gt_bboxes = copy.deepcopy([item['bbox'] for item in results["ann"]["annotations"]][self.random_ind])
But still,
File "/home/user/workspace/SimVG/simvg/datasets/pipelines/loading.py", line 286,in__call__
results self._load bboxes(results)
File "/home/gpu18/workspace/SimVG/simvg/datasets/pipelines/loading.py", line 239, in _load_bboxes
gt_bbox[2] = gt_bbox[0] + gt_bbox[2]
TypeError:'float'object is not subscriptable
The reason might be that there is no corresponding bboxes in the image, causing the error.
result ann: [None]
result ann: [[219.85, 14.45, 319.01, 69.5]]
result ann: [[291.23, 88.74, 188.77, 269.45], [1.61, 88.74, 172.65, 266.23]]
@Dmmm1997 Could you please share the code for training on the GrefCOCO dataset?
I encountered a similar issue (#3 ), and my solution was to modify the
loading.py
file https://github.com/Dmmm1997/SimVG/blob/b7319ca5f24cd3f46cbe566010288f83b8c9268b/simvg/datasets/pipelines/loading.py#L157-L158but after that, I ran into many other issues.
I also modified that: https://github.com/Dmmm1997/SimVG/blob/b7319ca5f24cd3f46cbe566010288f83b8c9268b/simvg/datasets/pipelines/loading.py#L224-L226
But still,
The reason might be that there is no corresponding bboxes in the image, causing the error.
@Dmmm1997 Could you please share the code for training on the GrefCOCO dataset?