# 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`
人工智能-项目实践-计算机视觉-yolov5目标检测模型的知识蒸馏（基于响应的蒸馏）.zip （52个子文件） 
yolov5-knowledge-distillation-main 
export.py 8KB hubconf.py 6KB utils __init__.py 0B google_utils.py 6KB loss.py 19KB loggers __init__.py 6KB augmentations.py 11KB flask_rest_api example_request.py 299B restapi.py 1KB README.md 2KB metrics.py 13KB aws __init__.py 0B userdata.sh 1KB mime.sh 780B resume.py 1KB autoanchor.py 7KB general.py 28KB activations.py 4KB google_app_engine Dockerfile 821B app.yaml 173B
additional_requirements.txt 105B plots.py 18KB datasets.py 39KB torch_utils.py 12KB convert.py 3KB val.py 16KB requirements.txt 703B models hub yolov5x6.yaml 2KB anchors.yaml 3KB yolov5-p2.yaml 2KB yolov5-panet.yaml 2KB yolov5s6.yaml 2KB yolov3.yaml 2KB yolov5-p6.yaml 2KB yolov5-p7.yaml 2KB yolov5l6.yaml 2KB yolov5m6.yaml 2KB yolov3-spp.yaml 2KB yolov3-tiny.yaml 1KB yolov5-fpn.yaml 1KB yolov5s-transformer.yaml 2KB __init__.py 0B yolov5m.yaml 1KB yolov5s.yaml 1KB yolov5l.yaml 1KB common.py 16KB experimental.py 5KB yolov5x.yaml 1KB yolo.py 13KB detect.py 12KB train.py 30KB distill.py 31KB资源评论
