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Implemented liveness detection functionality within Docker
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/data |
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import sys | ||
sys.path.append('.') | ||
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import os | ||
import numpy as np | ||
import base64 | ||
import io | ||
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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 | ||
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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 | ||
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maxFaceCount = 10 | ||
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licensePath = "license.txt" | ||
license = "" | ||
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machineCode = getMachineCode() | ||
print("machineCode: ", machineCode.decode('utf-8')) | ||
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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) | ||
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ret = setActivation(license.encode('utf-8')) | ||
print("activation: ", ret) | ||
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ret = initSDK("data".encode('utf-8')) | ||
print("init: ", ret) | ||
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app = Flask(__name__) | ||
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@app.route('/check_liveness', methods=['POST']) | ||
def check_liveness(): | ||
file = request.files['file'] | ||
image = Image.open(file) | ||
image_np = np.asarray(image) | ||
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faceBoxes = (FaceBox * maxFaceCount)() | ||
faceCount = faceDetection(image_np, image_np.shape[1], image_np.shape[0], faceBoxes, maxFaceCount) | ||
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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 | ||
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result = "" | ||
if faceCount == 0: | ||
result = "No face" | ||
elif faceCount > 1: | ||
result = "Multiple face" | ||
else: | ||
if faceBoxes[0].liveness > livenessThreshold: | ||
result = "Real" | ||
else: | ||
result = "Spoof" | ||
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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 | ||
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if faceBoxes[0].face_occlusion > occlusionThreshold: | ||
isOcclusion = True | ||
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if faceBoxes[0].left_eye_closed > eyeClosureThreshold or faceBoxes[0].right_eye_closed > eyeClosureThreshold: | ||
isEyeClosure = True | ||
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if faceBoxes[0].mouth_opened > mouthOpeningThreshold: | ||
isMouthOpening = True | ||
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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 | ||
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if faceBoxes[0].eye_dist < smallFaceThreshold: | ||
isSmall = True | ||
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if faceBoxes[0].face_quality < lowQualityThreshold: | ||
quality = "Low" | ||
elif faceBoxes[0].face_quality < hightQualityThreshold: | ||
quality = "Medium" | ||
else: | ||
quality = "High" | ||
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if faceBoxes[0].face_luminance < luminanceDarkThreshold: | ||
luminance = "Dark" | ||
elif faceBoxes[0].face_luminance < luminanceLightThreshold: | ||
luminance = "Normal" | ||
else: | ||
luminance = "Light" | ||
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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}) | ||
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response.status_code = 200 | ||
response.headers["Content-Type"] = "application/json; charset=utf-8" | ||
return response | ||
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status = "ok" | ||
response = jsonify({"face_state": {"result": result}, "faces": faces}) | ||
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response.status_code = 200 | ||
response.headers["Content-Type"] = "application/json; charset=utf-8" | ||
return response | ||
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@app.route('/check_liveness_base64', methods=['POST']) | ||
def check_liveness_base64(): | ||
content = request.get_json() | ||
imageBase64 = content['base64'] | ||
image_data = base64.b64decode(imageBase64) | ||
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image = Image.open(io.BytesIO(image_data)) | ||
image_np = np.asarray(image) | ||
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faceBoxes = (FaceBox * maxFaceCount)() | ||
faceCount = faceDetection(image_np, image_np.shape[1], image_np.shape[0], faceBoxes, maxFaceCount) | ||
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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 | ||
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result = "" | ||
if faceCount == 0: | ||
result = "No face" | ||
elif faceCount > 1: | ||
result = "Multiple face" | ||
else: | ||
if faceBoxes[0].liveness > livenessThreshold: | ||
result = "Real" | ||
else: | ||
result = "Spoof" | ||
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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 | ||
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if faceBoxes[0].face_occlusion > occlusionThreshold: | ||
isOcclusion = True | ||
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if faceBoxes[0].left_eye_closed > eyeClosureThreshold or faceBoxes[0].right_eye_closed > eyeClosureThreshold: | ||
isEyeClosure = True | ||
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if faceBoxes[0].mouth_opened > mouthOpeningThreshold: | ||
isMouthOpening = True | ||
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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 | ||
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if faceBoxes[0].eye_dist < smallFaceThreshold: | ||
isSmall = True | ||
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if faceBoxes[0].face_quality < lowQualityThreshold: | ||
quality = "Low" | ||
elif faceBoxes[0].face_quality < hightQualityThreshold: | ||
quality = "Medium" | ||
else: | ||
quality = "High" | ||
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if faceBoxes[0].face_luminance < luminanceDarkThreshold: | ||
luminance = "Dark" | ||
elif faceBoxes[0].face_luminance < luminanceLightThreshold: | ||
luminance = "Normal" | ||
else: | ||
luminance = "Light" | ||
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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}) | ||
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response.status_code = 200 | ||
response.headers["Content-Type"] = "application/json; charset=utf-8" | ||
return response | ||
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status = "ok" | ||
response = jsonify({"face_state": {"result": result}, "faces": faces}) | ||
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response.status_code = 200 | ||
response.headers["Content-Type"] = "application/json; charset=utf-8" | ||
return response | ||
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if __name__ == '__main__': | ||
port = int(os.environ.get("PORT", 8080)) | ||
app.run(host='0.0.0.0', port=port) |
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from ctypes import * | ||
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class FaceBox(Structure): | ||
_fields_ = [("x1", c_int32), ("y1", c_int32), ("x2", c_int32), ("y2", c_int32), | ||
("liveness", c_float), | ||
("yaw", c_float), ("roll", c_float), ("pitch", c_float), | ||
("face_quality", c_float), ("face_luminance", c_float), ("eye_dist", c_float), | ||
("left_eye_closed", c_float), ("right_eye_closed", c_float), | ||
("face_occlusion", c_float), ("mouth_opened", c_float), | ||
("landmark_68", c_float * 136) | ||
] |
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import os | ||
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from ctypes import * | ||
from numpy.ctypeslib import ndpointer | ||
from facebox import FaceBox | ||
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libPath = os.path.abspath(os.path.dirname(__file__)) + '/libfacesdk1.so' | ||
facesdk = cdll.LoadLibrary(libPath) | ||
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getMachineCode = facesdk.getMachineCode | ||
getMachineCode.argtypes = [] | ||
getMachineCode.restype = c_char_p | ||
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setActivation = facesdk.setActivation | ||
setActivation.argtypes = [c_char_p] | ||
setActivation.restype = c_int32 | ||
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initSDK = facesdk.initSDK | ||
initSDK.argtypes = [c_char_p] | ||
initSDK.restype = c_int32 | ||
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faceDetection = facesdk.faceDetection | ||
faceDetection.argtypes = [ndpointer(c_ubyte, flags='C_CONTIGUOUS'), c_int32, c_int32, POINTER(FaceBox), c_int32] | ||
faceDetection.restype = c_int32 | ||
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flask | ||
flask-cors | ||
Pillow | ||
numpy |