API to find a face using uploaded image

find-face.py

from flask import Flask, request, jsonify, make_response
from werkzeug.utils import secure_filename
import dlib
import cv2
import face_recognition
import os
import postgresql


app = Flask(__name__)
app.config['MAX_CONTENT_LENGTH'] = 10 * 1024 * 1024
app.config['UPLOAD_EXTENSIONS'] = ['.jpg', '.png', '.jpeg']
app.config['UPLOAD_PATH'] = 'uploads'


def process_face_matches(face_matches):
    results = []
    for face_match in face_matches:
        results.append({
            'id': face_match[0],
            'file': face_match[1],
            'image_id': face_match[2]
        })
    return results


def find_face_in_db(local_filename):
    # Create a HOG face detector using the built-in dlib class
    face_detector = dlib.get_frontal_face_detector()

    # Load the image
    image = cv2.imread(local_filename)

    # Run the HOG face detector on the image data
    detected_faces = face_detector(image, 1)

    print("Found {} faces in the image file {}".format(len(detected_faces), local_filename))

    db = postgresql.open(os.environ.get('DATABASE_STRING'))

    # Loop through each face we found in the image
    face_records = []
    for i, face_rect in enumerate(detected_faces):
        # Detected faces are returned as an object with the coordinates
        # of the top, left, right and bottom edges
        print("- Face #{} found at Left: {} Top: {} Right: {} Bottom: {}".format(i, face_rect.left(), face_rect.top(),
                                                                                 face_rect.right(), face_rect.bottom()))
        crop = image[face_rect.top():face_rect.bottom(), face_rect.left():face_rect.right()]

        encodings = face_recognition.face_encodings(crop)
        threshold = 0.6
        if len(encodings) > 0:
            query = "SELECT id, file, image_id FROM vectors WHERE sqrt(power(CUBE(array[{}]) <-> vec_low, 2) + power(CUBE(array[{}]) <-> vec_high, 2)) <= {} ".format(
                ','.join(str(s) for s in encodings[0][0:64]),
                ','.join(str(s) for s in encodings[0][64:128]),
                threshold,
            ) + \
                    "ORDER BY sqrt(power(CUBE(array[{}]) <-> vec_low, 2) + power(CUBE(array[{}]) <-> vec_high, 2)) ASC".format(
                        ','.join(str(s) for s in encodings[0][0:64]),
                        ','.join(str(s) for s in encodings[0][64:128]),
                    )
            face_record = db.query(query)
            face_records.append(process_face_matches(face_record))
    return face_records


@app.route('/faces/searches', methods=['POST'])
def faces_searches():
    uploaded_file = request.files['file']
    filename = secure_filename(uploaded_file.filename)
    if filename != '':
        file_ext = os.path.splitext(filename)[1]
        if file_ext in app.config['UPLOAD_EXTENSIONS']:  # and file_ext == validate_image(uploaded_file.stream):
            file_path = os.path.join(app.config['UPLOAD_PATH'], filename)
            uploaded_file.save(file_path)
            face_matches = find_face_in_db(file_path)
            os.remove(file_path)
            return make_response(jsonify(matches=face_matches), 200)
    return make_response(jsonify(error='Invalid file'), 400)


if __name__ == "__main__":
    app.run(debug=True, port=9000)