🦄 FastAPI Inference Server

A blazing-fast inference server for computer vision tasks using FastAPI, YOLO, DINOv2, and FAISS! 🚀

Features

• YOLOv8 Segmentation: Detect and segment objects in images
• DINOv2 Embeddings: Extract powerful image features
• FAISS Vector Search: Find similar items using vector search
• Easy REST API: Simple endpoints for integration with any frontend

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🛠️ Setup

1. Clone the repository

git clone <your-repo-url>
cd <your-project-directory>

2. Install dependencies

pip install -r requirements.txt

3. Download/Place Model Files

• Place your YOLO model at models/deepfashion2_yolov8s-seg.pt
• Place your FAISS index and metadata at index/jersey_index.faiss and index/jersey_metadata.npy

4. Start the server

uvicorn inference_server:app --host 0.0.0.0 --port 8000 --reload

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🔥 API Endpoints

POST /yolo

• Description: Run YOLOv8 segmentation on an image
• Request: Multipart/form-data with an image file
• Response: JSON with detected polygons

POST /dino

• Description: Extract DINOv2 features from an image
• Request: Multipart/form-data with an image file
• Response: JSON with feature vector

POST /faiss

• Description: Search for similar items using FAISS
• Request: JSON with features (list of floats)
• Response: JSON with ranked search results

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🧑‍💻 Example Usage

YOLO Inference (Python)

import requests

with open('your_image.jpg', 'rb') as f:
    response = requests.post('http://localhost:8000/yolo', files={'file': f})
print(response.json())

DINOv2 Inference (Python)

import requests

with open('your_image.jpg', 'rb') as f:
    response = requests.post('http://localhost:8000/dino', files={'file': f})
print(response.json())

FAISS Search (Python)

import requests
features = [0.1, 0.2, ...]  # Replace with your feature vector
response = requests.post('http://localhost:8000/faiss', json={'features': features})
print(response.json())

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🌐 CORS

If using a frontend on a different port, make sure to enable CORS in inference_server.py:

from fastapi.middleware.cors import CORSMiddleware
app.add_middleware(
    CORSMiddleware,
    allow_origins=["https://localhost:8081"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

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📂 Project Structure

├── inference_server.py      # FastAPI app and endpoints
├── requirements.txt         # Python dependencies
├── models/
│   └── deepfashion2_yolov8s-seg.pt
├── index/
│   ├── jersey_index.faiss
│   └── jersey_metadata.npy

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📝 License

MIT License