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test.py
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test.py
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import sys
sys.path.append('.')
from PIL import Image
import numpy as np
from facesdk import getMachineCode
from facesdk import setActivation
from facesdk import faceDetection
from facesdk import initSDK
from facesdk import templateExtraction
from facesdk import similarityCalculation
from facebox import FaceBox
verifyThreshold = 0.7
maxFaceCount = 1
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("D:/Temp/kby_face/github/FaceRecognition-Windows/data".encode('utf-8'))
print("init: ", ret)
def compare_face(file1, file2):
result = "None"
similarity = -1
face1 = None
face2 = None
try:
image1 = Image.open(file1)
except:
result = "Failed to open file1"
response = jsonify({"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2})
response.status_code = 200
response.headers["Content-Type"] = "application/json; charset=utf-8"
return response
try:
image2 = Image.open(file2)
except:
result = "Failed to open file2"
response = jsonify({"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2})
response.status_code = 200
response.headers["Content-Type"] = "application/json; charset=utf-8"
return response
image_np1 = np.asarray(image1)
image_np2 = np.asarray(image2)
faceBoxes1 = (FaceBox * maxFaceCount)()
faceCount1 = faceDetection(image_np1, image_np1.shape[1], image_np1.shape[0], faceBoxes1, maxFaceCount)
faceBoxes2 = (FaceBox * maxFaceCount)()
faceCount2 = faceDetection(image_np2, image_np2.shape[1], image_np2.shape[0], faceBoxes2, maxFaceCount)
if faceCount1 == 1 and faceCount2 == 1:
templateExtraction(image_np1, image_np1.shape[1], image_np1.shape[0], faceBoxes1[0])
templateExtraction(image_np2, image_np2.shape[1], image_np2.shape[0], faceBoxes2[0])
similarity = similarityCalculation(faceBoxes1[0].templates, faceBoxes2[0].templates)
if similarity > verifyThreshold:
result = "Same person"
else:
result = "Different person"
elif faceCount1 == 0:
result = "No face1"
elif faceCount2 == 0:
result = "No face2"
if faceCount1 == 1:
# landmark_68 = []
# for j in range(68):
# landmark_68.append({"x": faceBoxes1[0].landmark_68[j * 2], "y": faceBoxes1[0].landmark_68[j * 2 + 1]})
face1 = {"x1": faceBoxes1[0].x1, "y1": faceBoxes1[0].y1, "x2": faceBoxes1[0].x2, "y2": faceBoxes1[0].y2,
"yaw": faceBoxes1[0].yaw, "roll": faceBoxes1[0].roll, "pitch": faceBoxes1[0].pitch,
"face_quality": faceBoxes1[0].face_quality, "face_luminance": faceBoxes1[0].face_luminance, "eye_dist": faceBoxes1[0].eye_dist,
"left_eye_closed": faceBoxes1[0].left_eye_closed, "right_eye_closed": faceBoxes1[0].right_eye_closed,
"face_occlusion": faceBoxes1[0].face_occlusion, "mouth_opened": faceBoxes1[0].mouth_opened}
# "landmark_68": landmark_68}
if faceCount2 == 1:
# landmark_68 = []
# for j in range(68):
# landmark_68.append({"x": faceBoxes2[0].landmark_68[j * 2], "y": faceBoxes2[0].landmark_68[j * 2 + 1]})
face2 = {"x1": faceBoxes2[0].x1, "y1": faceBoxes2[0].y1, "x2": faceBoxes2[0].x2, "y2": faceBoxes2[0].y2,
"yaw": faceBoxes2[0].yaw, "roll": faceBoxes2[0].roll, "pitch": faceBoxes2[0].pitch,
"face_quality": faceBoxes2[0].face_quality, "face_luminance": faceBoxes2[0].face_luminance, "eye_dist": faceBoxes2[0].eye_dist,
"left_eye_closed": faceBoxes2[0].left_eye_closed, "right_eye_closed": faceBoxes2[0].right_eye_closed,
"face_occlusion": faceBoxes2[0].face_occlusion, "mouth_opened": faceBoxes2[0].mouth_opened}
# "landmark_68": landmark_68}
response = {"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2}
return response
if __name__ == "__main__":
ret = compare_face('D:/Temp/kby_face/github/FaceRecognition-Windows/face_examples/1.jpg', 'D:/Temp/kby_face/github/FaceRecognition-Windows/face_examples/2.jpg')
print(ret)