diff --git a/README.md b/README.md index fc231f5..88eb005 100644 --- a/README.md +++ b/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() ``` -results1 +results1 @@ -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. diff --git a/results2.png b/results2.png index 7a8b970..c3df1f8 100644 Binary files a/results2.png and b/results2.png differ diff --git a/test.png b/test.png index c3ca0be..f9954d9 100755 Binary files a/test.png and b/test.png differ