def match_two_images(self, thresh, score_rec, image_base64_1, image_base64_2):
"""
Match face in two images.
Once a face matched, it will return True.
:param image_base64_1: image encoded in base64
:param image_base64_2: image encoded in base64
:param score_rec: float, the score of detected faces should be larger than score_rec
:param thresh: distance between face and matched face should be smaller than thresh
:return:bool: True means face matched, False means face not matched.
"""
image_1 = resize(base64_to_image(image_base64_1))
image_2 = resize(base64_to_image(image_base64_2))
faces_1, scores_1, idx_1 = self.detector.run(image_1, 1, score_rec)
faces_2, scores_2, idx_2 = self.detector.run(image_2, 1, score_rec)
if len(faces_1) != 1 or len(faces_2) != 1:
raise FaceNum
shape_1 = self.sp(image_1, faces_1[0])
face_chip_1 = dlib.get_face_chip(image_1, shape_1)
face_descriptor_1 = np.array(self.facerec.compute_face_descriptor(face_chip_1))
shape_2 = self.sp(image_2, faces_2[0])
face_chip_2 = dlib.get_face_chip(image_2, shape_2)
face_descriptor_2 = np.array(self.facerec.compute_face_descriptor(face_chip_2))
distance = calculate_distance(face_descriptor_1, face_descriptor_2)
if distance < thresh:
return True # True means face matched
return False # False means face not matched
def car_plate_match(self, image_base64):
"""
现场监控图像提取车牌信息，在证件信息提取的结果中进行比对。
:param image_base64: image encoded in base64
:return: bool, True表示匹配，False表示不匹配
"""
image = base64_to_image(image_base64)
ocr_result = self.get_all(image)
plate = []
for line in ocr_result:
info = re.search('[\u4E00-\u9FA5][A-Z][A-Z0-9]{4}[A-Z0-9挂学警港澳]',
line[-1][0])
if info:
plate.append(info.group(0))
for key, value in self.tmp_result.items():
if value:
if "车牌" in value.keys():
if value["车牌"] in plate:
return True
return False
def match_identity(self, feature_vector, thresh, score_rec, image_base64):
"""
Match the input feature vector and vector for each face in one image.
Once a face matched, it will return True.
:param score_rec: float, the score of detected faces should be larger than score_rec
:param feature_vector: list, the feature vector to be matched
:param thresh: distance between face and matched face should be smaller than thresh
:param image_base64: image encoded in base64
:return: bool, True means face matched, False means face not matched.
"""
image = resize(base64_to_image(image_base64))
faces, scores, idx = self.detector.run(image, 1, score_rec)
for face in faces:
shape = self.sp(image, face)
face_chip = dlib.get_face_chip(image, shape)
face_descriptor = np.array(self.facerec.compute_face_descriptor(face_chip))
distance = calculate_distance(face_descriptor, np.array(feature_vector))
# print(distance)
if distance < thresh:
return True # True means face matched
return False # False means face not matched
def face_register(self, image_base64, score_reg):
"""
Registers only one face in one picture.
:param score_reg: float, the score of the face to be registered should be larger than score_reg
:param image_base64: image encoded in base64
:return: list: the feature vector of the face in input image
"""
image = base64_to_image(image_base64)
# print(image.shape[0], image.shape[1])
if image.shape[0] > 1000 or image.shape[1] > 1000:
if image.shape[0] > image.shape[1]:
proportion = 1000 / image.shape[0]
else:
proportion = 1000 / image.shape[1]
image = cv2.resize(image, None, fx=proportion, fy=proportion, interpolation=cv2.INTER_AREA)
faces, scores, idx = self.detector.run(image, 1, score_reg)
if len(faces) != 1:
raise FaceNum
shape = self.sp(image, faces[0])
face_chip = dlib.get_face_chip(image, shape)
feature_vector = list(self.facerec.compute_face_descriptor(face_chip))
return feature_vector
def recog_one(self, image_base64):
"""
Recognize one image, and to update tmp_result dict
:param image_base64: image encoded in base64
:return: tmp_result: e.x. {"特种设备使用登记证": {"发证日期": "2018年8月1日"}，
"中华人民共和国道路运输证": {"有效期": None, "经营范围": "危险化学品", "车牌": "鲁FBR932"},
"危险货物运输押运人员证": None, "中华人民共和国机动车驾驶证": None,
"中华人民共和国机动车行驶证": None, "道路危险货物运输驾驶员证": None}
:return: pos: int, to tell client witch certificate the image is.
"""
image = base64_to_image(image_base64)
ocr_result = self.get_all(image)
name = self.name_recog(ocr_result)
if not name:
raise NameRecFail
pos = self.pos_dict[name]
result = {}
if name in self.config["人脸"]:
feature = face.face_register(image_base64, 0.5)
result["人脸"] = feature
self.face_feature.append(feature)
for key in self.config["证件"][name]:
if key == "证件名":
continue
method = self.config["证件"][name][key]
if isinstance(method, list):
loc = get_location(method[0], ocr_result)
result[key] = get_info_by_location(ocr_result, method[2], loc,
method[1], 20)
elif isinstance(method, str):
res = []
for line in ocr_result:
info = re.search(method, line[-1][0])
if info:
res.append(info.group(0))
result[key] = res
filter_one(result)
self.tmp_result[name] = result
return self.tmp_result, pos