T2I-Adapter / ldm /data /dataset_coco.py
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import json
import cv2
import os
from basicsr.utils import img2tensor
class dataset_coco_mask_color():
def __init__(self, path_json, root_path_im, root_path_mask, image_size):
super(dataset_coco_mask_color, self).__init__()
with open(path_json, 'r', encoding='utf-8') as fp:
data = json.load(fp)
data = data['annotations']
self.files = []
self.root_path_im = root_path_im
self.root_path_mask = root_path_mask
for file in data:
name = "%012d.png" % file['image_id']
self.files.append({'name': name, 'sentence': file['caption']})
def __getitem__(self, idx):
file = self.files[idx]
name = file['name']
# print(os.path.join(self.root_path_im, name))
im = cv2.imread(os.path.join(self.root_path_im, name.replace('.png', '.jpg')))
im = cv2.resize(im, (512, 512))
im = img2tensor(im, bgr2rgb=True, float32=True) / 255.
mask = cv2.imread(os.path.join(self.root_path_mask, name)) # [:,:,0]
mask = cv2.resize(mask, (512, 512))
mask = img2tensor(mask, bgr2rgb=True, float32=True) / 255. # [0].unsqueeze(0)#/255.
sentence = file['sentence']
return {'im': im, 'mask': mask, 'sentence': sentence}
def __len__(self):
return len(self.files)