import os, time, face_recognition, numpy as np from flask import Flask, request from PIL import Image from io import BytesIO from utils import rotate_image, response_formatter, allowed_file, face_eval, face_eval_regis from translations import trans # import uuid # from werkzeug.utils import secure_filename dirname = os.getcwd() attendance_folder = os.path.join(dirname, 'users', 'attendance') if not os.path.exists(attendance_folder): os.makedirs(attendance_folder) app = Flask(__name__) app.config['UPLOAD_FOLDER'] = attendance_folder @app.route("/") def helloWorld(): return "hello world" @app.route('/compare_faces', methods=['POST']) def match_attendance(): try: lang = request.headers.get('Accept-Language', 'en') if 'image_1' not in request.files or 'image_2' not in request.files: message = trans[lang]['req_file_name'] return response_formatter(message, 'failed') req_image_1 = request.files['image_1'] req_image_2 = request.files['image_2'] if not (allowed_file(req_image_1.filename) and allowed_file(req_image_2.filename)): message = trans[lang]['allowed_extension'] return response_formatter(message, 'failed') # # detect spoofing # result = detect(app.config['UPLOAD_FOLDER'], req_image_2) # if(result): # return response_formatter('Verifikasi gagal, pastikan mengambil foto di tempat yang cukup cahaya', 'failed') # load image image_1 = face_recognition.load_image_file(req_image_1) image_2 = face_recognition.load_image_file(req_image_2) # deteksi wajah face_locations_1 = face_recognition.face_locations(image_1) face_locations_2 = face_recognition.face_locations(image_2) # Rotate images if faces are not detected if not face_locations_1: image_1 = rotate_image(req_image_1) face_locations_1 = face_recognition.face_locations(image_1) if not face_locations_1: message = trans[lang]['face_1_not_found'] return response_formatter(message, 'failed') if not face_locations_2: image_2 = rotate_image(req_image_2) face_locations_2 = face_recognition.face_locations(image_2) if not face_locations_2: message = trans[lang]['face_2_not_found'] return response_formatter(message, 'failed') # evaluasi attendance image if len(face_locations_2) == 1: eval_attendance = face_eval(image_2, face_locations_2, min_wide_face_area=15000, laplacian_thresold=85, lang=lang) # print(eval_attendance) if eval_attendance['result'] == False: return response_formatter(eval_attendance['message'], eval_attendance['status']) elif len(face_locations_2) > 1: return response_formatter(trans[lang]['only_one_face'], 'failed', False) # encoding image agar bisa di lakukan komparasi image_1_encodings = face_recognition.face_encodings(image_1, model='large')[0] image_2_encodings = face_recognition.face_encodings(image_2, model='large')[0] # compare image match_result = face_recognition.compare_faces([image_1_encodings], image_2_encodings, tolerance=0.5) # Check and create folder if not exists folder_path = os.path.join(app.config['UPLOAD_FOLDER'], req_image_2.filename.split('.')[0]) if not os.path.exists(folder_path): os.makedirs(folder_path) existing_files = [f for f in os.listdir(folder_path) if f.endswith('.jpg')] if match_result[0]: # save attendance foto to users/attendance folder, max 5 file if len(existing_files) < 5: path = os.path.join(folder_path, time.strftime("%Y%m%d_%H%M%S") + '.jpg') req_image_2.seek(0) req_image_2.save(path) status = 'success' message = trans[lang]['face_match'] else: status = 'failed' message = trans[lang]['face_not_match'] if len(existing_files) > 0: for f in existing_files: # print(f) image_1 = face_recognition.load_image_file(os.path.join(folder_path, f)) image_1_encodings = face_recognition.face_encodings(image_1, model='large')[0] match_result = face_recognition.compare_faces([image_1_encodings], image_2_encodings, tolerance=0.5) if match_result[0]: status = 'success' message = trans[lang]['face_match'] break return response_formatter(message, status, bool(match_result[0])) except Exception as e: return response_formatter(str(e), 'failed') @app.route('/find_faces', methods=['POST']) def find_faces(): try: lang = request.form.get('lang', 'en') req_image = request.files['image'] ############### testing save gambar ################## # unique_filename = 'reg_' + str(uuid.uuid4()) + '_' + secure_filename(req_image.filename) # path = os.path.join(attendance_folder, unique_filename) # req_image.save(path) ################################# loadedImage = face_recognition.load_image_file(req_image) faces = face_recognition.face_locations(loadedImage) # faces akan berisi list lokasi wajah if not faces: # coba rotasi jika tidak ada wajah req_image.seek(0) # Pindahkan kursor ke awal byte file_bytes = BytesIO(req_image.read()) image = Image.open(file_bytes).rotate(90) image.convert('RGB') # faces = face_recognition.load_image_file(file_bytes) # jangan di load lagi dengan face_recog karena sudah di open dengan Pill.Image faces = face_recognition.face_locations(np.array(image)) if len(faces) == 1: #hanya satu wajah yang di ijinkan data = face_eval_regis(loadedImage, faces, min_wide_face_area=15000, laplacian_thresold=85) return response_formatter(data['message'], data['status'], data['result']) elif len(faces) > 1 : return response_formatter(trans[lang]['only_one_face'], 'failed') else: return response_formatter(trans[lang]['face_not_found'], 'failed') except Exception as e: return response_formatter(str(e), 'failed') @app.route('/testing', methods=['POST']) def testing(): if 'image_1' not in request.files or 'image_2' not in request.files: message = 'request file must have name image_1 and image_2' return response_formatter(message, 'failed') req_image_1 = request.files['image_1'] req_image_2 = request.files['image_2'] if not (allowed_file(req_image_1.filename) and allowed_file(req_image_2.filename)): message = 'Hanya ekstensi berikut yang diperbolehkan: jpg, jpeg, png, webp' return response_formatter(message, 'failed') # load image image_1 = face_recognition.load_image_file(req_image_1) image_2 = face_recognition.load_image_file(req_image_2) # deteksi wajah face_locations_1 = face_recognition.face_locations(image_1) face_locations_2 = face_recognition.face_locations(image_2) if not face_locations_1: message = 'Faces not detected in the source image.' return response_formatter(message, 'failed') if not face_locations_2: message = 'Faces not detected in the requested image.' return response_formatter(message, 'failed') # encoding image agar bisa di lakukan komparasi image_1_encodings = face_recognition.face_encodings(image_1, model='large')[0] image_2_encodings = face_recognition.face_encodings(image_2, model='large')[0] # compare image match_result = face_recognition.compare_faces([image_1_encodings], image_2_encodings, tolerance=0.39) print(match_result) if match_result[0]: status = 'success' message = 'Facial recognition is match.' else: status = 'failed' message = 'Facial recognition does not match.' return response_formatter(message, status, bool(match_result[0]))