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Copy path8_generate_posmap_300WLP.py
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8_generate_posmap_300WLP.py
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'''
Generate uv position map of 300W_LP.
'''
import os, sys
import numpy as np
import scipy.io as sio
from skimage import io
import skimage.transform
from time import time
import matplotlib.pyplot as plt
sys.path.append('..')
import face3d
from face3d import mesh
from face3d import mesh_cython
from face3d.morphable_model import MorphabelModel
def process_uv(uv_coords, uv_h = 256, uv_w = 256):
uv_coords[:,0] = uv_coords[:,0]*(uv_h - 1)
uv_coords[:,1] = uv_coords[:,1]*(uv_h - 1)
uv_coords[:,1] = uv_h - uv_coords[:,1] - 1
uv_coords = np.hstack((uv_coords, np.zeros((uv_coords.shape[0], 1)))) # add z
return uv_coords
def run_posmap_300W_LP(bfm, image_path, mat_path, save_folder, uv_h = 256, uv_w = 256, image_h = 256, image_w = 256):
# 1. load image and fitted parameters
image_name = image_path.strip().split('/')[-1]
image = io.imread(image_path)/255.
[h, w, c] = image.shape
info = sio.loadmat(mat_path)
pose_para = info['Pose_Para'].T.astype(np.float32)
shape_para = info['Shape_Para'].astype(np.float32)
exp_para = info['Exp_Para'].astype(np.float32)
# 2. generate mesh
# generate shape
vertices = bfm.generate_vertices(shape_para, exp_para)
# transform mesh
s = pose_para[-1, 0]
angles = pose_para[:3, 0]
t = pose_para[3:6, 0]
transformed_vertices = bfm.transform_3ddfa(vertices, s, angles, t)
projected_vertices = transformed_vertices.copy() # using stantard camera & orth projection as in 3DDFA
image_vertices = projected_vertices.copy()
image_vertices[:,1] = h - image_vertices[:,1] - 1
# 3. crop image with key points
kpt = image_vertices[bfm.kpt_ind, :].astype(np.int32)
left = np.min(kpt[:, 0])
right = np.max(kpt[:, 0])
top = np.min(kpt[:, 1])
bottom = np.max(kpt[:, 1])
center = np.array([right - (right - left) / 2.0,
bottom - (bottom - top) / 2.0])
old_size = (right - left + bottom - top)/2
size = int(old_size*1.5)
# random pertube. you can change the numbers
marg = old_size*0.1
t_x = np.random.rand()*marg*2 - marg
t_y = np.random.rand()*marg*2 - marg
center[0] = center[0]+t_x; center[1] = center[1]+t_y
size = size*(np.random.rand()*0.2 + 0.9)
# crop and record the transform parameters
src_pts = np.array([[center[0]-size/2, center[1]-size/2], [center[0] - size/2, center[1]+size/2], [center[0]+size/2, center[1]-size/2]])
DST_PTS = np.array([[0, 0], [0, image_h - 1], [image_w - 1, 0]])
tform = skimage.transform.estimate_transform('similarity', src_pts, DST_PTS)
cropped_image = skimage.transform.warp(image, tform.inverse, output_shape=(image_h, image_w))
# transform face position(image vertices) along with 2d facial image
position = image_vertices.copy()
position[:, 2] = 1
position = np.dot(position, tform.params.T)
position[:, 2] = image_vertices[:, 2]*tform.params[0, 0] # scale z
position[:, 2] = position[:, 2] - np.min(position[:, 2]) # translate z
# 4. uv position map: render position in uv space
uv_position_map = mesh_cython.render.render_colors(uv_coords, bfm.full_triangles, position, uv_h, uv_w, c = 3)
# 5. save files
io.imsave('{}/{}'.format(save_folder, image_name), np.squeeze(cropped_image))
np.save('{}/{}'.format(save_folder, image_name.replace('jpg', 'npy')), uv_position_map)
io.imsave('{}/{}'.format(save_folder, image_name.replace('.jpg', '_posmap.jpg')), (uv_position_map)/max(image_h, image_w)) # only for show
# --verify
# import cv2
# uv_texture_map_rec = cv2.remap(cropped_image, uv_position_map[:,:,:2].astype(np.float32), None, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT,borderValue=(0))
# io.imsave('{}/{}'.format(save_folder, image_name.replace('.jpg', '_tex.jpg')), np.squeeze(uv_texture_map_rec))
if __name__ == '__main__':
save_folder = 'results/posmap_300WLP'
if not os.path.exists(save_folder):
os.mkdir(save_folder)
# set para
uv_h = uv_w = 256
image_h = image_w = 256
# load uv coords
global uv_coords
uv_coords = face3d.morphable_model.load.load_uv_coords('Data/BFM/Out/BFM_UV.mat') #
uv_coords = process_uv(uv_coords, uv_h, uv_w)
# load bfm
bfm = MorphabelModel('Data/BFM/Out/BFM.mat')
# run
image_path = 'Data/IBUG_image_008_1_0.jpg'
mat_path = 'Data/IBUG_image_008_1_0.mat'
run_posmap_300W_LP(bfm, image_path, mat_path, save_folder)