# Flask REST API
[REST](https://en.wikipedia.org/wiki/Representational_state_transfer) [API](https://en.wikipedia.org/wiki/API)s 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](https://pytorch.org/hub/ultralytics_yolov5/).
## Requirements
[Flask](https://palletsprojects.com/p/flask/) is required. Install with:
```shell
$ pip install Flask
```
## Run
After Flask installation run:
```shell
$ python3 restapi.py --port 5000
```
Then use [curl](https://curl.se/) to perform a request:
```shell
$ curl -X POST -F image=@zidane.jpg 'http://localhost:5000/v1/object-detection/yolov5s'`
```
The model inference results are returned as a JSON response:
```json
[
{
"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](https://docs.python-requests.org/en/master/) is given in `example_request.py`
labelimg制作VOC数据集并用yolov5训练目标检测模型 （611个子文件） 
train.cache 38KB val.cache 5KB Dockerfile 2KB Dockerfile 846B .dockerignore 4KB .gitattributes 77B .gitignore 4KB tutorial.ipynb 384KB LICENSE 35KB CONTRIBUTING.md 5KB README.md 2KB README.md 222B train.cache.npy 43KB datasets.py 42KB train.py 30KB general.py 30KB plots.py 18KB common.py 17KB val.py 17KB metrics.py 13KB yolo.py 13KB torch_utils.py 13KB detect.py 12KB augmentations.py 11KB loss.py 10KB export.py 8KB autoanchor.py 7KB downloads.py 6KB __init__.py 6KB hubconf.py 6KB experimental.py 5KB activations.py 4KB resize_img.py 3KB txt2yolo_label.py 2KB histogram_equalization_equalHist.py 2KB changname.py 1KB histogram_equalization2.py 1KB split.py 1KB resume.py 1KB restapi.py 1KB high_pass_filter_scharr.py 709B high_pass_filter_sobel.py 643B high_pass_filter_laplacian.py 471B yolotest.py 344B example_request.py 312B __init__.py 0B __init__.py 0B __init__.py 0B userdata.sh 1KB mime.sh 806B
train.txt 6KB trainval.txt 1KB train.txt 1KB requirements.txt 722B val.txt 638B 196.txt 131B val.txt 125B additional_requirements.txt 109B 244.txt 84B 13.txt 83B 234.txt 83B 202.txt 83B 247.txt 83B 186.txt 83B 258.txt 83B 218.txt 82B 92.txt 82B 194.txt 82B 159.txt 82B 160.txt 82B 124.txt 82B 51.txt 81B 114.txt 81B 105.txt 77B 168.txt 76B 129.txt 76B 145.txt 75B 140.txt 75B 19.txt 75B 235.txt 75B 138.txt 75B 32.txt 75B 180.txt 74B 57.txt 74B 59.txt 74B 118.txt 74B 73.txt 74B 117.txt 74B 120.txt 74B 227.txt 74B 95.txt 73B 217.txt 73B 221.txt 73B 216.txt 73B 78.txt 73B 248.txt 73B 233.txt 73B 267.txt 73B 34.txt 73B 208.txt 73B共 611 条
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