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Raymond231/
AI_Image_Classifier

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AI Image Classifier — Backend

FastAPI backend untuk demo AI-Assisted Dev Workflow.

Quick Start

bash

# 1. Install dependencies
pip install -r requirements.txt

# 2. (Opsional) Konfigurasi model kustom
cp .env.example .env
# Edit .env: set MODEL_PATH ke model YOLOv8 kamu

# 3. Jalankan server
uvicorn main:app --reload --port 8000

Server berjalan di http://localhost:8000
Swagger docs: http://localhost:8000/docs

Endpoints

Method	Path	Deskripsi
GET	/health	Cek status server + model
POST	/predict	Upload gambar → hasil prediksi
GET	/history	Ambil N prediksi terakhir
DELETE	/history	Hapus semua history

Kustomisasi Model

Ganti MODEL_PATH di .env dengan path ke model .pt kamu:

env

MODEL_PATH=runs/detect/train/weights/best.pt
MODEL_TASK=detect   # atau "classify"

Model YOLOv8n akan di-download otomatis (~6 MB) jika tidak ada model kustom.

Struktur File

backend/
├── main.py         ← FastAPI app + routing
├── predictor.py    ← Wrapper model inference
├── schemas.py      ← Pydantic request/response types
├── requirements.txt
└── .env.example

Raymond231/AI_Image_Classifier