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Run the following command:
python extract_bboxes.py --proj_root=/data1/zhouwx/hf2vad-master/ --dataset_name=ped2 --mode=train
Problem:
Traceback (most recent call last):
File "data/hf2vad-master/extract_bboxes.py", line 161, in
obj_bboxes_extraction(dataset_root=os.path.join(args.proj_root, "data"),
File "/data/hf2vad-master/extract_bboxes.py", line 149, in obj_bboxes_extraction
np.save(os.path.join(os.path.join(dataset_root, dataset_name),
File "<array_function internals>", line 200, in save
File "/data/anaconda3/envs/pytorch1.10/lib/python3.9/site-packages/numpy/lib/npyio.py", line 521, in save
arr = np.asanyarray(arr)
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (2010,) + inhomogeneous part.
Should I change the npyio.py to "arr = np.asanyarray(arr, dtype=object)" to solve this problem?
The text was updated successfully, but these errors were encountered:
The problem seems to be solved by changing the code.
By the way, can this work detect specific anomalies in the video, like 'video anomaly localization'?
For example, how the red bonding boxes in the Fig5 come about? Are they manually marked? Thanks a lot if any body can answer this question!
Run the following command:
python extract_bboxes.py --proj_root=/data1/zhouwx/hf2vad-master/ --dataset_name=ped2 --mode=train
Problem:
Traceback (most recent call last):
File "data/hf2vad-master/extract_bboxes.py", line 161, in
obj_bboxes_extraction(dataset_root=os.path.join(args.proj_root, "data"),
File "/data/hf2vad-master/extract_bboxes.py", line 149, in obj_bboxes_extraction
np.save(os.path.join(os.path.join(dataset_root, dataset_name),
File "<array_function internals>", line 200, in save
File "/data/anaconda3/envs/pytorch1.10/lib/python3.9/site-packages/numpy/lib/npyio.py", line 521, in save
arr = np.asanyarray(arr)
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (2010,) + inhomogeneous part.
Should I change the npyio.py to "arr = np.asanyarray(arr, dtype=object)" to solve this problem?
The text was updated successfully, but these errors were encountered: