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Michel Promonet 4d05472d2b | 1 year ago | |
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README.md | 2 years ago | |
example_request.py | 2 years ago | |
restapi.py | 1 year ago |
REST APIs are
commonly used to expose Machine Learning (ML) models to other services. This folder contains an example REST API
created using Flask to expose the YOLOv5s model from PyTorch Hub.
Flask is required. Install with:
$ pip install Flask
After Flask installation run:
$ python3 restapi.py --port 5000
Then use curl to perform a request:
$ curl -X POST -F image=@zidane.jpg 'http://localhost:5000/v1/object-detection/yolov5s'
The model inference results are returned as a JSON response:
[
{
"class": 0,
"confidence": 0.8900438547,
"height": 0.9318675399,
"name": "person",
"width": 0.3264600933,
"xcenter": 0.7438579798,
"ycenter": 0.5207948685
},
{
"class": 0,
"confidence": 0.8440024257,
"height": 0.7155083418,
"name": "person",
"width": 0.6546785235,
"xcenter": 0.427829951,
"ycenter": 0.6334488392
},
{
"class": 27,
"confidence": 0.3771208823,
"height": 0.3902671337,
"name": "tie",
"width": 0.0696444362,
"xcenter": 0.3675483763,
"ycenter": 0.7991207838
},
{
"class": 27,
"confidence": 0.3527112305,
"height": 0.1540903747,
"name": "tie",
"width": 0.0336618312,
"xcenter": 0.7814827561,
"ycenter": 0.5065554976
}
]
An example python script to perform inference using requests is given
in example_request.py
利用yolov5实现安全帽检测
Python Jupyter Notebook Markdown Shell Dockerfile other
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