import os
import time
import json
import tempfile
from datetime import datetime

import cv2
from deepface import DeepFace
from db import get_connection_from_env, ensure_table, save_embedding

CASCADE_PATH = "src/face.xml"
EMBED_DIR = "embeddings"


def ensure_dir(d):
    if not os.path.exists(d):
        os.makedirs(d, exist_ok=True)


def compute_and_save(crop_img, name, save_db=True):
    ensure_dir(EMBED_DIR)
    ts = int(time.time())
    tmp = os.path.join(tempfile.gettempdir(), f"{name}_{ts}_crop.jpg")
    # add padding and resize as in detect_and_enroll
    h, w = crop_img.shape[:2]
    pad = int(0.25 * max(w, h))
    padded = cv2.copyMakeBorder(crop_img, pad, pad, pad, pad, borderType=cv2.BORDER_CONSTANT, value=[0,0,0])
    resized = cv2.resize(padded, (224,224), interpolation=cv2.INTER_AREA)
    cv2.imwrite(tmp, resized)
    try:
        emb = DeepFace.represent(tmp, model_name='Facenet', enforce_detection=True)
    except Exception as e:
        print('First attempt failed:', e)
        try:
            emb = DeepFace.represent(tmp, model_name='Facenet', enforce_detection=False, detector_backend='opencv')
        except Exception as e2:
            print('Second attempt failed:', e2)
            return False
    # normalize embedding to list
    if isinstance(emb, dict) and 'embedding' in emb:
        vec = emb['embedding']
    elif isinstance(emb, list) and len(emb) > 0 and isinstance(emb[0], dict) and 'embedding' in emb[0]:
        vec = emb[0]['embedding']
    else:
        vec = list(emb)
    out_json = os.path.join(EMBED_DIR, f"{name}.json")
    meta = {"name":name, "timestamp":datetime.utcnow().isoformat()+"Z", "embedding":vec}
    with open(out_json, 'w') as f:
        json.dump(meta, f)
    out_img = os.path.join(EMBED_DIR, f"{name}.jpg")
    cv2.imwrite(out_img, resized)
    print('Saved embedding and crop for', name)
    if save_db:
        try:
            conn = get_connection_from_env()
            ensure_table(conn)
            save_embedding(conn, name, json.dumps(vec))
            conn.close()
            print('Saved embedding to database for', name)
        except Exception as e:
            print('DB save failed:', e)
    try:
        os.remove(tmp)
    except Exception:
        pass
    return True


def main(camera_id=0):
    cap = cv2.VideoCapture(camera_id)
    if not cap.isOpened():
        print('Cannot open camera')
        return
    face_cascade = cv2.CascadeClassifier(CASCADE_PATH)
    print("Press 'c' to capture current detected face and enroll; 'q' to quit")
    while True:
        ret, frame = cap.read()
        if not ret:
            print('Failed to read frame')
            break
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(60,60))
        for (x,y,w,h) in faces:
            cv2.rectangle(frame, (x,y), (x+w, y+h), (0,255,0), 2)
        cv2.imshow('Manual Detect & Enroll', frame)
        key = cv2.waitKey(1) & 0xFF
        if key == ord('q'):
            break
        if key == ord('c'):
            if len(faces)==0:
                print('No faces detected to capture')
                continue
            x,y,w,h = faces[0]
            crop = frame[y:y+h, x:x+w]
            name = input('Enter name for enrollment: ').strip()
            if name == '':
                print('Empty name, skipping')
            else:
                compute_and_save(crop, name)
    cap.release()
    cv2.destroyAllWindows()

if __name__ == '__main__':
    main()