| 
					
					
						
							
						
					
					
				 | 
				@ -22,37 +22,40 @@ This operator uses [PyTorch.yolov5](https://pytorch.org/hub/ultralytics_yolov5/) | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				
 | 
			
		
		
	
		
			
				 | 
				 | 
				### Code Example | 
				 | 
				 | 
				### Code Example | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				
 | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				Load an image from path './test.png' and use yolov5 model to detect objects in the image. | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				
 | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				*Write a same pipeline with explicit inputs/outputs name specifications:* | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				
 | 
			
		
		
	
		
			
				 | 
				 | 
				- Write the pipeline in the simplified way: | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				- **option 1: towhee>=0.9.0** | 
			
		
		
	
		
			
				 | 
				 | 
				```Python | 
				 | 
				 | 
				```Python | 
			
		
		
	
		
			
				 | 
				 | 
				import towhee | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
				towhee.glob('./test.png') \ | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
					.image_decode() \ | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
					.object_detection.yolov5() \ | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
					.show() | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
				``` | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				from towhee.dc2 import pipe, ops, DataCollection | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				
 | 
			
		
		
	
		
			
				 | 
				 | 
				<img src="./results1.png" alt="results1" height="40px"/> | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				p = ( | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				    pipe.input('path') | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				        .map('path', 'img', ops.image_decode()) | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				        .map('img', ('box', 'class', 'score'), ops.object_detection.yolov5()) | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				        .map(('img', 'box'), 'object', ops.image_crop(clamp=True)) | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				        .output('img', 'object', 'class') | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				) | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				
 | 
			
		
		
	
		
			
				 | 
				 | 
				- Write the same pipeline with explicitly specified inputs and outputs: | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				DataCollection(p('./test.png')).show() | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				``` | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				
 | 
			
		
		
	
		
			
				 | 
				 | 
				```Python | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				- **option 2:** | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				```python | 
			
		
		
	
		
			
				 | 
				 | 
				import towhee | 
				 | 
				 | 
				import towhee | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				
 | 
			
		
		
	
		
			
				 | 
				 | 
				towhee.glob['path']('./test.png') \ | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
					.image_decode['path','img']() \ | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
					.object_detection.yolov5['img', ('box', 'class', 'score')]() \ | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
					.image_crop[('img', 'box'), 'object'](clamp = True) \ | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
					.select['img','object']() \ | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
					.show() | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				( | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				    towhee.glob['path']('./test.png') | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				          .image_decode['path','img']() | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				          .object_detection.yolov5['img', ('box', 'class', 'score')]() | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				          .image_crop[('img', 'box'), 'object'](clamp = True) | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				          .select['img','object', 'class']() | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				          .show() | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				) | 
			
		
		
	
		
			
				 | 
				 | 
				``` | 
				 | 
				 | 
				``` | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				
 | 
			
		
		
	
		
			
				 | 
				 | 
				<img src="./results2.png" alt="results1" height="140px"/> | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				 | 
			
		
		
	
		
			
				 | 
				 | 
				 | 
				 | 
				 | 
				<img src="./result.png" alt="result" height="140px"/> | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				
 | 
			
		
		
	
		
			
				 | 
				 | 
				<br /> | 
				 | 
				 | 
				<br /> | 
			
		
		
	
		
			
				 | 
				 | 
				
 | 
				 | 
				 | 
				
 | 
			
		
		
	
	
		
			
				| 
					
						
							
						
					
					
					
				 | 
				
  |