app.py

import sys
sys.path.append('.')

import os
import numpy as np
import base64
import io

from PIL import Image
from flask import Flask, request, jsonify
from facesdk import getMachineCode
from facesdk import setActivation
from facesdk import faceDetection
from facesdk import initSDK
from face_util import FaceBox

livenessThreshold = 0.7
yawThreshold = 10
pitchThreshold = 10
rollThreshold = 10
occlusionThreshold = 0.9
eyeClosureThreshold = 0.8
mouthOpeningThreshold = 0.5
borderRate = 0.05
smallFaceThreshold = 100
lowQualityThreshold = 0.3
hightQualityThreshold = 0.7
luminanceDarkThreshold = 50
luminanceLightThreshold = 200

maxFaceCount = 10

app = Flask(__name__)

is_activated = False

if os.path.exists("license.txt"):

    with open("license.txt", 'r') as file:
        license = file.read()
    
    ret = setActivation(license.encode('utf-8'))
    ret = initSDK("data".encode('utf-8'))

    is_activated = True


@app.route('/get-machine-code', methods=['GET'])
def get_machine_code():
    machine_code = getMachineCode()

    response = jsonify({"machineCode": machine_code.decode("utf-8")})

    response.status_code = 200
    response.headers["Content-Type"] = "application/json; charset=utf-8"
    return response


@app.route('/activate-machine', methods=['POST'])
def activate_machine():
    content = request.get_json()
    license = content['license']

    ret = setActivation(license.encode('utf-8'))
    activate_state = ret
    print("activation: ", ret)
    if ret == 0:
        with open("license.txt", 'w') as file:
            file.write(license)

    ret = initSDK("data".encode('utf-8'))
    init_state = ret
    print("init: ", ret)

    response = jsonify({"activationStatus": activate_state}, {'initStatus': init_state})

    response.status_code = 200
    response.headers["Content-Type"] = "application/json; charset=utf-8"
    return response


@app.route('/liveness-detection', methods=['POST'])
def check_liveness():
    faces = []
    isNotFront = None
    isOcclusion = None
    isEyeClosure = None
    isMouthOpening = None
    isBoundary = None
    isSmall = None
    quality = None
    luminance = None
    livenessScore = None

    file = request.files['file']

    try:
        image = Image.open(file)
    except:
        result = "Failed to open file"
        faceState = {"is_not_front": isNotFront, "is_occluded": isOcclusion, "eye_closed": isEyeClosure, "mouth_opened": isMouthOpening, 
                        "is_boundary_face": isBoundary, "is_small": isSmall, "quality": quality, "luminance": luminance, "result": result, "liveness_score": livenessScore}
        response = jsonify({"face_state": faceState, "faces": faces})

        response.status_code = 200
        response.headers["Content-Type"] = "application/json; charset=utf-8"
        return response


    image_np = np.asarray(image)

    faceBoxes = (FaceBox * maxFaceCount)()
    faceCount = faceDetection(image_np, image_np.shape[1], image_np.shape[0], faceBoxes, maxFaceCount)

    for i in range(faceCount):
        landmark_68 = []
        for j in range(68):
            landmark_68.append({"x": faceBoxes[i].landmark_68[j * 2], "y": faceBoxes[i].landmark_68[j * 2 + 1]})
        faces.append({"x1": faceBoxes[i].x1, "y1": faceBoxes[i].y1, "x2": faceBoxes[i].x2, "y2": faceBoxes[i].y2, 
                      "liveness": faceBoxes[i].liveness, 
                      "yaw": faceBoxes[i].yaw, "roll": faceBoxes[i].roll, "pitch": faceBoxes[i].pitch,
                      "face_quality": faceBoxes[i].face_quality, "face_luminance": faceBoxes[i].face_luminance, "eye_dist": faceBoxes[i].eye_dist,
                      "left_eye_closed": faceBoxes[i].left_eye_closed, "right_eye_closed": faceBoxes[i].right_eye_closed,
                      "face_occlusion": faceBoxes[i].face_occlusion, "mouth_opened": faceBoxes[i].mouth_opened,
                      "landmark_68": landmark_68})
    
    result = ""
    if faceCount == 0:
        result = "No face"
    elif faceCount > 1:
        result = "Multiple face"
    else:
        livenessScore = faceBoxes[0].liveness
        if livenessScore > livenessThreshold:
            result = "Real"
        else:
            result = "Spoof"
        
        isNotFront = True
        isOcclusion = False
        isEyeClosure = False
        isMouthOpening = False
        isBoundary = False
        isSmall = False
        quality = "Low"
        luminance = "Dark"
        if abs(faceBoxes[0].yaw) < yawThreshold and abs(faceBoxes[0].roll) < rollThreshold and abs(faceBoxes[0].pitch) < pitchThreshold:
            isNotFront = False
        
        if faceBoxes[0].face_occlusion > occlusionThreshold:
            isOcclusion = True

        if faceBoxes[0].left_eye_closed > eyeClosureThreshold or faceBoxes[0].right_eye_closed > eyeClosureThreshold:
            isEyeClosure = True

        if faceBoxes[0].mouth_opened > mouthOpeningThreshold:
            isMouthOpening = True
        
        if (faceBoxes[0].x1 < image_np.shape[1] * borderRate or 
            faceBoxes[0].y1 < image_np.shape[0] * borderRate or 
                faceBoxes[0].x1 > image_np.shape[1] - image_np.shape[1] * borderRate or 
                faceBoxes[0].x1 > image_np.shape[0] - image_np.shape[0] * borderRate):
            isBoundary = True

        if faceBoxes[0].eye_dist < smallFaceThreshold:
            isSmall = True
        
        if faceBoxes[0].face_quality < lowQualityThreshold:
            quality = "Low"
        elif faceBoxes[0].face_quality < hightQualityThreshold:
            quality = "Medium"
        else:
            quality = "High"
        
        if faceBoxes[0].face_luminance < luminanceDarkThreshold:
            luminance = "Dark"
        elif faceBoxes[0].face_luminance < luminanceLightThreshold:
            luminance = "Normal"
        else:
            luminance = "Light"

    faceState = {"is_not_front": isNotFront, "is_occluded": isOcclusion, "eye_closed": isEyeClosure, "mouth_opened": isMouthOpening, 
                    "is_boundary_face": isBoundary, "is_small": isSmall, "quality": quality, "luminance": luminance, "result": result, "liveness_score": livenessScore}
    response = jsonify({"face_state": faceState, "faces": faces})

    response.status_code = 200
    response.headers["Content-Type"] = "application/json; charset=utf-8"
    return response


@app.route('/liveness-detection-base64', methods=['POST'])
def check_liveness_base64():
    faces = []
    isNotFront = None
    isOcclusion = None
    isEyeClosure = None
    isMouthOpening = None
    isBoundary = None
    isSmall = None
    quality = None
    luminance = None
    livenessScore = None

    content = request.get_json()

    try:
        imageBase64 = content['base64']
        image_data = base64.b64decode(imageBase64)
        image = Image.open(io.BytesIO(image_data))
    except:
        result = "Failed to open file"
        faceState = {"is_not_front": isNotFront, "is_occluded": isOcclusion, "eye_closed": isEyeClosure, "mouth_opened": isMouthOpening, 
                        "is_boundary_face": isBoundary, "is_small": isSmall, "quality": quality, "luminance": luminance, "result": result, "liveness_score": livenessScore}
        response = jsonify({"face_state": faceState, "faces": faces})

        response.status_code = 200
        response.headers["Content-Type"] = "application/json; charset=utf-8"
        return response


    image_np = np.asarray(image)

    faceBoxes = (FaceBox * maxFaceCount)()
    faceCount = faceDetection(image_np, image_np.shape[1], image_np.shape[0], faceBoxes, maxFaceCount)

    for i in range(faceCount):
        landmark_68 = []
        for j in range(68):
            landmark_68.append({"x": faceBoxes[i].landmark_68[j * 2], "y": faceBoxes[i].landmark_68[j * 2 + 1]})
        faces.append({"x1": faceBoxes[i].x1, "y1": faceBoxes[i].y1, "x2": faceBoxes[i].x2, "y2": faceBoxes[i].y2, 
                      "liveness": faceBoxes[i].liveness, 
                      "yaw": faceBoxes[i].yaw, "roll": faceBoxes[i].roll, "pitch": faceBoxes[i].pitch,
                      "face_quality": faceBoxes[i].face_quality, "face_luminance": faceBoxes[i].face_luminance, "eye_dist": faceBoxes[i].eye_dist,
                      "left_eye_closed": faceBoxes[i].left_eye_closed, "right_eye_closed": faceBoxes[i].right_eye_closed,
                      "face_occlusion": faceBoxes[i].face_occlusion, "mouth_opened": faceBoxes[i].mouth_opened,
                      "landmark_68": landmark_68})

    result = ""
    if faceCount == 0:
        result = "No face"
    elif faceCount > 1:
        result = "Multiple face"
    else:
        livenessScore = faceBoxes[0].liveness
        if livenessScore > livenessThreshold:
            result = "Real"
        else:
            result = "Spoof"
        
        isNotFront = True
        isOcclusion = False
        isEyeClosure = False
        isMouthOpening = False
        isBoundary = False
        isSmall = False
        quality = "Low"
        luminance = "Dark"
        if abs(faceBoxes[0].yaw) < yawThreshold and abs(faceBoxes[0].roll) < rollThreshold and abs(faceBoxes[0].pitch) < pitchThreshold:
            isNotFront = False
        
        if faceBoxes[0].face_occlusion > occlusionThreshold:
            isOcclusion = True

        if faceBoxes[0].left_eye_closed > eyeClosureThreshold or faceBoxes[0].right_eye_closed > eyeClosureThreshold:
            isEyeClosure = True

        if faceBoxes[0].mouth_opened > mouthOpeningThreshold:
            isMouthOpening = True
        
        if (faceBoxes[0].x1 < image_np.shape[1] * borderRate or 
            faceBoxes[0].y1 < image_np.shape[0] * borderRate or 
                faceBoxes[0].x1 > image_np.shape[1] - image_np.shape[1] * borderRate or 
                faceBoxes[0].x1 > image_np.shape[0] - image_np.shape[0] * borderRate):
            isBoundary = True

        if faceBoxes[0].eye_dist < smallFaceThreshold:
            isSmall = True
        
        if faceBoxes[0].face_quality < lowQualityThreshold:
            quality = "Low"
        elif faceBoxes[0].face_quality < hightQualityThreshold:
            quality = "Medium"
        else:
            quality = "High"
        
        if faceBoxes[0].face_luminance < luminanceDarkThreshold:
            luminance = "Dark"
        elif faceBoxes[0].face_luminance < luminanceLightThreshold:
            luminance = "Normal"
        else:
            luminance = "Light"

    faceState = {"is_not_front": isNotFront, "is_occluded": isOcclusion, "eye_closed": isEyeClosure, "mouth_opened": isMouthOpening, 
                    "is_boundary_face": isBoundary, "is_small": isSmall, "quality": quality, "luminance": luminance, "result": result, "liveness_score": livenessScore}
    response = jsonify({"face_state": faceState, "faces": faces})

    response.status_code = 200
    response.headers["Content-Type"] = "application/json; charset=utf-8"
    return response


if __name__ == '__main__':
    port = int(os.environ.get("PORT", 8888))
    app.run(host='0.0.0.0', port=port)