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hub / github.com/drinkingcoder/FlowFormer-Official / KITTI

Class KITTI

core/utils/datasets.py:225–261  ·  view source on GitHub ↗

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223
224
225class KITTI(FlowDataset):
226 def __init__(self, aug_params=None, split='training', root='datasets/KITTI'):
227 super(KITTI, self).__init__(aug_params, sparse=True)
228 if split == 'testing':
229 self.is_test = True
230
231 root = 's3://'
232
233 self.image_list = []
234 with open("./flow_dataset/KITTI/KITTI_{}_image.txt".format(split)) as f:
235 images = f.readlines()
236 for img1, img2 in zip(images[0::2], images[1::2]):
237 self.image_list.append([root+img1.strip(), root+img2.strip()])
238
239 self.extra_info = []
240 with open("./flow_dataset/KITTI/KITTI_{}_extra_info.txt".format(split)) as f:
241 info = f.readlines()
242 for id in info:
243 self.extra_info.append([id.strip()])
244
245 if split == "training":
246 self.flow_list = []
247 with open("./flow_dataset/KITTI/KITTI_{}_flow.txt".format(split)) as f:
248 flow = f.readlines()
249 for flo in flow:
250 self.flow_list.append(root+flo.strip())
251 # root = osp.join(root, split)
252 # images1 = sorted(glob(osp.join(root, 'image_2/*_10.png')))
253 # images2 = sorted(glob(osp.join(root, 'image_2/*_11.png')))
254
255 # for img1, img2 in zip(images1, images2):
256 # frame_id = img1.split('/')[-1]
257 # self.extra_info += [ [frame_id] ]
258 # self.image_list += [ [img1, img2] ]
259
260 # if split == 'training':
261 # self.flow_list = sorted(glob(osp.join(root, 'flow_occ/*_10.png')))
262
263class AutoFlow(data.Dataset):
264 def __init__(self, num_steps, crop_size, log_dir, root='datasets/'):

Callers 1

fetch_dataloaderFunction · 0.70

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