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add5

Signed-off-by: xujinling <jinling.xu@zilliz.com>
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xujinling 2 years ago
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949ce7ab77
  1. 24
      README.md
  2. BIN
      result1.png
  3. BIN
      result2.png

24
README.md

@ -25,8 +25,9 @@ to classify and generate a vector for the given video path './archery.mp4' ([dow
import towhee import towhee
( (
towhee.glob('./archery.mp4')
.video_decode.ffmpeg()
towhee.dc(['./demo_video.mp4'])
.video_decode.ffmpeg(sample_type='uniform_temporal_subsample', args={'num_samples': 4})
.runas_op(func=lambda x: [y for y in x])
.action_classification.video_swin_transformer(model_name='swin_tiny_patch244_window877_kinetics400_1k') .action_classification.video_swin_transformer(model_name='swin_tiny_patch244_window877_kinetics400_1k')
.show() .show()
) )
@ -41,10 +42,10 @@ import towhee
import towhee import towhee
( (
towhee.glob['path']('./archery.mp4')
.video_decode.ffmpeg['path', 'frames']()
.action_classification.video_swin_transformer['frames', ('labels', 'scores', 'features')](
model_name='swin_tiny_patch244_window877_kinetics400_1k')
towhee.dc['path']('./demo_video.mp4')
.video_decode.ffmpeg['path', 'frames'](sample_type='uniform_temporal_subsample', args={'num_samples': 4})
.runas_op['frames', 'frames'](func=lambda x: [y for y in x])
.action_classification.video_swin_transformer['frames', ('labels', 'scores', 'features')](model_name='swin_tiny_patch244_window877_kinetics400_1k')
.select['path', 'labels', 'scores', 'features']() .select['path', 'labels', 'scores', 'features']()
.show(formatter={'path': 'video_path'}) .show(formatter={'path': 'video_path'})
) )
@ -57,15 +58,20 @@ import towhee
Create the operator via the following factory method Create the operator via the following factory method
***action_classification.timesformer(
model_name='timesformer_k400_8x224', skip_preprocess=False, classmap=None, topk=5)***
***action_classification.video_swin_transformer(
model_name='swin_tiny_patch244_window877_kinetics400_1k', skip_preprocess=False, classmap=None, topk=5)***
**Parameters:** **Parameters:**
***model_name***: *str* ***model_name***: *str*
​ The name of pre-trained model. Supported model names: ​ The name of pre-trained model. Supported model names:
- timesformer_k400_8x224
- swin_tiny_patch244_window877_kinetics400_1k
- swin_base_patch244_window877_kinetics400_1k
- swin_small_patch244_window877_kinetics400_1k
- swin_base_patch244_window877_kinetics400_22k
- swin_base_patch244_window877_kinetics600_22k
- swin_base_patch244_window1677_sthv2
***skip_preprocess***: *bool* ***skip_preprocess***: *bool*

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