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 facebox import FaceBox

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

maxFaceCount = 10

licensePath = "license.txt"
license = ""

machineCode = getMachineCode()
print("machineCode: ", machineCode.decode('utf-8'))

try:
    with open(licensePath, 'r') as file:
        license = file.read()
except IOError as exc:
    print("failed to open license.txt: ", exc.errno)
print("license: ", license)

ret = setActivation(license.encode('utf-8'))
print("activation: ", ret)

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

app = Flask(__name__) 

@app.route('/check_liveness', methods=['POST'])
def check_liveness():
    file = request.files['file']
    image = Image.open(file)
    image_np = np.asarray(image)

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

    i = 0
    faces = []
    while (i < faceCount):
        j = 0
        landmark_68 = []
        while(j < 68):
            landmark_68.append({"x": faceBoxes[i].landmark_68[j * 2], "y": faceBoxes[i].landmark_68[j * 2 + 1]})
            j = j + 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})
        i = i + 1
    
    result = ""
    if faceCount == 0:
        result = "No face"
    elif faceCount > 1:
        result = "Multiple face"
    else:
        if faceBoxes[0].liveness > 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"

        status = "ok"
        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}
        response = jsonify({"face_state": faceState, "faces": faces})

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

    status = "ok"
    response = jsonify({"face_state": {"result": result}, "faces": faces})

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

@app.route('/check_liveness_base64', methods=['POST'])
def check_liveness_base64():
    content = request.get_json()
    imageBase64 = content['base64']
    image_data = base64.b64decode(imageBase64)

    image = Image.open(io.BytesIO(image_data))
    image_np = np.asarray(image)

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

    i = 0
    faces = []
    while (i < faceCount):
        j = 0
        landmark_68 = []
        while(j < 68):
            landmark_68.append({"x": faceBoxes[i].landmark_68[j * 2], "y": faceBoxes[i].landmark_68[j * 2 + 1]})
            j = j + 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})
        i = i + 1
    
    result = ""
    if faceCount == 0:
        result = "No face"
    elif faceCount > 1:
        result = "Multiple face"
    else:
        if faceBoxes[0].liveness > 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"

        status = "ok"
        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}
        response = jsonify({"face_state": faceState, "faces": faces})

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

    status = "ok"
    response = jsonify({"face_state": {"result": result}, "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", 8080))
    app.run(host='0.0.0.0', port=port)