def vis_parsing(img, parsing, colormap, show_segms=True):
"""Visualizes a single binary parsing."""
img = img.astype(np.float32)
idx = np.nonzero(parsing)
# for i in range(20):
# print(parsing[parsing == i])
# if i == 15:
# parsing[parsing == i] = 1
# print(i)
parsing_alpha = 0.4
colormap = colormap_utils.dict2array(colormap)
parsing_color = colormap[parsing.astype(np.int)]
border_color = (255, 255, 255)
border_thick = 1
img[idx[0], idx[1], :] *= (1.0 - parsing_alpha)
# img[idx[0], idx[1], :] += alpha * parsing_color
print(img.shape, parsing_color.shape)
img += parsing_alpha * parsing_color
# if cfg.VIS.SHOW_PARSS.SHOW_BORDER and not show_segms:
# _, contours, _ = cv2.findContours(parsing.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
# cv2.drawContours(img, contours, -1, border_color, border_thick, cv2.LINE_AA)
return parsing_color.astype(np.uint8)
def vis_parsing(path):
parsing = cv2.imread(path, 0)
parsing_color_list = eval('colormap_utils.{}'.format('CIHP20')) # CIHP20
parsing_color_list = colormap_utils.dict_bgr2rgb(parsing_color_list)
colormap = colormap_utils.dict2array(parsing_color_list)
parsing_color = colormap[parsing.astype(np.int)]
cv2.imwrite('vis_train_{}_{}.png'.format(str(10), str(10)), parsing_color)
def vis_parsing333(path, dir):
parsing = cv2.imread(path, 0)
parsing_color_list = eval('colormap_utils.{}'.format('MHP59')) # CIHP20
parsing_color_list = colormap_utils.dict_bgr2rgb(parsing_color_list)
colormap = colormap_utils.dict2array(parsing_color_list)
parsing_color = colormap[parsing.astype(np.int)]
cv2.imwrite(os.path.join(dir, os.path.basename(path)), parsing_color)
def vis_parsing(path, dir, colormap, im_ori, draw_contours):
parsing = cv2.imread(path, 0)
parsing_color_list = eval('colormap_utils.{}'.format(colormap)) # CIHP20
parsing_color_list = colormap_utils.dict_bgr2rgb(parsing_color_list)
colormap = colormap_utils.dict2array(parsing_color_list)
parsing_color = colormap[parsing.astype(np.int)]
parsing_alpha = 0.9
idx = np.nonzero(parsing)
im_ori = im_ori.astype(np.float32)
im_ori[idx[0], idx[1], :] *= 1.0 - parsing_alpha
im_ori += parsing_alpha * parsing_color
######
if draw_contours:
contours, _ = cv2.findContours(parsing.copy(), cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
parsing_color = parsing_color.astype(np.uint8)
cv2.drawContours(im_ori, contours, -1, (0, 0, 255), 1)
# M = cv2.moments(contours[1]) # 计算第一条轮廓的各阶矩,字典形式
# center_x = int(M["m10"] / M["m00"])
# center_y = int(M["m01"] / M["m00"])
# cv2.circle(parsing_color, (center_x, center_y), 30, 128, -1) # 绘制中心点
# print(center_x, center_y)
cv2.imwrite(os.path.join(dir, os.path.basename(path)), im_ori)
def vis_parsing_dir(new_dir, colormap, img_dir, parsing_dir, draw_contours):
coco_folder = '/xuhanzhu/mscoco2014'
cihp_coco = COCO(coco_folder +
'/annotations/densepose_coco_2014_train.json')
im_ids = cihp_coco.getImgIds()
for im_id in sorted(im_ids):
im = cihp_coco.loadImgs(im_id)[0]
filename = im['file_name']
ori_path = os.path.join(img_dir, filename)
new_path = os.path.join(new_dir, filename)
parsing_path = os.path.join(parsing_dir,
filename.replace('.jpg', '.png'))
parsing = cv2.imread(parsing_path, 0)
if os.path.exists(ori_path):
im_ori = cv2.imread(ori_path)
parsing_color_list = eval(
'colormap_utils.{}'.format('MHP59')) # CIHP20
parsing_color_list = colormap_utils.dict_bgr2rgb(
parsing_color_list)
colormap = colormap_utils.dict2array(parsing_color_list)
parsing_color = colormap[parsing.astype(np.int)]
# parsing_color = parsing_color[..., ::-1]
parsing_alpha = 0.9
idx = np.nonzero(parsing)
im_ori = im_ori.astype(np.float32)
im_ori[idx[0], idx[1], :] *= 1.0 - parsing_alpha
im_ori += parsing_alpha * parsing_color
#####
if draw_contours:
contours, _ = cv2.findContours(parsing.copy(), cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
cv2.drawContours(im_ori, contours, -1, (0, 0, 255), 1)
cv2.imwrite(new_path, im_ori)
else:
continue
im_ids = cihp_coco.getImgIds()
Selected_im = im_ids[randint(0, len(im_ids))]
Selected_im = 17144
im = cihp_coco.loadImgs(Selected_im)[0]
ann_ids = cihp_coco.getAnnIds(imgIds=im['id'])
anns = cihp_coco.loadAnns(ann_ids)
im_name = os.path.join(coco_folder + 'train_img', im['file_name'])
mask_name = os.path.join(coco_folder + 'train_seg',
im['file_name'].replace('jpg', 'png'))
for i, obj in enumerate(anns):
parsing_name = os.path.join(coco_folder + 'train_parsing', obj['parsing'])
parsing = cv2.imread(parsing_name, 0)
parsing_color_list = eval('colormap_utils.{}'.format('CIHP20')) # CIHP20
parsing_color_list = colormap_utils.dict_bgr2rgb(parsing_color_list)
colormap = colormap_utils.dict2array(parsing_color_list)
parsing_color = colormap[parsing.astype(np.int)]
cv2.imwrite('vis_train_{}_{}.png'.format(str(Selected_im), str(i)),
parsing_color)
# if os.path.exists(im_name) and os.path.exists(mask_name):
# print('Exits', im_name, mask_name)
# I = cv2.imread(im_name)
# mask = cv2.imread(mask_name, 0)
# # ins_pars = mask.numpy() # [instance].parsing
# # ins_pars = np.array(F.to_pil_image(mask))
# mask = np.reshape(mask, I.shape[:2])
# # h, w = mask.shape[:2]
# parsing_color_list = eval('colormap_utils.{}'.format('CIHP20')) # CIHP20
# parsing_color_list = colormap_utils.dict_bgr2rgb(parsing_color_list)
# # I[0:h, 0:w, :] = vis_parsing(I[0:h, 0:w, :], mask, parsing_color_list)
# I = vis_parsing(I, mask, parsing_color_list)