https://github.com/clementsan/object_detection_detr_api
AI-driven object detection via FastAPI
https://github.com/clementsan/object_detection_detr_api
ai api deep-learning fastapi object-detection object-detection-api
Last synced: about 1 month ago
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AI-driven object detection via FastAPI
- Host: GitHub
- URL: https://github.com/clementsan/object_detection_detr_api
- Owner: clementsan
- Created: 2024-11-16T00:19:34.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-01-17T00:06:30.000Z (4 months ago)
- Last Synced: 2025-02-04T13:03:31.267Z (3 months ago)
- Topics: ai, api, deep-learning, fastapi, object-detection, object-detection-api
- Language: Python
- Homepage:
- Size: 63.5 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Object detection via FastAPI
[](https://www.python.org/downloads/)
[](https://hub.docker.com/repository/docker/cvachet/object-detection-detr-api)
**Aim:** AI-driven object detection via FastAPI (on COCO image dataset)
**Machine learning models:**
- facebook/detr-resnet-50
- facebook/detr-resnet-101
------
### Table of contents:
- [Direct execution](#1-direct-execution)
- [Run FastAPI interface](#11-run-fastapi-interface)
- [Run API query via curl command](#12-run-api-query-via-curl-command)
- [Run API query via python script](#13-run-api-query-via-python-script)
- [Tests via pytest library](#14-tests-via-pytest-library)
- [Execution via docker container](#2-execution-via-docker-container)
- [Build image and run docker container](#21-build-image-and-run-docker-container)
- [Run query via API](#22-run-query-via-api)
- [Deployment on Docker hub](#3-deployment-on-docker-hub)
- [MLOps pipeline via GitHub actions](#4-mlops-pipeline-via-github-actions)
----
## 1. Direct execution
### 1.1. Run FastAPI interface
Command line in development mode:
> fastapi dev app/main.py
Manual command line in production:
> fastapi run app/main.py
Notes:
- Serving at: http://127.0.0.1:8000
- API docs: http://127.0.0.1:8000/docs
### 1.2. Run API query via curl command
Command lines:
- Endpoint "/":
> curl -X 'GET' -H 'accept: application/json' 'http://127.0.0.1:8000/'
- Endpoint "/info":
> curl -X 'GET' -H 'accept: application/json' 'http://127.0.0.1:8000/info'
- Endpoint "/api/v1/detect":
> curl -X POST -F "image=@./tests/data/savanna.jpg" http://127.0.0.1:8000/api/v1/detect
- Endpoint "/api/v1/detect" with optional model type (e.g. detr-resnet-50 or detr-resnet-101):
> curl -X POST -F "image=@./tests/data/savanna.jpg" http://127.0.0.1:8000/api/v1/detect?model=detr-resnet-50
### 1.3. Run API query via python script
Command line:
> python app/inference_api.py -u "http://127.0.0.1:8000/api/v1/detect" -f tests/data/savanna.jpg
### 1.4. Tests via pytest library
Command lines:
> pytest tests/ -v
> pytest tests/ -s -o log_cli=true -o log_level=DEBUG
## 2. Execution via docker container
### 2.1. Build image and run docker container
Command lines:
> sudo docker build -t object-detection-detr-api .
> sudo docker run --name object-detection-detr-api-cont -p 8000:8000 object-detection-detr-api
### 2.2. Run query via API
Command lines:
- Endpoint "/":
> curl -X 'GET' 'http://0.0.0.0:8000/' -H 'accept: application/json'
- Endpoint "/info":
> curl -X 'GET' -H 'accept: application/json' 'http://0.0.0.0:8000/info'
- Endpoint "/api/v1/detect":
> curl -X 'POST' -F "image=@./tests/data/savanna.jpg" http://0.0.0.0:8000/api/v1/detect
- Endpoint "/api/v1/detect" with optional model type (e.g. detr-resnet-50 or detr-resnet-101):
> curl -X POST -F "image=@./tests/data/savanna.jpg" http://0.0.0.0:8000/api/v1/detect?model=detr-resnet-50
## 3. Deployment on Docker hub
This FastAPI application is available as a Docker container on Docker hub
URL: https://hub.docker.com/r/cvachet/object-detection-detr-api
## 4. MLOps pipeline via GitHub actions
Github actions were created to enable Continuous Integration (CI) and Continuous Deployment (CD) for this FastAPI app.
YAML files:
- Python testing suite: [ci_python.yml](.github/workflows/ci_python.yml)
- Pushing to docker: [publish_docker_image.yaml](.github/workflows/publish_docker_image.yaml)