app.py

from flask import Flask, request, jsonify
import cv2
import numpy as np
from huggingface_hub import hf_hub_download
import os

app = Flask(__name__)

# Auto-download YuNet model from official HF repo (only once, cached after)
model_filename = "face_detection_yunet_2023mar.onnx"
model_path = hf_hub_download(
    repo_id="opencv/face_detection_yunet",
    filename=model_filename
)

# Initialize YuNet detector
face_detector = cv2.FaceDetectorYN_create(
    model_path,
    "",
    (320, 320),   # input size
    0.87,         # score threshold (adjust if too strict/loose)
    0.3,          # NMS threshold
    5000          # top K
)

@app.route('/', methods=['GET'])
def home():
    return jsonify({
        "status": "API is running",
        "usage": "POST a JPEG image to /detect with form-data key 'image'",
        "response": "Returns {'has_face': true/false, 'count': number}"
    })

@app.route('/detect', methods=['POST'])
def detect():
    if 'image' not in request.files:
        return jsonify({"error": "No 'image' file in request"}), 400

    file = request.files['image']
    if file.filename == '':
        return jsonify({"error": "No selected file"}), 400

    filestr = file.read()
    npimg = np.frombuffer(filestr, np.uint8)
    img = cv2.imdecode(npimg, cv2.IMREAD_COLOR)

    if img is None:
        return jsonify({"error": "Invalid or corrupted image"}), 400

    # Set input size to match the uploaded image
    height, width = img.shape[:2]
    face_detector.setInputSize((width, height))

    # Run detection
    _, faces = face_detector.detect(img)

    has_face = faces is not None and len(faces) > 0

    result = {
        "has_face": has_face,
        "count": len(faces) if faces is not None else 0,
        "message": "Face detected" if has_face else "No face detected"
    }

    return jsonify(result)

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=7860, debug=True)