This project enables image object detection using a YOLOv8 model hosted on AWS SageMaker, accessible via a REST API powered by Lambda and API Gateway. Users can send images via a REST API endpoint and receive annotated images with detected bounding boxes.
All setup instructions, deployment details, and troubleshooting steps are
organized in the docs/ folder.
| 📄 Document | Description | 
|---|---|
| 1-overview.md | System architecture and high-level project overview | 
| 2-sagemaker-setup.md | Setup SageMaker model, inference script, and deployment | 
| 3-lambda-function.md | Lambda function logic, permissions, and deployment | 
| 4-api-gateway.md | API Gateway configuration, routes, and URL structure | 
| 5-local-testing.md | Test from local PC using curlor Pythonrequests | 
| 6-troubleshooting.md | Fix common issues, error codes, and log locations | 
| 7-references.md | Useful external links and AWS documentation | 
mim download mmyolo \
  --config yolov8_x_mask-refine_syncbn_fast_8xb16-500e_coco \
  --dest models/yolov8_x_mask-refine_syncbn_fast_8xb16-500e_cococonda create -n mmyolo python=3.8
conda activate mmyolo
pip install -r src/requirements.txt
pip install -r scripts/requirements.txtAWS_PROFILE=your-profile python scripts/deploy.pypython src/test_yolo_locally.py # Should show a window with detection