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Merge branch 'main' of https://towhee.io/object-detection/yolov5 into main

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shiyu22 3 years ago
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      README.md

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README.md

@ -24,7 +24,7 @@ This operator uses [PyTorch.yolov5](https://pytorch.org/hub/ultralytics_yolov5/)
Writing the pipeline in the simplified way
- Write the pipeline in the simplified way:
```Python ```Python
import towhee import towhee
@ -37,7 +37,7 @@ towhee.glob('./test.png') \
<img src="./results1.png" alt="results1" height="40px"/> <img src="./results1.png" alt="results1" height="40px"/>
Writing the same pipeline with explicitly specified inputs and outputs
- Write the same pipeline with explicitly specified inputs and outputs:
```Python ```Python
import towhee import towhee
@ -60,7 +60,7 @@ towhee.glob['path']('./test.png') \
## Factory Constructor ## Factory Constructor
Create the operator via the following factory method
Create the operator via the following factory method:
***object_detection.yolov5()*** ***object_detection.yolov5()***
@ -72,7 +72,7 @@ Create the operator via the following factory method
### Interface ### Interface
The operator takes an image as input. It first detects the objects appeared in the image, and gives the bounding box of each object.
The operator takes an image as input. It first detects the objects appeared in the image, and generates a bounding box around each object.
**Parameters:** **Parameters:**
@ -84,5 +84,5 @@ The operator takes an image as input. It first detects the objects appeared in t
**Return**: List[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.
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 confidence scores.

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