sc = bbox[4]
ex = bbox[5:13].astype(np.int32).reshape(4, 2)
bbox = bbox[0:4].astype(np.int32)
txt = '{}{:.2f}'.format(cat_name, sc)
color_mask = color_list[mask_color_id % len(color_list), :3]
mask_color_id += 1
# image = vis_bbox(image,
# (bbox[0], bbox[1],
# bbox[2] - bbox[0], bbox[3] - bbox[1]))
image = vis_class(image,
(bbox[0], bbox[1] - 2), txt)
# image = vis_octagon( image, ex, color_mask)
image = vis_ex(image, ex, color_mask)
# if args.show_mask:
mask = dextr.segment(input_image[:, :, ::-1], ex) # BGR to RGB
mask = np.asfortranarray(mask.astype(np.uint8))
mask_image = vis_bbox(mask_image,
(bbox[0], bbox[1],
bbox[2] - bbox[0],
bbox[3] - bbox[1]))
mask_image = vis_class(mask_image,
(bbox[0], bbox[1] - 2), txt)
mask_image = vis_mask(mask_image, mask, color_mask)
#yezheng: comment out
if args.show_mask:
cv2.imshow('mask', mask_image)
# cv2.imshow('out', image)
# cv2.waitKey()
# cv2.imwrite("out_images/"+ image_name.split('/')[-1].split('.')[0]+"_out.png", image)
cv2.imwrite("out_images/"+ image_name.split('/')[-1].split('.')[0]+"_out.png", mask_image)
score_thresh = 0.2
num_boxes = 0
for i, ann in enumerate(anns):
if ann['score'] >= score_thresh:
num_boxes += 1
bar = Bar('Pred + Dextr', max=num_boxes)
for i, ann in enumerate(anns):
if ann['score'] < score_thresh:
continue
ex = np.array(ann['extreme_points'], dtype=np.int32).reshape(4, 2)
img_id = ann['image_id']
img_info = coco.loadImgs(ids=[img_id])[0]
img_path = IMG_DIR + img_info['file_name']
img = cv2.imread(img_path)
mask = dextr.segment(img[:, :, ::-1], ex)
mask = np.asfortranarray(mask.astype(np.uint8))
if DEBUG:
if ann['score'] < 0.1:
continue
print(ann['score'])
img = (0.4 * img + 0.6 *
mask.reshape(mask.shape[0], mask.shape[1], 1) * 255).astype(
np.uint8)
cv2.imshow('img', img)
cv2.waitKey()
encode = COCOmask.encode(mask)
if 'counts' in encode:
encode['counts'] = encode['counts'].decode("utf8")
pred = {
'image_id': ann['image_id'],