def isPointInTri(point, tri_points):
|
||||
''' Judge whether the point is in the triangle
|
||||
Method:
|
||||
http://blackpawn.com/texts/pointinpoly/
|
||||
Args:
|
||||
point: (2,). [u, v] or [x, y]
|
||||
tri_points: (3 vertices, 2 coords). three vertices(2d points) of a triangle.
|
||||
Returns:
|
||||
bool: true for in triangle
|
||||
'''
|
||||
tp = tri_points
|
||||
|
||||
# vectors
|
||||
v0 = tp[2,:] - tp[0,:]
|
||||
v1 = tp[1,:] - tp[0,:]
|
||||
v2 = point - tp[0,:]
|
||||
|
||||
# dot products
|
||||
dot00 = np.dot(v0.T, v0)
|
||||
dot01 = np.dot(v0.T, v1)
|
||||
dot02 = np.dot(v0.T, v2)
|
||||
dot11 = np.dot(v1.T, v1)
|
||||
dot12 = np.dot(v1.T, v2)
|
||||
|
||||
# barycentric coordinates
|
||||
if dot00*dot11 - dot01*dot01 == 0:
|
||||
inverDeno = 0
|
||||
else:
|
||||
inverDeno = 1/(dot00*dot11 - dot01*dot01)
|
||||
|
||||
u = (dot11*dot02 - dot01*dot12)*inverDeno
|
||||
v = (dot00*dot12 - dot01*dot02)*inverDeno
|
||||
|
||||
# check if point in triangle
|
||||
return (u >= 0) & (v >= 0) & (u + v < 1)
|
||||
|
||||
def get_point_weight(point, tri_points):
|
||||
''' Get the weights of the position
|
||||
Methods: https://gamedev.stackexchange.com/questions/23743/whats-the-most-efficient-way-to-find-barycentric-coordinates
|
||||
-m1.compute the area of the triangles formed by embedding the point P inside the triangle
|
||||
-m2.Christer Ericson's book "Real-Time Collision Detection". faster.(used)
|
||||
Args:
|
||||
point: (2,). [u, v] or [x, y]
|
||||
tri_points: (3 vertices, 2 coords). three vertices(2d points) of a triangle.
|
||||
Returns:
|
||||
w0: weight of v0
|
||||
w1: weight of v1
|
||||
w2: weight of v3
|
||||
'''
|
||||
tp = tri_points
|
||||
# vectors
|
||||
v0 = tp[2,:] - tp[0,:]
|
||||
v1 = tp[1,:] - tp[0,:]
|
||||
v2 = point - tp[0,:]
|
||||
|
||||
# dot products
|
||||
dot00 = np.dot(v0.T, v0)
|
||||
dot01 = np.dot(v0.T, v1)
|
||||
dot02 = np.dot(v0.T, v2)
|
||||
dot11 = np.dot(v1.T, v1)
|
||||
dot12 = np.dot(v1.T, v2)
|
||||
|
||||
# barycentric coordinates
|
||||
if dot00*dot11 - dot01*dot01 == 0:
|
||||
inverDeno = 0
|
||||
else:
|
||||
inverDeno = 1/(dot00*dot11 - dot01*dot01)
|
||||
|
||||
u = (dot11*dot02 - dot01*dot12)*inverDeno
|
||||
v = (dot00*dot12 - dot01*dot02)*inverDeno
|
||||
|
||||
w0 = 1 - u - v
|
||||
w1 = v
|
||||
w2 = u
|
||||
|
||||
return w0, w1, w2
|
||||
|
||||
def rasterize_triangles(vertices, triangles, h, w):
|
||||
'''
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
triangles: [ntri, 3]
|
||||
h: height
|
||||
w: width
|
||||
Returns:
|
||||
depth_buffer: [h, w] saves the depth, here, the bigger the z, the fronter the point.
|
||||
triangle_buffer: [h, w] saves the tri id(-1 for no triangle).
|
||||
barycentric_weight: [h, w, 3] saves corresponding barycentric weight.
|
||||
|
||||
# Each triangle has 3 vertices & Each vertex has 3 coordinates x, y, z.
|
||||
# h, w is the size of rendering
|
||||
'''
|
||||
# initial
|
||||
depth_buffer = np.zeros([h, w]) - 999999. #+ np.min(vertices[2,:]) - 999999. # set the initial z to the farest position
|
||||
triangle_buffer = np.zeros([h, w], dtype = np.int32) - 1 # if tri id = -1, the pixel has no triangle correspondance
|
||||
barycentric_weight = np.zeros([h, w, 3], dtype = np.float32) #
|
||||
|
||||
for i in range(triangles.shape[0]):
|
||||
tri = triangles[i, :] # 3 vertex indices
|
||||
|
||||
# the inner bounding box
|
||||
umin = max(int(np.ceil(np.min(vertices[tri, 0]))), 0)
|
||||
umax = min(int(np.floor(np.max(vertices[tri, 0]))), w-1)
|
||||
|
||||
vmin = max(int(np.ceil(np.min(vertices[tri, 1]))), 0)
|
||||
vmax = min(int(np.floor(np.max(vertices[tri, 1]))), h-1)
|
||||
|
||||
if umax<umin or vmax<vmin:
|
||||
continue
|
||||
|
||||
for u in range(umin, umax+1):
|
||||
for v in range(vmin, vmax+1):
|
||||
if not isPointInTri([u,v], vertices[tri, :2]):
|
||||
continue
|
||||
w0, w1, w2 = get_point_weight([u, v], vertices[tri, :2]) # barycentric weight
|
||||
point_depth = w0*vertices[tri[0], 2] + w1*vertices[tri[1], 2] + w2*vertices[tri[2], 2]
|
||||
if point_depth > depth_buffer[v, u]:
|
||||
depth_buffer[v, u] = point_depth
|
||||
triangle_buffer[v, u] = i
|
||||
barycentric_weight[v, u, :] = np.array([w0, w1, w2])
|
||||
|
||||
return depth_buffer, triangle_buffer, barycentric_weight
|
||||
|
||||
|
||||
def render_colors_ras(vertices, triangles, colors, h, w, c = 3):
|
||||
''' render mesh with colors(rasterize triangle first)
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
triangles: [ntri, 3]
|
||||
colors: [nver, 3]
|
||||
h: height
|
||||
w: width
|
||||
c: channel
|
||||
Returns:
|
||||
image: [h, w, c]. rendering.
|
||||
'''
|
||||
assert vertices.shape[0] == colors.shape[0]
|
||||
|
||||
depth_buffer, triangle_buffer, barycentric_weight = rasterize_triangles(vertices, triangles, h, w)
|
||||
|
||||
triangle_buffer_flat = np.reshape(triangle_buffer, [-1]) # [h*w]
|
||||
barycentric_weight_flat = np.reshape(barycentric_weight, [-1, c]) #[h*w, c]
|
||||
weight = barycentric_weight_flat[:, :, np.newaxis] # [h*w, 3(ver in tri), 1]
|
||||
|
||||
colors_flat = colors[triangles[triangle_buffer_flat, :], :] # [h*w(tri id in pixel), 3(ver in tri), c(color in ver)]
|
||||
colors_flat = weight*colors_flat # [h*w, 3, 3]
|
||||
colors_flat = np.sum(colors_flat, 1) #[h*w, 3]. add tri.
|
||||
|
||||
image = np.reshape(colors_flat, [h, w, c])
|
||||
# mask = (triangle_buffer[:,:] > -1).astype(np.float32)
|
||||
# image = image*mask[:,:,np.newaxis]
|
||||
return image
|
||||
|
||||
|
||||
def render_colors(vertices, triangles, colors, h, w, c = 3):
|
||||
''' render mesh with colors
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
triangles: [ntri, 3]
|
||||
colors: [nver, 3]
|
||||
h: height
|
||||
w: width
|
||||
Returns:
|
||||
image: [h, w, c].
|
||||
'''
|
||||
assert vertices.shape[0] == colors.shape[0]
|
||||
|
||||
# initial
|
||||
image = np.zeros((h, w, c))
|
||||
depth_buffer = np.zeros([h, w]) - 999999.
|
||||
|
||||
for i in range(triangles.shape[0]):
|
||||
tri = triangles[i, :] # 3 vertex indices
|
||||
|
||||
# the inner bounding box
|
||||
umin = max(int(np.ceil(np.min(vertices[tri, 0]))), 0)
|
||||
umax = min(int(np.floor(np.max(vertices[tri, 0]))), w-1)
|
||||
|
||||
vmin = max(int(np.ceil(np.min(vertices[tri, 1]))), 0)
|
||||
vmax = min(int(np.floor(np.max(vertices[tri, 1]))), h-1)
|
||||
|
||||
if umax<umin or vmax<vmin:
|
||||
continue
|
||||
|
||||
for u in range(umin, umax+1):
|
||||
for v in range(vmin, vmax+1):
|
||||
if not isPointInTri([u,v], vertices[tri, :2]):
|
||||
continue
|
||||
w0, w1, w2 = get_point_weight([u, v], vertices[tri, :2])
|
||||
point_depth = w0*vertices[tri[0], 2] + w1*vertices[tri[1], 2] + w2*vertices[tri[2], 2]
|
||||
|
||||
if point_depth > depth_buffer[v, u]:
|
||||
depth_buffer[v, u] = point_depth
|
||||
image[v, u, :] = w0*colors[tri[0], :] + w1*colors[tri[1], :] + w2*colors[tri[2], :]
|
||||
return image
|
||||
|
||||
|
||||
def render_texture(vertices, triangles, texture, tex_coords, tex_triangles, h, w, c = 3, mapping_type = 'nearest'):
|
||||
''' render mesh with texture map
|
||||
Args:
|
||||
vertices: [nver], 3
|
||||
triangles: [ntri, 3]
|
||||
texture: [tex_h, tex_w, 3]
|
||||
tex_coords: [ntexcoords, 3]
|
||||
tex_triangles: [ntri, 3]
|
||||
h: height of rendering
|
||||
w: width of rendering
|
||||
c: channel
|
||||
mapping_type: 'bilinear' or 'nearest'
|
||||
'''
|
||||
assert triangles.shape[0] == tex_triangles.shape[0]
|
||||
tex_h, tex_w, _ = texture.shape
|
||||
|
||||
# initial
|
||||
image = np.zeros((h, w, c))
|
||||
depth_buffer = np.zeros([h, w]) - 999999.
|
||||
|
||||
for i in range(triangles.shape[0]):
|
||||
tri = triangles[i, :] # 3 vertex indices
|
||||
tex_tri = tex_triangles[i, :] # 3 tex indice
|
||||
|
||||
# the inner bounding box
|
||||
umin = max(int(np.ceil(np.min(vertices[tri, 0]))), 0)
|
||||
umax = min(int(np.floor(np.max(vertices[tri, 0]))), w-1)
|
||||
|
||||
vmin = max(int(np.ceil(np.min(vertices[tri, 1]))), 0)
|
||||
vmax = min(int(np.floor(np.max(vertices[tri, 1]))), h-1)
|
||||
|
||||
if umax<umin or vmax<vmin:
|
||||
continue
|
||||
|
||||
for u in range(umin, umax+1):
|
||||
for v in range(vmin, vmax+1):
|
||||
if not isPointInTri([u,v], vertices[tri, :2]):
|
||||
continue
|
||||
w0, w1, w2 = get_point_weight([u, v], vertices[tri, :2])
|
||||
point_depth = w0*vertices[tri[0], 2] + w1*vertices[tri[1], 2] + w2*vertices[tri[2], 2]
|
||||
if point_depth > depth_buffer[v, u]:
|
||||
# update depth
|
||||
depth_buffer[v, u] = point_depth
|
||||
|
||||
# tex coord
|
||||
tex_xy = w0*tex_coords[tex_tri[0], :] + w1*tex_coords[tex_tri[1], :] + w2*tex_coords[tex_tri[2], :]
|
||||
tex_xy[0] = max(min(tex_xy[0], float(tex_w - 1)), 0.0);
|
||||
tex_xy[1] = max(min(tex_xy[1], float(tex_h - 1)), 0.0);
|
||||
|
||||
# nearest
|
||||
if mapping_type == 'nearest':
|
||||
tex_xy = np.round(tex_xy).astype(np.int32)
|
||||
tex_value = texture[tex_xy[1], tex_xy[0], :]
|
||||
|
||||
# bilinear
|
||||
elif mapping_type == 'bilinear':
|
||||
# next 4 pixels
|
||||
ul = texture[int(np.floor(tex_xy[1])), int(np.floor(tex_xy[0])), :]
|
||||
ur = texture[int(np.floor(tex_xy[1])), int(np.ceil(tex_xy[0])), :]
|
||||
dl = texture[int(np.ceil(tex_xy[1])), int(np.floor(tex_xy[0])), :]
|
||||
dr = texture[int(np.ceil(tex_xy[1])), int(np.ceil(tex_xy[0])), :]
|
||||
|
||||
yd = tex_xy[1] - np.floor(tex_xy[1])
|
||||
xd = tex_xy[0] - np.floor(tex_xy[0])
|
||||
tex_value = ul*(1-xd)*(1-yd) + ur*xd*(1-yd) + dl*(1-xd)*yd + dr*xd*yd
|
||||
|
||||
image[v, u, :] = tex_value
|
||||
return image
|
||||
@ -1,385 +0,0 @@
|
||||
'''
|
||||
Functions about transforming mesh(changing the position: modify vertices).
|
||||
1. forward: transform(transform, camera, project).
|
||||
2. backward: estimate transform matrix from correspondences.
|
||||
|
||||
Preparation knowledge:
|
||||
transform&camera model:
|
||||
https://cs184.eecs.berkeley.edu/lecture/transforms-2
|
||||
Part I: camera geometry and single view geometry in MVGCV
|
||||
'''
|
||||
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import numpy as np
|
||||
import math
|
||||
from math import cos, sin
|
||||
|
||||
def angle2matrix(angles):
|
||||
''' get rotation matrix from three rotation angles(degree). right-handed.
|
||||
Args:
|
||||
angles: [3,]. x, y, z angles
|
||||
x: pitch. positive for looking down.
|
||||
y: yaw. positive for looking left.
|
||||
z: roll. positive for tilting head right.
|
||||
Returns:
|
||||
R: [3, 3]. rotation matrix.
|
||||
'''
|
||||
x, y, z = np.deg2rad(angles[0]), np.deg2rad(angles[1]), np.deg2rad(angles[2])
|
||||
# x
|
||||
Rx=np.array([[1, 0, 0],
|
||||
[0, cos(x), -sin(x)],
|
||||
[0, sin(x), cos(x)]])
|
||||
# y
|
||||
Ry=np.array([[ cos(y), 0, sin(y)],
|
||||
[ 0, 1, 0],
|
||||
[-sin(y), 0, cos(y)]])
|
||||
# z
|
||||
Rz=np.array([[cos(z), -sin(z), 0],
|
||||
[sin(z), cos(z), 0],
|
||||
[ 0, 0, 1]])
|
||||
|
||||
R=Rz.dot(Ry.dot(Rx))
|
||||
return R.astype(np.float32)
|
||||
|
||||
def angle2matrix_3ddfa(angles):
|
||||
''' get rotation matrix from three rotation angles(radian). The same as in 3DDFA.
|
||||
Args:
|
||||
angles: [3,]. x, y, z angles
|
||||
x: pitch.
|
||||
y: yaw.
|
||||
z: roll.
|
||||
Returns:
|
||||
R: 3x3. rotation matrix.
|
||||
'''
|
||||
# x, y, z = np.deg2rad(angles[0]), np.deg2rad(angles[1]), np.deg2rad(angles[2])
|
||||
x, y, z = angles[0], angles[1], angles[2]
|
||||
|
||||
# x
|
||||
Rx=np.array([[1, 0, 0],
|
||||
[0, cos(x), sin(x)],
|
||||
[0, -sin(x), cos(x)]])
|
||||
# y
|
||||
Ry=np.array([[ cos(y), 0, -sin(y)],
|
||||
[ 0, 1, 0],
|
||||
[sin(y), 0, cos(y)]])
|
||||
# z
|
||||
Rz=np.array([[cos(z), sin(z), 0],
|
||||
[-sin(z), cos(z), 0],
|
||||
[ 0, 0, 1]])
|
||||
R = Rx.dot(Ry).dot(Rz)
|
||||
return R.astype(np.float32)
|
||||
|
||||
|
||||
## ------------------------------------------ 1. transform(transform, project, camera).
|
||||
## ---------- 3d-3d transform. Transform obj in world space
|
||||
def rotate(vertices, angles):
|
||||
''' rotate vertices.
|
||||
X_new = R.dot(X). X: 3 x 1
|
||||
Args:
|
||||
vertices: [nver, 3].
|
||||
rx, ry, rz: degree angles
|
||||
rx: pitch. positive for looking down
|
||||
ry: yaw. positive for looking left
|
||||
rz: roll. positive for tilting head right
|
||||
Returns:
|
||||
rotated vertices: [nver, 3]
|
||||
'''
|
||||
R = angle2matrix(angles)
|
||||
rotated_vertices = vertices.dot(R.T)
|
||||
|
||||
return rotated_vertices
|
||||
|
||||
def similarity_transform(vertices, s, R, t3d):
|
||||
''' similarity transform. dof = 7.
|
||||
3D: s*R.dot(X) + t
|
||||
Homo: M = [[sR, t],[0^T, 1]]. M.dot(X)
|
||||
Args:(float32)
|
||||
vertices: [nver, 3].
|
||||
s: [1,]. scale factor.
|
||||
R: [3,3]. rotation matrix.
|
||||
t3d: [3,]. 3d translation vector.
|
||||
Returns:
|
||||
transformed vertices: [nver, 3]
|
||||
'''
|
||||
t3d = np.squeeze(np.array(t3d, dtype = np.float32))
|
||||
transformed_vertices = s * vertices.dot(R.T) + t3d[np.newaxis, :]
|
||||
|
||||
return transformed_vertices
|
||||
|
||||
|
||||
## -------------- Camera. from world space to camera space
|
||||
# Ref: https://cs184.eecs.berkeley.edu/lecture/transforms-2
|
||||
def normalize(x):
|
||||
epsilon = 1e-12
|
||||
norm = np.sqrt(np.sum(x**2, axis = 0))
|
||||
norm = np.maximum(norm, epsilon)
|
||||
return x/norm
|
||||
|
||||
def lookat_camera(vertices, eye, at = None, up = None):
|
||||
""" 'look at' transformation: from world space to camera space
|
||||
standard camera space:
|
||||
camera located at the origin.
|
||||
looking down negative z-axis.
|
||||
vertical vector is y-axis.
|
||||
Xcam = R(X - C)
|
||||
Homo: [[R, -RC], [0, 1]]
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
eye: [3,] the XYZ world space position of the camera.
|
||||
at: [3,] a position along the center of the camera's gaze.
|
||||
up: [3,] up direction
|
||||
Returns:
|
||||
transformed_vertices: [nver, 3]
|
||||
"""
|
||||
if at is None:
|
||||
at = np.array([0, 0, 0], np.float32)
|
||||
if up is None:
|
||||
up = np.array([0, 1, 0], np.float32)
|
||||
|
||||
eye = np.array(eye).astype(np.float32)
|
||||
at = np.array(at).astype(np.float32)
|
||||
z_aixs = -normalize(at - eye) # look forward
|
||||
x_aixs = normalize(np.cross(up, z_aixs)) # look right
|
||||
y_axis = np.cross(z_aixs, x_aixs) # look up
|
||||
|
||||
R = np.stack((x_aixs, y_axis, z_aixs))#, axis = 0) # 3 x 3
|
||||
transformed_vertices = vertices - eye # translation
|
||||
transformed_vertices = transformed_vertices.dot(R.T) # rotation
|
||||
return transformed_vertices
|
||||
|
||||
## --------- 3d-2d project. from camera space to image plane
|
||||
# generally, image plane only keeps x,y channels, here reserve z channel for calculating z-buffer.
|
||||
def orthographic_project(vertices):
|
||||
''' scaled orthographic projection(just delete z)
|
||||
assumes: variations in depth over the object is small relative to the mean distance from camera to object
|
||||
x -> x*f/z, y -> x*f/z, z -> f.
|
||||
for point i,j. zi~=zj. so just delete z
|
||||
** often used in face
|
||||
Homo: P = [[1,0,0,0], [0,1,0,0], [0,0,1,0]]
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
Returns:
|
||||
projected_vertices: [nver, 3] if isKeepZ=True. [nver, 2] if isKeepZ=False.
|
||||
'''
|
||||
return vertices.copy()
|
||||
|
||||
def perspective_project(vertices, fovy, aspect_ratio = 1., near = 0.1, far = 1000.):
|
||||
''' perspective projection.
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
fovy: vertical angular field of view. degree.
|
||||
aspect_ratio : width / height of field of view
|
||||
near : depth of near clipping plane
|
||||
far : depth of far clipping plane
|
||||
Returns:
|
||||
projected_vertices: [nver, 3]
|
||||
'''
|
||||
fovy = np.deg2rad(fovy)
|
||||
top = near*np.tan(fovy)
|
||||
bottom = -top
|
||||
right = top*aspect_ratio
|
||||
left = -right
|
||||
|
||||
#-- homo
|
||||
P = np.array([[near/right, 0, 0, 0],
|
||||
[0, near/top, 0, 0],
|
||||
[0, 0, -(far+near)/(far-near), -2*far*near/(far-near)],
|
||||
[0, 0, -1, 0]])
|
||||
vertices_homo = np.hstack((vertices, np.ones((vertices.shape[0], 1)))) # [nver, 4]
|
||||
projected_vertices = vertices_homo.dot(P.T)
|
||||
projected_vertices = projected_vertices/projected_vertices[:,3:]
|
||||
projected_vertices = projected_vertices[:,:3]
|
||||
projected_vertices[:,2] = -projected_vertices[:,2]
|
||||
|
||||
#-- non homo. only fovy
|
||||
# projected_vertices = vertices.copy()
|
||||
# projected_vertices[:,0] = -(near/right)*vertices[:,0]/vertices[:,2]
|
||||
# projected_vertices[:,1] = -(near/top)*vertices[:,1]/vertices[:,2]
|
||||
return projected_vertices
|
||||
|
||||
|
||||
def to_image(vertices, h, w, is_perspective = False):
|
||||
''' change vertices to image coord system
|
||||
3d system: XYZ, center(0, 0, 0)
|
||||
2d image: x(u), y(v). center(w/2, h/2), flip y-axis.
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
h: height of the rendering
|
||||
w : width of the rendering
|
||||
Returns:
|
||||
projected_vertices: [nver, 3]
|
||||
'''
|
||||
image_vertices = vertices.copy()
|
||||
if is_perspective:
|
||||
# if perspective, the projected vertices are normalized to [-1, 1]. so change it to image size first.
|
||||
image_vertices[:,0] = image_vertices[:,0]*w/2
|
||||
image_vertices[:,1] = image_vertices[:,1]*h/2
|
||||
# move to center of image
|
||||
image_vertices[:,0] = image_vertices[:,0] + w/2
|
||||
image_vertices[:,1] = image_vertices[:,1] + h/2
|
||||
# flip vertices along y-axis.
|
||||
image_vertices[:,1] = h - image_vertices[:,1] - 1
|
||||
return image_vertices
|
||||
|
||||
|
||||
#### -------------------------------------------2. estimate transform matrix from correspondences.
|
||||
def estimate_affine_matrix_3d23d(X, Y):
|
||||
''' Using least-squares solution
|
||||
Args:
|
||||
X: [n, 3]. 3d points(fixed)
|
||||
Y: [n, 3]. corresponding 3d points(moving). Y = PX
|
||||
Returns:
|
||||
P_Affine: (3, 4). Affine camera matrix (the third row is [0, 0, 0, 1]).
|
||||
'''
|
||||
X_homo = np.hstack((X, np.ones([X.shape[1],1]))) #n x 4
|
||||
P = np.linalg.lstsq(X_homo, Y)[0].T # Affine matrix. 3 x 4
|
||||
return P
|
||||
|
||||
def estimate_affine_matrix_3d22d(X, x):
|
||||
''' Using Golden Standard Algorithm for estimating an affine camera
|
||||
matrix P from world to image correspondences.
|
||||
See Alg.7.2. in MVGCV
|
||||
Code Ref: https://github.com/patrikhuber/eos/blob/master/include/eos/fitting/affine_camera_estimation.hpp
|
||||
x_homo = X_homo.dot(P_Affine)
|
||||
Args:
|
||||
X: [n, 3]. corresponding 3d points(fixed)
|
||||
x: [n, 2]. n>=4. 2d points(moving). x = PX
|
||||
Returns:
|
||||
P_Affine: [3, 4]. Affine camera matrix
|
||||
'''
|
||||
X = X.T; x = x.T
|
||||
assert(x.shape[1] == X.shape[1])
|
||||
n = x.shape[1]
|
||||
assert(n >= 4)
|
||||
|
||||
#--- 1. normalization
|
||||
# 2d points
|
||||
mean = np.mean(x, 1) # (2,)
|
||||
x = x - np.tile(mean[:, np.newaxis], [1, n])
|
||||
average_norm = np.mean(np.sqrt(np.sum(x**2, 0)))
|
||||
scale = np.sqrt(2) / average_norm
|
||||
x = scale * x
|
||||
|
||||
T = np.zeros((3,3), dtype = np.float32)
|
||||
T[0, 0] = T[1, 1] = scale
|
||||
T[:2, 2] = -mean*scale
|
||||
T[2, 2] = 1
|
||||
|
||||
# 3d points
|
||||
X_homo = np.vstack((X, np.ones((1, n))))
|
||||
mean = np.mean(X, 1) # (3,)
|
||||
X = X - np.tile(mean[:, np.newaxis], [1, n])
|
||||
m = X_homo[:3,:] - X
|
||||
average_norm = np.mean(np.sqrt(np.sum(X**2, 0)))
|
||||
scale = np.sqrt(3) / average_norm
|
||||
X = scale * X
|
||||
|
||||
U = np.zeros((4,4), dtype = np.float32)
|
||||
U[0, 0] = U[1, 1] = U[2, 2] = scale
|
||||
U[:3, 3] = -mean*scale
|
||||
U[3, 3] = 1
|
||||
|
||||
# --- 2. equations
|
||||
A = np.zeros((n*2, 8), dtype = np.float32);
|
||||
X_homo = np.vstack((X, np.ones((1, n)))).T
|
||||
A[:n, :4] = X_homo
|
||||
A[n:, 4:] = X_homo
|
||||
b = np.reshape(x, [-1, 1])
|
||||
|
||||
# --- 3. solution
|
||||
p_8 = np.linalg.pinv(A).dot(b)
|
||||
P = np.zeros((3, 4), dtype = np.float32)
|
||||
P[0, :] = p_8[:4, 0]
|
||||
P[1, :] = p_8[4:, 0]
|
||||
P[-1, -1] = 1
|
||||
|
||||
# --- 4. denormalization
|
||||
P_Affine = np.linalg.inv(T).dot(P.dot(U))
|
||||
return P_Affine
|
||||
|
||||
def P2sRt(P):
|
||||
''' decompositing camera matrix P
|
||||
Args:
|
||||
P: (3, 4). Affine Camera Matrix.
|
||||
Returns:
|
||||
s: scale factor.
|
||||
R: (3, 3). rotation matrix.
|
||||
t: (3,). translation.
|
||||
'''
|
||||
t = P[:, 3]
|
||||
R1 = P[0:1, :3]
|
||||
R2 = P[1:2, :3]
|
||||
s = (np.linalg.norm(R1) + np.linalg.norm(R2))/2.0
|
||||
r1 = R1/np.linalg.norm(R1)
|
||||
r2 = R2/np.linalg.norm(R2)
|
||||
r3 = np.cross(r1, r2)
|
||||
|
||||
R = np.concatenate((r1, r2, r3), 0)
|
||||
return s, R, t
|
||||
|
||||
#Ref: https://www.learnopencv.com/rotation-matrix-to-euler-angles/
|
||||
def isRotationMatrix(R):
|
||||
''' checks if a matrix is a valid rotation matrix(whether orthogonal or not)
|
||||
'''
|
||||
Rt = np.transpose(R)
|
||||
shouldBeIdentity = np.dot(Rt, R)
|
||||
I = np.identity(3, dtype = R.dtype)
|
||||
n = np.linalg.norm(I - shouldBeIdentity)
|
||||
return n < 1e-6
|
||||
|
||||
def matrix2angle(R):
|
||||
''' get three Euler angles from Rotation Matrix
|
||||
Args:
|
||||
R: (3,3). rotation matrix
|
||||
Returns:
|
||||
x: pitch
|
||||
y: yaw
|
||||
z: roll
|
||||
'''
|
||||
assert(isRotationMatrix)
|
||||
sy = math.sqrt(R[0,0] * R[0,0] + R[1,0] * R[1,0])
|
||||
|
||||
singular = sy < 1e-6
|
||||
|
||||
if not singular :
|
||||
x = math.atan2(R[2,1] , R[2,2])
|
||||
y = math.atan2(-R[2,0], sy)
|
||||
z = math.atan2(R[1,0], R[0,0])
|
||||
else :
|
||||
x = math.atan2(-R[1,2], R[1,1])
|
||||
y = math.atan2(-R[2,0], sy)
|
||||
z = 0
|
||||
|
||||
# rx, ry, rz = np.rad2deg(x), np.rad2deg(y), np.rad2deg(z)
|
||||
rx, ry, rz = x*180/np.pi, y*180/np.pi, z*180/np.pi
|
||||
return rx, ry, rz
|
||||
|
||||
# def matrix2angle(R):
|
||||
# ''' compute three Euler angles from a Rotation Matrix. Ref: http://www.gregslabaugh.net/publications/euler.pdf
|
||||
# Args:
|
||||
# R: (3,3). rotation matrix
|
||||
# Returns:
|
||||
# x: yaw
|
||||
# y: pitch
|
||||
# z: roll
|
||||
# '''
|
||||
# # assert(isRotationMatrix(R))
|
||||
|
||||
# if R[2,0] !=1 or R[2,0] != -1:
|
||||
# x = math.asin(R[2,0])
|
||||
# y = math.atan2(R[2,1]/cos(x), R[2,2]/cos(x))
|
||||
# z = math.atan2(R[1,0]/cos(x), R[0,0]/cos(x))
|
||||
|
||||
# else:# Gimbal lock
|
||||
# z = 0 #can be anything
|
||||
# if R[2,0] == -1:
|
||||
# x = np.pi/2
|
||||
# y = z + math.atan2(R[0,1], R[0,2])
|
||||
# else:
|
||||
# x = -np.pi/2
|
||||
# y = -z + math.atan2(-R[0,1], -R[0,2])
|
||||
|
||||
# return x, y, z
|
||||
@ -1,24 +0,0 @@
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
from skimage import measure
|
||||
from mpl_toolkits.mplot3d import Axes3D
|
||||
|
||||
def plot_mesh(vertices, triangles, subplot = [1,1,1], title = 'mesh', el = 90, az = -90, lwdt=.1, dist = 6, color = "grey"):
|
||||
'''
|
||||
plot the mesh
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
triangles: [ntri, 3]
|
||||
'''
|
||||
ax = plt.subplot(subplot[0], subplot[1], subplot[2], projection = '3d')
|
||||
ax.plot_trisurf(vertices[:, 0], vertices[:, 1], vertices[:, 2], triangles = triangles, lw = lwdt, color = color, alpha = 1)
|
||||
ax.axis("off")
|
||||
ax.view_init(elev = el, azim = az)
|
||||
ax.dist = dist
|
||||
plt.title(title)
|
||||
|
||||
### -------------- Todo: use vtk to visualize mesh? or visvis? or VisPy?
|
||||
@ -1,7 +0,0 @@
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
from .. import mesh
|
||||
from .morphabel_model import MorphabelModel
|
||||
from . import load
|
||||
@ -1,272 +0,0 @@
|
||||
'''
|
||||
Estimating parameters about vertices: shape para, exp para, pose para(s, R, t)
|
||||
'''
|
||||
import numpy as np
|
||||
from .. import mesh
|
||||
|
||||
''' TODO: a clear document.
|
||||
Given: image_points, 3D Model, Camera Matrix(s, R, t2d)
|
||||
Estimate: shape parameters, expression parameters
|
||||
|
||||
Inference:
|
||||
|
||||
projected_vertices = s*P*R(mu + shape + exp) + t2d --> image_points
|
||||
s*P*R*shape + s*P*R(mu + exp) + t2d --> image_poitns
|
||||
|
||||
# Define:
|
||||
X = vertices
|
||||
x_hat = projected_vertices
|
||||
x = image_points
|
||||
A = s*P*R
|
||||
b = s*P*R(mu + exp) + t2d
|
||||
==>
|
||||
x_hat = A*shape + b (2 x n)
|
||||
|
||||
A*shape (2 x n)
|
||||
shape = reshape(shapePC * sp) (3 x n)
|
||||
shapePC*sp : (3n x 1)
|
||||
|
||||
* flatten:
|
||||
x_hat_flatten = A*shape + b_flatten (2n x 1)
|
||||
A*shape (2n x 1)
|
||||
--> A*shapePC (2n x 199) sp: 199 x 1
|
||||
|
||||
# Define:
|
||||
pc_2d = A* reshape(shapePC)
|
||||
pc_2d_flatten = flatten(pc_2d) (2n x 199)
|
||||
|
||||
=====>
|
||||
x_hat_flatten = pc_2d_flatten * sp + b_flatten ---> x_flatten (2n x 1)
|
||||
|
||||
Goals:
|
||||
(ignore flatten, pc_2d-->pc)
|
||||
min E = || x_hat - x || + lambda*sum(sp/sigma)^2
|
||||
= || pc * sp + b - x || + lambda*sum(sp/sigma)^2
|
||||
|
||||
Solve:
|
||||
d(E)/d(sp) = 0
|
||||
2 * pc' * (pc * sp + b - x) + 2 * lambda * sp / (sigma' * sigma) = 0
|
||||
|
||||
Get:
|
||||
(pc' * pc + lambda / (sigma'* sigma)) * sp = pc' * (x - b)
|
||||
|
||||
'''
|
||||
|
||||
def estimate_shape(x, shapeMU, shapePC, shapeEV, expression, s, R, t2d, lamb = 3000):
|
||||
'''
|
||||
Args:
|
||||
x: (2, n). image points (to be fitted)
|
||||
shapeMU: (3n, 1)
|
||||
shapePC: (3n, n_sp)
|
||||
shapeEV: (n_sp, 1)
|
||||
expression: (3, n)
|
||||
s: scale
|
||||
R: (3, 3). rotation matrix
|
||||
t2d: (2,). 2d translation
|
||||
lambda: regulation coefficient
|
||||
|
||||
Returns:
|
||||
shape_para: (n_sp, 1) shape parameters(coefficients)
|
||||
'''
|
||||
x = x.copy()
|
||||
assert(shapeMU.shape[0] == shapePC.shape[0])
|
||||
assert(shapeMU.shape[0] == x.shape[1]*3)
|
||||
|
||||
dof = shapePC.shape[1]
|
||||
|
||||
n = x.shape[1]
|
||||
sigma = shapeEV
|
||||
t2d = np.array(t2d)
|
||||
P = np.array([[1, 0, 0], [0, 1, 0]], dtype = np.float32)
|
||||
A = s*P.dot(R)
|
||||
|
||||
# --- calc pc
|
||||
pc_3d = np.resize(shapePC.T, [dof, n, 3]) # 199 x n x 3
|
||||
pc_3d = np.reshape(pc_3d, [dof*n, 3])
|
||||
pc_2d = pc_3d.dot(A.T.copy()) # 199 x n x 2
|
||||
|
||||
pc = np.reshape(pc_2d, [dof, -1]).T # 2n x 199
|
||||
|
||||
# --- calc b
|
||||
# shapeMU
|
||||
mu_3d = np.resize(shapeMU, [n, 3]).T # 3 x n
|
||||
# expression
|
||||
exp_3d = expression
|
||||
#
|
||||
b = A.dot(mu_3d + exp_3d) + np.tile(t2d[:, np.newaxis], [1, n]) # 2 x n
|
||||
b = np.reshape(b.T, [-1, 1]) # 2n x 1
|
||||
|
||||
# --- solve
|
||||
equation_left = np.dot(pc.T, pc) + lamb * np.diagflat(1/sigma**2)
|
||||
x = np.reshape(x.T, [-1, 1])
|
||||
equation_right = np.dot(pc.T, x - b)
|
||||
|
||||
shape_para = np.dot(np.linalg.inv(equation_left), equation_right)
|
||||
|
||||
return shape_para
|
||||
|
||||
def estimate_expression(x, shapeMU, expPC, expEV, shape, s, R, t2d, lamb = 2000):
|
||||
'''
|
||||
Args:
|
||||
x: (2, n). image points (to be fitted)
|
||||
shapeMU: (3n, 1)
|
||||
expPC: (3n, n_ep)
|
||||
expEV: (n_ep, 1)
|
||||
shape: (3, n)
|
||||
s: scale
|
||||
R: (3, 3). rotation matrix
|
||||
t2d: (2,). 2d translation
|
||||
lambda: regulation coefficient
|
||||
|
||||
Returns:
|
||||
exp_para: (n_ep, 1) shape parameters(coefficients)
|
||||
'''
|
||||
x = x.copy()
|
||||
assert(shapeMU.shape[0] == expPC.shape[0])
|
||||
assert(shapeMU.shape[0] == x.shape[1]*3)
|
||||
|
||||
dof = expPC.shape[1]
|
||||
|
||||
n = x.shape[1]
|
||||
sigma = expEV
|
||||
t2d = np.array(t2d)
|
||||
P = np.array([[1, 0, 0], [0, 1, 0]], dtype = np.float32)
|
||||
A = s*P.dot(R)
|
||||
|
||||
# --- calc pc
|
||||
pc_3d = np.resize(expPC.T, [dof, n, 3])
|
||||
pc_3d = np.reshape(pc_3d, [dof*n, 3])
|
||||
pc_2d = pc_3d.dot(A.T)
|
||||
pc = np.reshape(pc_2d, [dof, -1]).T # 2n x 29
|
||||
|
||||
# --- calc b
|
||||
# shapeMU
|
||||
mu_3d = np.resize(shapeMU, [n, 3]).T # 3 x n
|
||||
# expression
|
||||
shape_3d = shape
|
||||
#
|
||||
b = A.dot(mu_3d + shape_3d) + np.tile(t2d[:, np.newaxis], [1, n]) # 2 x n
|
||||
b = np.reshape(b.T, [-1, 1]) # 2n x 1
|
||||
|
||||
# --- solve
|
||||
equation_left = np.dot(pc.T, pc) + lamb * np.diagflat(1/sigma**2)
|
||||
x = np.reshape(x.T, [-1, 1])
|
||||
equation_right = np.dot(pc.T, x - b)
|
||||
|
||||
exp_para = np.dot(np.linalg.inv(equation_left), equation_right)
|
||||
|
||||
return exp_para
|
||||
|
||||
|
||||
# ---------------- fit
|
||||
def fit_points(x, X_ind, model, n_sp, n_ep, max_iter = 4):
|
||||
'''
|
||||
Args:
|
||||
x: (n, 2) image points
|
||||
X_ind: (n,) corresponding Model vertex indices
|
||||
model: 3DMM
|
||||
max_iter: iteration
|
||||
Returns:
|
||||
sp: (n_sp, 1). shape parameters
|
||||
ep: (n_ep, 1). exp parameters
|
||||
s, R, t
|
||||
'''
|
||||
x = x.copy().T
|
||||
|
||||
#-- init
|
||||
sp = np.zeros((n_sp, 1), dtype = np.float32)
|
||||
ep = np.zeros((n_ep, 1), dtype = np.float32)
|
||||
|
||||
#-------------------- estimate
|
||||
X_ind_all = np.tile(X_ind[np.newaxis, :], [3, 1])*3
|
||||
X_ind_all[1, :] += 1
|
||||
X_ind_all[2, :] += 2
|
||||
valid_ind = X_ind_all.flatten('F')
|
||||
|
||||
shapeMU = model['shapeMU'][valid_ind, :]
|
||||
shapePC = model['shapePC'][valid_ind, :n_sp]
|
||||
expPC = model['expPC'][valid_ind, :n_ep]
|
||||
|
||||
for i in range(max_iter):
|
||||
X = shapeMU + shapePC.dot(sp) + expPC.dot(ep)
|
||||
X = np.reshape(X, [int(len(X)/3), 3]).T
|
||||
|
||||
#----- estimate pose
|
||||
P = mesh.transform.estimate_affine_matrix_3d22d(X.T, x.T)
|
||||
s, R, t = mesh.transform.P2sRt(P)
|
||||
rx, ry, rz = mesh.transform.matrix2angle(R)
|
||||
#print('Iter:{}; estimated pose: s {}, rx {}, ry {}, rz {}, t1 {}, t2 {}'.format(i, s, rx, ry, rz, t[0], t[1]))
|
||||
|
||||
#----- estimate shape
|
||||
# expression
|
||||
shape = shapePC.dot(sp)
|
||||
shape = np.reshape(shape, [int(len(shape)/3), 3]).T
|
||||
ep = estimate_expression(x, shapeMU, expPC, model['expEV'][:n_ep,:], shape, s, R, t[:2], lamb = 20)
|
||||
|
||||
# shape
|
||||
expression = expPC.dot(ep)
|
||||
expression = np.reshape(expression, [int(len(expression)/3), 3]).T
|
||||
if i == 0 :
|
||||
sp = estimate_shape(x, shapeMU, shapePC, model['shapeEV'][:n_sp,:], expression, s, R, t[:2], lamb = 40)
|
||||
|
||||
return sp, ep, s, R, t
|
||||
|
||||
|
||||
# ---------------- fitting process
|
||||
def fit_points_for_show(x, X_ind, model, n_sp, n_ep, max_iter = 4):
|
||||
'''
|
||||
Args:
|
||||
x: (n, 2) image points
|
||||
X_ind: (n,) corresponding Model vertex indices
|
||||
model: 3DMM
|
||||
max_iter: iteration
|
||||
Returns:
|
||||
sp: (n_sp, 1). shape parameters
|
||||
ep: (n_ep, 1). exp parameters
|
||||
s, R, t
|
||||
'''
|
||||
x = x.copy().T
|
||||
|
||||
#-- init
|
||||
sp = np.zeros((n_sp, 1), dtype = np.float32)
|
||||
ep = np.zeros((n_ep, 1), dtype = np.float32)
|
||||
|
||||
#-------------------- estimate
|
||||
X_ind_all = np.tile(X_ind[np.newaxis, :], [3, 1])*3
|
||||
X_ind_all[1, :] += 1
|
||||
X_ind_all[2, :] += 2
|
||||
valid_ind = X_ind_all.flatten('F')
|
||||
|
||||
shapeMU = model['shapeMU'][valid_ind, :]
|
||||
shapePC = model['shapePC'][valid_ind, :n_sp]
|
||||
expPC = model['expPC'][valid_ind, :n_ep]
|
||||
|
||||
s = 4e-04
|
||||
R = mesh.transform.angle2matrix([0, 0, 0])
|
||||
t = [0, 0, 0]
|
||||
lsp = []; lep = []; ls = []; lR = []; lt = []
|
||||
for i in range(max_iter):
|
||||
X = shapeMU + shapePC.dot(sp) + expPC.dot(ep)
|
||||
X = np.reshape(X, [int(len(X)/3), 3]).T
|
||||
lsp.append(sp); lep.append(ep); ls.append(s), lR.append(R), lt.append(t)
|
||||
|
||||
#----- estimate pose
|
||||
P = mesh.transform.estimate_affine_matrix_3d22d(X.T, x.T)
|
||||
s, R, t = mesh.transform.P2sRt(P)
|
||||
lsp.append(sp); lep.append(ep); ls.append(s), lR.append(R), lt.append(t)
|
||||
|
||||
#----- estimate shape
|
||||
# expression
|
||||
shape = shapePC.dot(sp)
|
||||
shape = np.reshape(shape, [int(len(shape)/3), 3]).T
|
||||
ep = estimate_expression(x, shapeMU, expPC, model['expEV'][:n_ep,:], shape, s, R, t[:2], lamb = 20)
|
||||
lsp.append(sp); lep.append(ep); ls.append(s), lR.append(R), lt.append(t)
|
||||
|
||||
# shape
|
||||
expression = expPC.dot(ep)
|
||||
expression = np.reshape(expression, [int(len(expression)/3), 3]).T
|
||||
sp = estimate_shape(x, shapeMU, shapePC, model['shapeEV'][:n_sp,:], expression, s, R, t[:2], lamb = 40)
|
||||
|
||||
# print('ls', ls)
|
||||
# print('lR', lR)
|
||||
return np.array(lsp), np.array(lep), np.array(ls), np.array(lR), np.array(lt)
|
||||
@ -1,110 +0,0 @@
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import numpy as np
|
||||
import scipy.io as sio
|
||||
|
||||
### --------------------------------- load BFM data
|
||||
def load_BFM(model_path):
|
||||
''' load BFM 3DMM model
|
||||
Args:
|
||||
model_path: path to BFM model.
|
||||
Returns:
|
||||
model: (nver = 53215, ntri = 105840). nver: number of vertices. ntri: number of triangles.
|
||||
'shapeMU': [3*nver, 1]
|
||||
'shapePC': [3*nver, 199]
|
||||
'shapeEV': [199, 1]
|
||||
'expMU': [3*nver, 1]
|
||||
'expPC': [3*nver, 29]
|
||||
'expEV': [29, 1]
|
||||
'texMU': [3*nver, 1]
|
||||
'texPC': [3*nver, 199]
|
||||
'texEV': [199, 1]
|
||||
'tri': [ntri, 3] (start from 1, should sub 1 in python and c++)
|
||||
'tri_lip': [114, 3] (start from 1, as a supplement to lip triangles)
|
||||
'kpt_ind': [68,] (start from 1)
|
||||
PS:
|
||||
You can change codes according to your own saved data.
|
||||
Just make sure the model has corresponding attributes.
|
||||
'''
|
||||
C = sio.loadmat(model_path)
|
||||
model = C['model']
|
||||
model = model[0,0]
|
||||
|
||||
# change dtype from double(np.float64) to np.float32,
|
||||
# since big matrix process(espetially matrix dot) is too slow in python.
|
||||
model['shapeMU'] = (model['shapeMU'] + model['expMU']).astype(np.float32)
|
||||
model['shapePC'] = model['shapePC'].astype(np.float32)
|
||||
model['shapeEV'] = model['shapeEV'].astype(np.float32)
|
||||
model['expEV'] = model['expEV'].astype(np.float32)
|
||||
model['expPC'] = model['expPC'].astype(np.float32)
|
||||
|
||||
# matlab start with 1. change to 0 in python.
|
||||
model['tri'] = model['tri'].T.copy(order = 'C').astype(np.int32) - 1
|
||||
model['tri_lip'] = model['tri_lip'].T.copy(order = 'C').astype(np.int32) - 1
|
||||
|
||||
# kpt ind
|
||||
model['kpt_ind'] = (np.squeeze(model['kpt_ind']) - 1).astype(np.int32)
|
||||
|
||||
return model
|
||||
|
||||
def load_BFM_info(path = 'BFM_info.mat'):
|
||||
''' load 3DMM model extra information
|
||||
Args:
|
||||
path: path to BFM info.
|
||||
Returns:
|
||||
model_info:
|
||||
'symlist': 2 x 26720
|
||||
'symlist_tri': 2 x 52937
|
||||
'segbin': 4 x n (0: nose, 1: eye, 2: lip, 3: cheek)
|
||||
'segbin_tri': 4 x ntri
|
||||
'face_contour': 1 x 28
|
||||
'face_contour_line': 1 x 512
|
||||
'face_contour_front': 1 x 28
|
||||
'face_contour_front_line': 1 x 512
|
||||
'nose_hole': 1 x 142
|
||||
'nose_hole_right': 1 x 71
|
||||
'nose_hole_left': 1 x 71
|
||||
'parallel': 17 x 1 cell
|
||||
'parallel_face_contour': 28 x 1 cell
|
||||
'uv_coords': n x 2
|
||||
'''
|
||||
C = sio.loadmat(path)
|
||||
model_info = C['model_info']
|
||||
model_info = model_info[0,0]
|
||||
return model_info
|
||||
|
||||
def load_uv_coords(path = 'BFM_UV.mat'):
|
||||
''' load uv coords of BFM
|
||||
Args:
|
||||
path: path to data.
|
||||
Returns:
|
||||
uv_coords: [nver, 2]. range: 0-1
|
||||
'''
|
||||
C = sio.loadmat(path)
|
||||
uv_coords = C['UV'].copy(order = 'C')
|
||||
return uv_coords
|
||||
|
||||
def load_pncc_code(path = 'pncc_code.mat'):
|
||||
''' load pncc code of BFM
|
||||
PNCC code: Defined in 'Face Alignment Across Large Poses: A 3D Solution Xiangyu'
|
||||
download at http://www.cbsr.ia.ac.cn/users/xiangyuzhu/projects/3DDFA/main.htm.
|
||||
Args:
|
||||
path: path to data.
|
||||
Returns:
|
||||
pncc_code: [nver, 3]
|
||||
'''
|
||||
C = sio.loadmat(path)
|
||||
pncc_code = C['vertex_code'].T
|
||||
return pncc_code
|
||||
|
||||
##
|
||||
def get_organ_ind(model_info):
|
||||
''' get nose, eye, lip index
|
||||
'''
|
||||
valid_bin = model_info['segbin'].astype(bool)
|
||||
organ_ind = np.nonzero(valid_bin[0,:])[0]
|
||||
for i in range(1, valid_bin.shape[0] - 1):
|
||||
organ_ind = np.union1d(organ_ind, np.nonzero(valid_bin[i,:])[0])
|
||||
return organ_ind.astype(np.int32)
|
||||
@ -1,143 +0,0 @@
|
||||
from __future__ import absolute_import
|
||||
from __future__ import division
|
||||
from __future__ import print_function
|
||||
|
||||
import numpy as np
|
||||
import scipy.io as sio
|
||||
from .. import mesh
|
||||
from . import fit
|
||||
from . import load
|
||||
|
||||
class MorphabelModel(object):
|
||||
"""docstring for MorphabelModel
|
||||
model: nver: number of vertices. ntri: number of triangles. *: must have. ~: can generate ones array for place holder.
|
||||
'shapeMU': [3*nver, 1]. *
|
||||
'shapePC': [3*nver, n_shape_para]. *
|
||||
'shapeEV': [n_shape_para, 1]. ~
|
||||
'expMU': [3*nver, 1]. ~
|
||||
'expPC': [3*nver, n_exp_para]. ~
|
||||
'expEV': [n_exp_para, 1]. ~
|
||||
'texMU': [3*nver, 1]. ~
|
||||
'texPC': [3*nver, n_tex_para]. ~
|
||||
'texEV': [n_tex_para, 1]. ~
|
||||
'tri': [ntri, 3] (start from 1, should sub 1 in python and c++). *
|
||||
'tri_lip': [114, 3] (start from 1, as a supplement to lip triangles). ~
|
||||
'kpt_ind': [68,] (start from 1). ~
|
||||
"""
|
||||
def __init__(self, model_path, model_type = 'BFM'):
|
||||
super( MorphabelModel, self).__init__()
|
||||
if model_type=='BFM':
|
||||
self.model = load.load_BFM(model_path)
|
||||
else:
|
||||
print('sorry, not support other 3DMM model now')
|
||||
exit()
|
||||
|
||||
# fixed attributes
|
||||
self.nver = self.model['shapePC'].shape[0]/3
|
||||
self.ntri = self.model['tri'].shape[0]
|
||||
self.n_shape_para = self.model['shapePC'].shape[1]
|
||||
self.n_exp_para = self.model['expPC'].shape[1]
|
||||
self.n_tex_para = self.model['texMU'].shape[1]
|
||||
|
||||
self.kpt_ind = self.model['kpt_ind']
|
||||
self.triangles = self.model['tri']
|
||||
self.full_triangles = np.vstack((self.model['tri'], self.model['tri_lip']))
|
||||
|
||||
# ------------------------------------- shape: represented with mesh(vertices & triangles(fixed))
|
||||
def get_shape_para(self, type = 'random'):
|
||||
if type == 'zero':
|
||||
sp = np.random.zeros((self.n_shape_para, 1))
|
||||
elif type == 'random':
|
||||
sp = np.random.rand(self.n_shape_para, 1)*1e04
|
||||
return sp
|
||||
|
||||
def get_exp_para(self, type = 'random'):
|
||||
if type == 'zero':
|
||||
ep = np.zeros((self.n_exp_para, 1))
|
||||
elif type == 'random':
|
||||
ep = -1.5 + 3*np.random.random([self.n_exp_para, 1])
|
||||
ep[6:, 0] = 0
|
||||
|
||||
return ep
|
||||
|
||||
def generate_vertices(self, shape_para, exp_para):
|
||||
'''
|
||||
Args:
|
||||
shape_para: (n_shape_para, 1)
|
||||
exp_para: (n_exp_para, 1)
|
||||
Returns:
|
||||
vertices: (nver, 3)
|
||||
'''
|
||||
vertices = self.model['shapeMU'] + self.model['shapePC'].dot(shape_para) + self.model['expPC'].dot(exp_para)
|
||||
vertices = np.reshape(vertices, [int(3), int(len(vertices)/3)], 'F').T
|
||||
|
||||
return vertices
|
||||
|
||||
# -------------------------------------- texture: here represented with rgb value(colors) in vertices.
|
||||
def get_tex_para(self, type = 'random'):
|
||||
if type == 'zero':
|
||||
tp = np.zeros((self.n_tex_para, 1))
|
||||
elif type == 'random':
|
||||
tp = np.random.rand(self.n_tex_para, 1)
|
||||
return tp
|
||||
|
||||
def generate_colors(self, tex_para):
|
||||
'''
|
||||
Args:
|
||||
tex_para: (n_tex_para, 1)
|
||||
Returns:
|
||||
colors: (nver, 3)
|
||||
'''
|
||||
colors = self.model['texMU'] + self.model['texPC'].dot(tex_para*self.model['texEV'])
|
||||
colors = np.reshape(colors, [int(3), int(len(colors)/3)], 'F').T/255.
|
||||
|
||||
return colors
|
||||
|
||||
|
||||
# ------------------------------------------- transformation
|
||||
# ------------- transform
|
||||
def rotate(self, vertices, angles):
|
||||
''' rotate face
|
||||
Args:
|
||||
vertices: [nver, 3]
|
||||
angles: [3] x, y, z rotation angle(degree)
|
||||
x: pitch. positive for looking down
|
||||
y: yaw. positive for looking left
|
||||
z: roll. positive for tilting head right
|
||||
Returns:
|
||||
vertices: rotated vertices
|
||||
'''
|
||||
return mesh.transform.rotate(vertices, angles)
|
||||
|
||||
def transform(self, vertices, s, angles, t3d):
|
||||
R = mesh.transform.angle2matrix(angles)
|
||||
return mesh.transform.similarity_transform(vertices, s, R, t3d)
|
||||
|
||||
def transform_3ddfa(self, vertices, s, angles, t3d): # only used for processing 300W_LP data
|
||||
R = mesh.transform.angle2matrix_3ddfa(angles)
|
||||
return mesh.transform.similarity_transform(vertices, s, R, t3d)
|
||||
|
||||
# --------------------------------------------------- fitting
|
||||
def fit(self, x, X_ind, max_iter = 4, isShow = False):
|
||||
''' fit 3dmm & pose parameters
|
||||
Args:
|
||||
x: (n, 2) image points
|
||||
X_ind: (n,) corresponding Model vertex indices
|
||||
max_iter: iteration
|
||||
isShow: whether to reserve middle results for show
|
||||
Returns:
|
||||
fitted_sp: (n_sp, 1). shape parameters
|
||||
fitted_ep: (n_ep, 1). exp parameters
|
||||
s, angles, t
|
||||
'''
|
||||
if isShow:
|
||||
fitted_sp, fitted_ep, s, R, t = fit.fit_points_for_show(x, X_ind, self.model, n_sp = self.n_shape_para, n_ep = self.n_exp_para, max_iter = max_iter)
|
||||
angles = np.zeros((R.shape[0], 3))
|
||||
for i in range(R.shape[0]):
|
||||
angles[i] = mesh.transform.matrix2angle(R[i])
|
||||
else:
|
||||
fitted_sp, fitted_ep, s, R, t = fit.fit_points(x, X_ind, self.model, n_sp = self.n_shape_para, n_ep = self.n_exp_para, max_iter = max_iter)
|
||||
angles = mesh.transform.matrix2angle(R)
|
||||
return fitted_sp, fitted_ep, s, angles, t
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user