72 lines
1.6 KiB
Markdown
72 lines
1.6 KiB
Markdown
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# SMAN 1 Garut – Face Embedding Service
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Layanan Python kecil untuk menghasilkan **embedding wajah** + metrik kualitas yang dipakai backend CI4 (`FaceService`).
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## Fitur
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- Framework: **FastAPI** + **InsightFace**.
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- Endpoint utama: `POST /embed` (single image → embedding + quality).
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- Deteksi wajah, pilih wajah terbesar, hitung:
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- `embedding` (vector float, default dimensi 512),
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- `faces_count`,
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- `face_size` (px),
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- `blur` (variance of Laplacian),
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- `brightness` (0..1),
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- `quality_score` (kombinasi sederhana dari metrik di atas).
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## Setup Cepat
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```bash
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cd face-service
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python -m venv .venv
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source .venv/bin/activate # Windows: .venv\Scripts\activate
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pip install -r requirements.txt
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uvicorn main:app --host 0.0.0.0 --port 5000
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```
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Lalu di `.env` backend CI4 (`backend/.env`), set:
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```ini
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FACE_SERVICE_URL = 'http://localhost:5000'
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FACE_EMBEDDING_DIM = 512
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FACE_SIM_THRESHOLD = 0.85
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FACE_MIN_SIZE = 80
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FACE_MIN_BLUR = 30
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FACE_MIN_BRIGHTNESS = 0.2
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```
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## Kontrak API: `POST /embed`
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**Request** (multipart/form-data):
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- Field `image`: file gambar (.jpg/.png).
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**Response** (`200 OK`, JSON):
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```json
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{
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"embedding": [0.01, -0.23, ...],
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"quality_score": 0.93,
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"faces_count": 1,
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"face_size": 120.5,
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"blur": 45.2,
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"brightness": 0.55
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}
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```
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Backend CI4 (`FaceService::extractEmbeddingWithQuality`) akan:
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- Menolak gambar dengan:
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- `faces_count != 1`,
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- `face_size < FACE_MIN_SIZE`,
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- `blur < FACE_MIN_BLUR`,
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- `brightness < FACE_MIN_BRIGHTNESS`.
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## Health Check
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`GET /health` → `{"status": "ok", "model": "buffalo_l"}`
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Dipakai untuk cek cepat apakah service sudah siap dipakai backend CI4.
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