def main(image_id):
# whether from the PNG are used or new colors are generated
generate_new_colors = True
json_file = 'panoptic_val2017.json'
segmentations_folder = './panoptic_val2017/'
pred_folder = './panoptic_pred2017/'
img_folder = '/Users/wuyangxin/Desktop/cv/dataset/coco/val2017'
panoptic_coco_categories = './panoptic_coco_categories.json'
with open(json_file, 'r') as f:
coco_d = json.load(f)
# ann = np.random.choice(coco_d['annotations'])
ann = None
for a in coco_d['annotations']:
if a['image_id'] == image_id:
ann = a
break
with open(panoptic_coco_categories, 'r') as f:
categories_list = json.load(f)
categegories = {category['id']: category for category in categories_list}
# find input img that correspond to the annotation
img = None
pred_img = None
for image_info in coco_d['images']:
if image_info['id'] == ann['image_id']:
try:
img = np.array(
Image.open(
os.path.join(img_folder, image_info['file_name'])))
pred_img = Image.open(
os.path.join(pred_folder,
image_info['file_name'].replace('jpg',
'png')))
except:
print("Undable to find correspoding input image.")
break
segmentation = np.array(Image.open(
os.path.join(segmentations_folder, ann['file_name'])),
dtype=np.uint8)
segmentation_id = rgb2id(segmentation)
# find segments boundaries
boundaries = find_boundaries(segmentation_id, mode='thick')
if generate_new_colors:
segmentation[:, :, :] = 0
color_generator = IdGenerator(categegories)
for segment_info in ann['segments_info']:
color = color_generator.get_color(segment_info['category_id'])
mask = segmentation_id == segment_info['id']
segmentation[mask] = color
# depict boundaries
# segmentation[boundaries] = [0, 0, 0]
if img is None:
plt.figure()
plt.imshow(segmentation)
plt.axis('off')
else:
plt.figure(figsize=(9, 5))
plt.subplot(131)
plt.imshow(img)
plt.axis('off')
plt.subplot(132)
plt.imshow(segmentation)
plt.axis('off')
plt.subplot(133)
plt.imshow(pred_img)
plt.axis('off')
plt.tight_layout()
plt.show()
except:
print("Undable to find correspoding input image.")
break
segmentation = np.array(Image.open(
os.path.join(segmentations_folder, ann['file_name'])),
dtype=np.uint8)
segmentation_id = rgb2id(segmentation)
# find segments boundaries
boundaries = find_boundaries(segmentation_id, mode='thick')
if generate_new_colors:
segmentation[:, :, :] = 0
color_generator = IdGenerator(categegories)
for segment_info in ann['segments_info']:
color = color_generator.get_color(segment_info['category_id'])
mask = segmentation_id == segment_info['id']
segmentation[mask] = color
# depict boundaries
segmentation[boundaries] = [0, 0, 0]
if img is None:
plt.figure()
plt.imshow(segmentation)
plt.axis('off')
else:
plt.figure(figsize=(20, 10))
plt.subplot(121)
plt.imshow(img)
plt.axis('off')