119 lines
4.1 KiB
Python
119 lines
4.1 KiB
Python
from flask import Flask, request, jsonify
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from minio import Minio
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from minio.error import (ResponseError, BucketAlreadyOwnedByYou, BucketAlreadyExists)
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import os
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import uuid
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import pickle
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import face_recognition
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from werkzeug.datastructures import ImmutableMultiDict
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import base64
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import cv2
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import numpy as np
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import imutils
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app = Flask(__name__)
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minioClient = Minio('minio:9000', access_key=os.environ['s3-name'], secret_key=os.environ['s3-password'], secure=False)
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@app.route('/')
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def hello_docker():
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return 'Hello, I run in a docker container'
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@app.route('/acces_minio')
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def access_minio():
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for bucket in minioClient.list_buckets():
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print(bucket.name, bucket.creation_date, flush=True)
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return 'Connection Succesfull'
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@app.route('/new_user_id')
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def new_user_id():
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#save demo object to reserve id in minio
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id = None
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for limited_try in range(0,5):
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id = str(uuid.uuid4())
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if check_id(id) == False:
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break
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demo_object = ['test']
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with open('/tmp/demo_object.pkl', 'wb') as f:
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pickle.dump(demo_object, f)
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minioClient.fput_object('users', str(id), '/tmp/demo_object.pkl')
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return jsonify({'id':id})
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@app.route('/init_face')
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#call like https://face.sguba.de/init_face?id=123&encoded_string=abc
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def new_face():
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id = request.args.get('id', None)
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img = request.args.get('encoded_string', None)
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temporary_img_path = '/tmp/'+str(id)+'.jpg'
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temporary_pkl_path = '/tmp/'+str(id)+'.pkl'
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save_img(img, temporary_img_path)
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face_encoding_response = encode_face(temporary_img_path)
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if face_encoding_response['success']==True:
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with open(temporary_pkl_path, 'wb') as file:
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pickle.dump(face_encoding_response['encoding'], file)
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minioClient.fput_object('users', str(id), temporary_pkl_path)
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return jsonify({'success':face_encoding_response['success']})
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@app.route('/check_face')
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#call like https://face.sguba.de/check_face?id=123&encoded_string=abc
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def check_face():
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id = request.args.get('id', None)
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img = request.args.get('encoded_string', None)
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temporary_img_path = '/tmp/'+str(id)+'.jpg'
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temporary_pkl_path = '/tmp/'+str(id)+'.pkl'
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save_img(img, temporary_img_path)
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face_encoding_response = encode_face(temporary_img_path)
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if face_encoding_response['success']==True:
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minioClient.fget_object('users', str(id), temporary_pkl_path)
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with open(temporary_pkl_path, 'rb') as file:
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face_encoding = pickle.load(file)
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face_encoding_response['result'] = str(face_recognition.compare_faces([face_encoding], face_encoding_response['encoding'])[0])
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else:
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face_encoding_response['result'] = str(False)
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return jsonify({'result':face_encoding_response['result'],'success':face_encoding_response['success']})
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def check_id(id):
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#return True -> id bereits verwendet
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#return False -> id noch nicht verwendet
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users = minioClient.list_objects('users')
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known = False
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for user in users:
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if id == user.object_name:
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known = True
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else:
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pass
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return known
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def save_img(encoded_data, filename):
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encoded_data += "=" * ((4 - len(encoded_data) % 4) % 4)
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encoded_data = bytes(encoded_data, encoding='utf-8')
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nparr = np.fromstring(base64.urlsafe_b64decode(encoded_data), np.uint8)
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img = cv2.imdecode(nparr, cv2.IMREAD_ANYCOLOR)
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img = imutils.rotate(img, 90)
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return cv2.imwrite(filename, img)
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def encode_face(path):
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success = None
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face = face_recognition.load_image_file(path)
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face_encoding = face_recognition.face_encodings(face)
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if len(face_encoding)==0:
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success = False
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response = {'success':success, 'encoding':None}
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else:
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success = True
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response = {'success':success, 'encoding':face_encoding[0]}
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return response
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def setup():
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try:
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minioClient.make_bucket("users")
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except BucketAlreadyOwnedByYou as err:
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pass
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except BucketAlreadyExists as err:
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pass
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except ResponseError as err:
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raise
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if __name__ == '__main__':
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setup()
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app.run(host='0.0.0.0') |