Update yolov5 README

Signed-off-by: shiyu22 <shiyu.chen@zilliz.com>

README.md

@@ -29,7 +29,7 @@ Writing the pipeline in the simplified way
 ```Python
 import towhee
 
-towhee.glob('./test.jpg') \
+towhee.glob('./test.png') \
 	.image_decode() \
 	.object_detection.yolov5() \
 	.show()
@@ -45,11 +45,12 @@ import towhee
 towhee.glob['path']('./test.png') \
 	.image_decode['path','img']() \
 	.object_detection.yolov5['img', ('box', 'class', 'score')]() \
-	.select('box', 'class', 'score') \
+	.image_crop[('img', 'box'), 'object'](clamp = True) \
+	.select['img','object']() \
 	.show()
 ```
 
-<img src="./results2.png" alt="results1" height="90px"/>
+<img src="./results2.png" alt="results1" height="190px"/>
 
 
 
@@ -81,7 +82,7 @@ The operator takes an image as input. It first detects the objects appeared in t
 
 
 
-**Return**: List[(int, int, int, int)], List[str], List[float]
+**Return**: List[List[(int, int, int, int)], ...], List[str], List[float]
 
 The return value is a tuple of (boxes, classes, scores). The *boxes* is a list of bounding boxes. Each bounding box is represented by the top-left and the bottom right points, i.e. (x1, y1, x2, y2). The *classes* is a list of prediction labels. The *scores* is a list of the confidence scores.