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import sys |
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sys.path.append('.') |
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import os |
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import numpy as np |
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import base64 |
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import io |
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from PIL import Image |
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from flask import Flask, request, jsonify |
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from facesdk import getMachineCode |
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from facesdk import setActivation |
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from facesdk import initSDK |
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from facesdk import faceDetection |
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from facesdk import templateExtraction |
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from facesdk import similarityCalculation |
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from facebox import FaceBox |
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verifyThreshold = 0.67 |
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maxFaceCount = 1 |
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licensePath = "license.txt" |
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license = "" |
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license = os.environ.get("LICENSE") |
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if license is not None: |
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print("Value of LICENSE:", license) |
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else: |
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license = "" |
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try: |
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with open(licensePath, 'r') as file: |
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license = file.read().strip() |
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except IOError as exc: |
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print("failed to open license.txt: ", exc.errno) |
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print("license: ", license) |
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machineCode = getMachineCode() |
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print("machineCode: ", machineCode.decode('utf-8')) |
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ret = setActivation(license.encode('utf-8')) |
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print("activation: ", ret) |
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ret = initSDK("data".encode('utf-8')) |
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print("init: ", ret) |
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app = Flask(__name__) |
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@app.route('/compare_face', methods=['POST']) |
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def compare_face(): |
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result = "None" |
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similarity = -1 |
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face1 = None |
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face2 = None |
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file1 = request.files['file1'] |
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file2 = request.files['file2'] |
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try: |
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image1 = Image.open(file1).convert('RGB') |
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except: |
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result = "Failed to open file1" |
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response = jsonify({"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2}) |
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response.status_code = 200 |
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response.headers["Content-Type"] = "application/json; charset=utf-8" |
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return response |
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try: |
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image2 = Image.open(file2).convert('RGB') |
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except: |
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result = "Failed to open file2" |
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response = jsonify({"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2}) |
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response.status_code = 200 |
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response.headers["Content-Type"] = "application/json; charset=utf-8" |
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return response |
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image_np1 = np.asarray(image1) |
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image_np2 = np.asarray(image2) |
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faceBoxes1 = (FaceBox * maxFaceCount)() |
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faceCount1 = faceDetection(image_np1, image_np1.shape[1], image_np1.shape[0], faceBoxes1, maxFaceCount) |
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faceBoxes2 = (FaceBox * maxFaceCount)() |
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faceCount2 = faceDetection(image_np2, image_np2.shape[1], image_np2.shape[0], faceBoxes2, maxFaceCount) |
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if faceCount1 == 1 and faceCount2 == 1: |
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templateExtraction(image_np1, image_np1.shape[1], image_np1.shape[0], faceBoxes1[0]) |
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templateExtraction(image_np2, image_np2.shape[1], image_np2.shape[0], faceBoxes2[0]) |
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similarity = similarityCalculation(faceBoxes1[0].templates, faceBoxes2[0].templates) |
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if similarity > verifyThreshold: |
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result = "Same person" |
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else: |
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result = "Different person" |
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elif faceCount1 == 0: |
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result = "No face1" |
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elif faceCount2 == 0: |
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result = "No face2" |
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if faceCount1 == 1: |
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landmark_68 = [] |
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for j in range(68): |
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landmark_68.append({"x": faceBoxes1[0].landmark_68[j * 2], "y": faceBoxes1[0].landmark_68[j * 2 + 1]}) |
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face1 = {"x1": faceBoxes1[0].x1, "y1": faceBoxes1[0].y1, "x2": faceBoxes1[0].x2, "y2": faceBoxes1[0].y2, |
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"yaw": faceBoxes1[0].yaw, "roll": faceBoxes1[0].roll, "pitch": faceBoxes1[0].pitch, |
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"face_quality": faceBoxes1[0].face_quality, "face_luminance": faceBoxes1[0].face_luminance, "eye_dist": faceBoxes1[0].eye_dist, |
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"left_eye_closed": faceBoxes1[0].left_eye_closed, "right_eye_closed": faceBoxes1[0].right_eye_closed, |
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"face_occlusion": faceBoxes1[0].face_occlusion, "mouth_opened": faceBoxes1[0].mouth_opened, |
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"landmark_68": landmark_68} |
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if faceCount2 == 1: |
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landmark_68 = [] |
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for j in range(68): |
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landmark_68.append({"x": faceBoxes2[0].landmark_68[j * 2], "y": faceBoxes2[0].landmark_68[j * 2 + 1]}) |
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face2 = {"x1": faceBoxes2[0].x1, "y1": faceBoxes2[0].y1, "x2": faceBoxes2[0].x2, "y2": faceBoxes2[0].y2, |
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"yaw": faceBoxes2[0].yaw, "roll": faceBoxes2[0].roll, "pitch": faceBoxes2[0].pitch, |
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"face_quality": faceBoxes2[0].face_quality, "face_luminance": faceBoxes2[0].face_luminance, "eye_dist": faceBoxes2[0].eye_dist, |
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"left_eye_closed": faceBoxes2[0].left_eye_closed, "right_eye_closed": faceBoxes2[0].right_eye_closed, |
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"face_occlusion": faceBoxes2[0].face_occlusion, "mouth_opened": faceBoxes2[0].mouth_opened, |
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"landmark_68": landmark_68} |
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response = jsonify({"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2}) |
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response.status_code = 200 |
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response.headers["Content-Type"] = "application/json; charset=utf-8" |
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return response |
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@app.route('/compare_face_base64', methods=['POST']) |
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def compare_face_base64(): |
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result = "None" |
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similarity = -1 |
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face1 = None |
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face2 = None |
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content = request.get_json() |
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try: |
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imageBase64_1 = content['base64_1'] |
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image_data1 = base64.b64decode(imageBase64_1) |
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image1 = Image.open(io.BytesIO(image_data1)).convert('RGB') |
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except: |
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result = "Failed to open file1" |
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response = jsonify({"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2}) |
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response.status_code = 200 |
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response.headers["Content-Type"] = "application/json; charset=utf-8" |
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return response |
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try: |
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imageBase64_2 = content['base64_2'] |
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image_data2 = base64.b64decode(imageBase64_2) |
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image2 = Image.open(io.BytesIO(image_data2)).convert('RGB') |
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except IOError as exc: |
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result = "Failed to open file2" |
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response = jsonify({"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2}) |
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response.status_code = 200 |
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response.headers["Content-Type"] = "application/json; charset=utf-8" |
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return response |
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image_np1 = np.asarray(image1) |
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image_np2 = np.asarray(image2) |
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faceBoxes1 = (FaceBox * maxFaceCount)() |
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faceCount1 = faceDetection(image_np1, image_np1.shape[1], image_np1.shape[0], faceBoxes1, maxFaceCount) |
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faceBoxes2 = (FaceBox * maxFaceCount)() |
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faceCount2 = faceDetection(image_np2, image_np2.shape[1], image_np2.shape[0], faceBoxes2, maxFaceCount) |
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if faceCount1 == 1 and faceCount2 == 1: |
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templateExtraction(image_np1, image_np1.shape[1], image_np1.shape[0], faceBoxes1[0]) |
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templateExtraction(image_np2, image_np2.shape[1], image_np2.shape[0], faceBoxes2[0]) |
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similarity = similarityCalculation(faceBoxes1[0].templates, faceBoxes2[0].templates) |
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if similarity > verifyThreshold: |
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result = "Same person" |
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else: |
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result = "Different person" |
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elif faceCount1 == 0: |
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result = "No face1" |
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elif faceCount2 == 0: |
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result = "No face2" |
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if faceCount1 == 1: |
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landmark_68 = [] |
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for j in range(68): |
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landmark_68.append({"x": faceBoxes1[0].landmark_68[j * 2], "y": faceBoxes1[0].landmark_68[j * 2 + 1]}) |
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face1 = {"x1": faceBoxes1[0].x1, "y1": faceBoxes1[0].y1, "x2": faceBoxes1[0].x2, "y2": faceBoxes1[0].y2, |
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"yaw": faceBoxes1[0].yaw, "roll": faceBoxes1[0].roll, "pitch": faceBoxes1[0].pitch, |
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"face_quality": faceBoxes1[0].face_quality, "face_luminance": faceBoxes1[0].face_luminance, "eye_dist": faceBoxes1[0].eye_dist, |
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"left_eye_closed": faceBoxes1[0].left_eye_closed, "right_eye_closed": faceBoxes1[0].right_eye_closed, |
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"face_occlusion": faceBoxes1[0].face_occlusion, "mouth_opened": faceBoxes1[0].mouth_opened, |
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"landmark_68": landmark_68} |
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if faceCount2 == 1: |
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landmark_68 = [] |
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for j in range(68): |
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landmark_68.append({"x": faceBoxes2[0].landmark_68[j * 2], "y": faceBoxes2[0].landmark_68[j * 2 + 1]}) |
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face2 = {"x1": faceBoxes2[0].x1, "y1": faceBoxes2[0].y1, "x2": faceBoxes2[0].x2, "y2": faceBoxes2[0].y2, |
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"yaw": faceBoxes2[0].yaw, "roll": faceBoxes2[0].roll, "pitch": faceBoxes2[0].pitch, |
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"face_quality": faceBoxes2[0].face_quality, "face_luminance": faceBoxes2[0].face_luminance, "eye_dist": faceBoxes2[0].eye_dist, |
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"left_eye_closed": faceBoxes2[0].left_eye_closed, "right_eye_closed": faceBoxes2[0].right_eye_closed, |
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"face_occlusion": faceBoxes2[0].face_occlusion, "mouth_opened": faceBoxes2[0].mouth_opened, |
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"landmark_68": landmark_68} |
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response = jsonify({"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2}) |
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response.status_code = 200 |
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response.headers["Content-Type"] = "application/json; charset=utf-8" |
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return response |
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if __name__ == '__main__': |
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port = int(os.environ.get("PORT", 8080)) |
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app.run(host='0.0.0.0', port=port) |
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