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') image = 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) if faceCount == 0: image = image.rotate(90, expand=True) faceCount = faceDetection(image_np, image_np.shape[1], image_np.shape[0], faceBoxes, maxFaceCount) if faceCount == 0: image = image.rotate(90, expand=True) faceCount = faceDetection(image_np, image_np.shape[1], image_np.shape[0], faceBoxes, maxFaceCount) if faceCount == 0: image = image.rotate(90, expand=True) 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") image = 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) if faceCount == 0: image = image.rotate(90, expand=True) faceCount = faceDetection(image_np, image_np.shape[1], image_np.shape[0], faceBoxes, maxFaceCount) if faceCount == 0: image = image.rotate(90, expand=True) faceCount = faceDetection(image_np, image_np.shape[1], image_np.shape[0], faceBoxes, maxFaceCount) if faceCount == 0: image = image.rotate(90, expand=True) 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)