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import sys
sys.path.append('.')
import os
import numpy as np
import base64
import io
from PIL import Image, ExifTags
from flask import Flask, request, jsonify
from flask_cors import CORS
from facesdk import getMachineCode
from facesdk import setActivation
from facesdk import faceDetection
from facesdk import initSDK
from facebox import FaceBox
licensePath = "license.txt"
license = ""
# Get a specific environment variable by name
license = os.environ.get("LICENSE")
# Check if the variable exists
if license is not None:
print("Value of LICENSE:", license)
else:
license = ""
try:
with open(licensePath, 'r') as file:
license = file.read().strip()
except IOError as exc:
print("failed to open license.txt: ", exc.errno)
print("license: ", license)
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
machineCode = getMachineCode()
print("machineCode: ", machineCode.decode('utf-8'))
ret = setActivation(license.encode('utf-8'))
print("activation: ", ret)
ret = initSDK("data".encode('utf-8'))
print("init: ", ret)
app = Flask(__name__)
CORS(app)
def apply_exif_rotation(image):
# Get the EXIF data
try:
exif = image._getexif()
if exif is not None:
for orientation in ExifTags.TAGS.keys():
if ExifTags.TAGS[orientation] == 'Orientation':
break
# Get the orientation value
orientation = exif.get(orientation, None)
# Apply the appropriate rotation based on the orientation
if orientation == 3:
image = image.rotate(180, expand=True)
elif orientation == 6:
image = image.rotate(270, expand=True)
elif orientation == 8:
image = image.rotate(90, expand=True)
except AttributeError:
print("No EXIF data found")
return image
@app.route('/check_liveness', 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 = apply_exif_rotation(Image.open(file)).convert('RGB')
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"
elif faceCount < 0:
result = "License error!"
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('/check_liveness_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 = apply_exif_rotation(Image.open(io.BytesIO(image_data))).convert("RGB")
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"
elif faceCount < 0:
result = "License error!"
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", 8080))
app.run(host='0.0.0.0', port=port)
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