|  | @ -25,8 +25,9 @@ to classify and generate a vector for the given video path './archery.mp4' ([dow | 
		
	
		
			
				|  |  | import towhee |  |  | import towhee | 
		
	
		
			
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				|  |  | ( |  |  | ( | 
		
	
		
			
				|  |  |     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 | 
		
	
		
			
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				|  |  | ( |  |  | ( | 
		
	
		
			
				|  |  |     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 | 
		
	
		
			
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				|  |  | Create the operator via the following factory method |  |  | Create the operator via the following factory method | 
		
	
		
			
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				|  |  | ***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)*** | 
		
	
		
			
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				|  |  | **Parameters:** |  |  | **Parameters:** | 
		
	
		
			
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				|  |  | 	***model_name***: *str* |  |  | 	***model_name***: *str* | 
		
	
		
			
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				|  |  | 	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 | 
		
	
		
			
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				|  |  | 	***skip_preprocess***: *bool* |  |  | 	***skip_preprocess***: *bool* | 
		
	
		
			
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