91 lines
2.9 KiB
Python
91 lines
2.9 KiB
Python
import glob
|
|
import json
|
|
import os
|
|
|
|
import cv2
|
|
import numpy as np
|
|
|
|
|
|
def get_mask_from_json(json_path, img):
|
|
try:
|
|
with open(json_path, "r") as r:
|
|
anno = json.loads(r.read())
|
|
except:
|
|
with open(json_path, "r", encoding="cp1252") as r:
|
|
anno = json.loads(r.read())
|
|
|
|
inform = anno["shapes"]
|
|
comments = anno["text"]
|
|
is_sentence = anno["is_sentence"]
|
|
|
|
height, width = img.shape[:2]
|
|
|
|
### sort polies by area
|
|
area_list = []
|
|
valid_poly_list = []
|
|
for i in inform:
|
|
label_id = i["label"]
|
|
points = i["points"]
|
|
if "flag" == label_id.lower(): ## meaningless deprecated annotations
|
|
continue
|
|
|
|
tmp_mask = np.zeros((height, width), dtype=np.uint8)
|
|
cv2.polylines(tmp_mask, np.array([points], dtype=np.int32), True, 1, 1)
|
|
cv2.fillPoly(tmp_mask, np.array([points], dtype=np.int32), 1)
|
|
tmp_area = tmp_mask.sum()
|
|
|
|
area_list.append(tmp_area)
|
|
valid_poly_list.append(i)
|
|
|
|
### ground-truth mask
|
|
sort_index = np.argsort(area_list)[::-1].astype(np.int32)
|
|
sort_index = list(sort_index)
|
|
sort_inform = []
|
|
for s_idx in sort_index:
|
|
sort_inform.append(valid_poly_list[s_idx])
|
|
|
|
mask = np.zeros((height, width), dtype=np.uint8)
|
|
for i in sort_inform:
|
|
label_id = i["label"]
|
|
points = i["points"]
|
|
|
|
if "ignore" in label_id.lower():
|
|
label_value = 255 # ignored during evaluation
|
|
else:
|
|
label_value = 1 # target
|
|
|
|
cv2.polylines(mask, np.array([points], dtype=np.int32), True, label_value, 1)
|
|
cv2.fillPoly(mask, np.array([points], dtype=np.int32), label_value)
|
|
|
|
return mask, comments, is_sentence
|
|
|
|
|
|
if __name__ == "__main__":
|
|
data_dir = "./train"
|
|
vis_dir = "./vis"
|
|
|
|
if not os.path.exists(vis_dir):
|
|
os.makedirs(vis_dir)
|
|
|
|
json_path_list = sorted(glob.glob(data_dir + "/*.json"))
|
|
for json_path in json_path_list:
|
|
img_path = json_path.replace(".json", ".jpg")
|
|
img = cv2.imread(img_path)[:, :, ::-1]
|
|
|
|
# In generated mask, value 1 denotes valid target region, and value 255 stands for region ignored during evaluaiton.
|
|
mask, comments, is_sentence = get_mask_from_json(json_path, img)
|
|
|
|
## visualization. Green for target, and red for ignore.
|
|
valid_mask = (mask == 1).astype(np.float32)[:, :, None]
|
|
ignore_mask = (mask == 255).astype(np.float32)[:, :, None]
|
|
vis_img = img * (1 - valid_mask) * (1 - ignore_mask) + (
|
|
(np.array([0, 255, 0]) * 0.6 + img * 0.4) * valid_mask
|
|
+ (np.array([255, 0, 0]) * 0.6 + img * 0.4) * ignore_mask
|
|
)
|
|
vis_img = np.concatenate([img, vis_img], 1)
|
|
vis_path = os.path.join(
|
|
vis_dir, json_path.split("/")[-1].replace(".json", ".jpg")
|
|
)
|
|
cv2.imwrite(vis_path, vis_img[:, :, ::-1])
|
|
print("Visualization has been saved to: ", vis_path)
|