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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 initSDK
from facesdk import faceDetection
from facesdk import templateExtraction
from facesdk import similarityCalculation
from facebox import FaceBox
verifyThreshold = 0.67
maxFaceCount = 1
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)
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__)
@app.route('/compare_face', methods=['POST'])
def compare_face():
result = "None"
similarity = -1
face1 = None
face2 = None
file1 = request.files['file1']
file2 = request.files['file2']
try:
image1 = Image.open(file1).convert('RGB')
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).convert('RGB')
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 = 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
@app.route('/compare_face_base64', methods=['POST'])
def compare_face_base64():
result = "None"
similarity = -1
face1 = None
face2 = None
content = request.get_json()
try:
imageBase64_1 = content['base64_1']
image_data1 = base64.b64decode(imageBase64_1)
image1 = Image.open(io.BytesIO(image_data1)).convert('RGB')
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:
imageBase64_2 = content['base64_2']
image_data2 = base64.b64decode(imageBase64_2)
image2 = Image.open(io.BytesIO(image_data2)).convert('RGB')
except IOError as exc:
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 = 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
if __name__ == '__main__':
port = int(os.environ.get("PORT", 8080))
app.run(host='0.0.0.0', port=port)
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