You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
---> seed has been set
---> model and optimizer have been set
pw3d: 37
WARNING: You are using a SMPL model, with only 10 shape coefficients.
WARNING: You are using a SMPL model, with only 10 shape coefficients.
WARNING: You are using a SMPL model, with only 10 shape coefficients.
1%| | 200/35515 [09:03<23:55:21, 2.44s/it]Step:199: MPJPE:108.14312744140625, PAMPJPE:52.69846725463867, PVE:94.87768046557903
1%| | 400/35515 [17:31<28:17:38, 2.90s/it]Step:399: MPJPE:99.1795425415039, PAMPJPE:47.766239166259766, PVE:88.05403053760529
2%|▏ | 600/35515 [25:37<13:24:34, 1.38s/it]Step:599: MPJPE:91.56452178955078, PAMPJPE:47.820899963378906, PVE:84.10537596791983
2%|▏ | 800/35515 [30:35<18:15:24, 1.89s/it]Step:799: MPJPE:84.9598159790039, PAMPJPE:44.537147521972656, PVE:82.7759880432859
3%|▎ | 1000/35515 [37:18<28:50:51, 3.01s/it]Step:999: MPJPE:79.5338134765625, PAMPJPE:42.920555114746094, PVE:81.89351376518607
3%|▎ | 1200/35515 [45:19<19:36:31, 2.06s/it]Step:1199: MPJPE:76.7173080444336, PAMPJPE:42.85281753540039, PVE:82.61778503345947
4%|▍ | 1400/35515 [50:35<19:12:54, 2.03s/it]Step:1399: MPJPE:74.18508911132812, PAMPJPE:40.78797912597656, PVE:80.56003755224603
5%|▍ | 1600/35515 [56:14<15:07:32, 1.61s/it]Step:1599: MPJPE:73.13909912109375, PAMPJPE:41.25379943847656, PVE:77.55705753806978
5%|▌ | 1800/35515 [1:00:38<10:39:45, 1.14s/it]Step:1799: MPJPE:72.77523803710938, PAMPJPE:42.25539016723633, PVE:76.45247981366184
6%|▌ | 2000/35515 [1:05:01<9:35:38, 1.03s/it]Step:1999: MPJPE:73.12327575683594, PAMPJPE:42.23678970336914, PVE:76.57051902078092
6%|▌ | 2200/35515 [1:09:42<14:54:10, 1.61s/it]Step:2199: MPJPE:72.85092163085938, PAMPJPE:41.97563171386719, PVE:75.81348557533188
7%|▋ | 2400/35515 [1:13:13<11:36:43, 1.26s/it]Step:2399: MPJPE:71.45988464355469, PAMPJPE:41.051570892333984, PVE:74.75854421810557
7%|▋ | 2600/35515 [1:17:23<10:32:56, 1.15s/it]Step:2599: MPJPE:71.4017562866211, PAMPJPE:41.07121276855469, PVE:76.12829965467637
8%|▊ | 2800/35515 [1:21:17<6:36:03, 1.38it/s]Step:2799: MPJPE:70.69111633300781, PAMPJPE:41.131832122802734, PVE:76.1530753770577
8%|▊ | 3000/35515 [1:24:56<8:37:23, 1.05it/s]Step:2999: MPJPE:69.84212493896484, PAMPJPE:40.65814971923828, PVE:75.713991060853
9%|▉ | 3200/35515 [1:29:11<9:58:27, 1.11s/it]Step:3199: MPJPE:68.54174041748047, PAMPJPE:39.8968620300293, PVE:74.9515091557987
9%|▉ | 3257/35515 [1:30:18<14:54:30, 1.66s/it]
Traceback (most recent call last):
File "/home/DynaBOA/dynaboa_benchmark.py", line 292, in
adaptor.excute()
File "/home/DynaBOA/dynaboa_benchmark.py", line 89, in excute
for step, batch in tqdm(enumerate(self.dataloader), total=len(self.dataloader)):
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/tqdm/std.py", line 1166, in iter
for obj in iterable:
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 517, in next
data = self._next_data()
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 1199, in _next_data
return self._process_data(data)
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 1225, in _process_data
data.reraise()
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/torch/_utils.py", line 429, in reraise
raise self.exc_type(msg) TypeError: Caught TypeError in DataLoader worker process 1.
Original Traceback (most recent call last):
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/torch/utils/data/_utils/worker.py", line 202, in _worker_loop
data = fetcher.fetch(index)
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/DynaBOA/boa_dataset/pw3d.py", line 101, in getitem
image = self.read_image(imgname, index)
File "/home/DynaBOA/boa_dataset/pw3d.py", line 146, in read_image
img = cv2.imread(imgname)[:, :, ::-1].copy().astype(np.float32) TypeError: 'NoneType' object is not subscriptable
Process finished with exit code 1
The errors all drop quickly but ... have you ever met this problem? I tried but failed to find where this error comes from.
It seems that some data are needed but missed. Maybe the labeled data?
I'm sure I followed all your descriptions and the human3.6m and 3dpw data has placed properly and input totally.
Could you please give me a little guidance? I'll be very appreciated it. Thank you!
The text was updated successfully, but these errors were encountered:
Hi! There I meet a problem :
---> seed has been set
---> model and optimizer have been set
pw3d: 37
WARNING: You are using a SMPL model, with only 10 shape coefficients.
WARNING: You are using a SMPL model, with only 10 shape coefficients.
WARNING: You are using a SMPL model, with only 10 shape coefficients.
1%| | 200/35515 [09:03<23:55:21, 2.44s/it]Step:199: MPJPE:108.14312744140625, PAMPJPE:52.69846725463867, PVE:94.87768046557903
1%| | 400/35515 [17:31<28:17:38, 2.90s/it]Step:399: MPJPE:99.1795425415039, PAMPJPE:47.766239166259766, PVE:88.05403053760529
2%|▏ | 600/35515 [25:37<13:24:34, 1.38s/it]Step:599: MPJPE:91.56452178955078, PAMPJPE:47.820899963378906, PVE:84.10537596791983
2%|▏ | 800/35515 [30:35<18:15:24, 1.89s/it]Step:799: MPJPE:84.9598159790039, PAMPJPE:44.537147521972656, PVE:82.7759880432859
3%|▎ | 1000/35515 [37:18<28:50:51, 3.01s/it]Step:999: MPJPE:79.5338134765625, PAMPJPE:42.920555114746094, PVE:81.89351376518607
3%|▎ | 1200/35515 [45:19<19:36:31, 2.06s/it]Step:1199: MPJPE:76.7173080444336, PAMPJPE:42.85281753540039, PVE:82.61778503345947
4%|▍ | 1400/35515 [50:35<19:12:54, 2.03s/it]Step:1399: MPJPE:74.18508911132812, PAMPJPE:40.78797912597656, PVE:80.56003755224603
5%|▍ | 1600/35515 [56:14<15:07:32, 1.61s/it]Step:1599: MPJPE:73.13909912109375, PAMPJPE:41.25379943847656, PVE:77.55705753806978
5%|▌ | 1800/35515 [1:00:38<10:39:45, 1.14s/it]Step:1799: MPJPE:72.77523803710938, PAMPJPE:42.25539016723633, PVE:76.45247981366184
6%|▌ | 2000/35515 [1:05:01<9:35:38, 1.03s/it]Step:1999: MPJPE:73.12327575683594, PAMPJPE:42.23678970336914, PVE:76.57051902078092
6%|▌ | 2200/35515 [1:09:42<14:54:10, 1.61s/it]Step:2199: MPJPE:72.85092163085938, PAMPJPE:41.97563171386719, PVE:75.81348557533188
7%|▋ | 2400/35515 [1:13:13<11:36:43, 1.26s/it]Step:2399: MPJPE:71.45988464355469, PAMPJPE:41.051570892333984, PVE:74.75854421810557
7%|▋ | 2600/35515 [1:17:23<10:32:56, 1.15s/it]Step:2599: MPJPE:71.4017562866211, PAMPJPE:41.07121276855469, PVE:76.12829965467637
8%|▊ | 2800/35515 [1:21:17<6:36:03, 1.38it/s]Step:2799: MPJPE:70.69111633300781, PAMPJPE:41.131832122802734, PVE:76.1530753770577
8%|▊ | 3000/35515 [1:24:56<8:37:23, 1.05it/s]Step:2999: MPJPE:69.84212493896484, PAMPJPE:40.65814971923828, PVE:75.713991060853
9%|▉ | 3200/35515 [1:29:11<9:58:27, 1.11s/it]Step:3199: MPJPE:68.54174041748047, PAMPJPE:39.8968620300293, PVE:74.9515091557987
9%|▉ | 3257/35515 [1:30:18<14:54:30, 1.66s/it]
Traceback (most recent call last):
File "/home/DynaBOA/dynaboa_benchmark.py", line 292, in
adaptor.excute()
File "/home/DynaBOA/dynaboa_benchmark.py", line 89, in excute
for step, batch in tqdm(enumerate(self.dataloader), total=len(self.dataloader)):
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/tqdm/std.py", line 1166, in iter
for obj in iterable:
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 517, in next
data = self._next_data()
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 1199, in _next_data
return self._process_data(data)
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 1225, in _process_data
data.reraise()
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/torch/_utils.py", line 429, in reraise
raise self.exc_type(msg)
TypeError: Caught TypeError in DataLoader worker process 1.
Original Traceback (most recent call last):
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/torch/utils/data/_utils/worker.py", line 202, in _worker_loop
data = fetcher.fetch(index)
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/miniconda3/envs/DynaBOA-env/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/DynaBOA/boa_dataset/pw3d.py", line 101, in getitem
image = self.read_image(imgname, index)
File "/home/DynaBOA/boa_dataset/pw3d.py", line 146, in read_image
img = cv2.imread(imgname)[:, :, ::-1].copy().astype(np.float32)
TypeError: 'NoneType' object is not subscriptable
Process finished with exit code 1
The errors all drop quickly but ... have you ever met this problem? I tried but failed to find where this error comes from.
It seems that some data are needed but missed. Maybe the labeled data?
I'm sure I followed all your descriptions and the human3.6m and 3dpw data has placed properly and input totally.
Could you please give me a little guidance? I'll be very appreciated it. Thank you!
The text was updated successfully, but these errors were encountered: