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[Fix] Dimension Mismatch in 5D Tensor Permute Operation in visualization_hook.py #2697

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[Fix] Dimension Mismatch in 5D Tensor Permute Operation in visualization_hook.py #2697

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0be15dd
[Fix] dimension mismatch in permute operation
kim-jeonghyun Oct 3, 2023
280dc21
[Fix] Dimension mismatch in permute operation
kim-jeonghyun Oct 3, 2023
064a0be
[fix] Format code to meet line length constraints
kim-jeonghyun Oct 3, 2023
f57c116
[Fix] Format code to meet code contraints
kim-jeonghyun Oct 3, 2023
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48 changes: 25 additions & 23 deletions mmaction/engine/hooks/visualization_hook.py
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Original file line number Diff line number Diff line change
Expand Up @@ -78,29 +78,31 @@ def _draw_samples(self,
for sample_id in range(first_sample_id, end_idx, self.interval):
video = videos[sample_id - start_idx]
# move channel to the last
video = video.permute(1, 2, 3, 0).numpy().astype('uint8')

data_sample = data_samples[sample_id - start_idx]
if 'filename' in data_sample:
# osp.basename works on different platforms even file clients.
sample_name = osp.basename(data_sample.get('filename'))
elif 'frame_dir' in data_sample:
sample_name = osp.basename(data_sample.get('frame_dir'))
else:
sample_name = str(sample_id)

draw_args = self.draw_args
if self.out_dir is not None:
draw_args['out_path'] = self.file_client.join_path(
self.out_dir, f'{sample_name}_{step}')

self._visualizer.add_datasample(
sample_name,
video=video,
data_sample=data_sample,
step=step,
**self.draw_args,
)
for i in range(video.shape[0]):
single_video = video[i].permute(1, 2, 3,
0).numpy().astype('uint8')
data_sample = data_samples[sample_id - start_idx]
if 'filename' in data_sample:
# osp.basename works on different platforms
# even file clients.
sample_name = osp.basename(data_sample.get('filename'))
elif 'frame_dir' in data_sample:
sample_name = osp.basename(data_sample.get('frame_dir'))
else:
sample_name = str(sample_id)

draw_args = self.draw_args
if self.out_dir is not None:
draw_args['out_path'] = self.file_client.join_path(
self.out_dir, f'{sample_name}_{step}')

self._visualizer.add_datasample(
sample_name,
video=single_video,
data_sample=data_sample,
step=step,
**self.draw_args,
)

def after_val_iter(self, runner: Runner, batch_idx: int, data_batch: dict,
outputs: Sequence[ActionDataSample]) -> None:
Expand Down