使用facenet进行人脸识别

Question

我想用facenet创建一个人脸识别，但我提到的大多数网站都使用tensorflow版本1而不是版本2。我对程序做了一点更改，使其可以在Tfv2中运行，但图像结果无法识别任何人脸。你们知道我的编码出了什么问题吗？

import cv2 
import numpy as np
import mtcnn
from architecture import *
from train_v2 import normalize,l2_normalizer
from scipy.spatial.distance import cosine
from tensorflow.keras.models import load_model
import pickle

def get_face(img, box):
x1, y1, width, height = box
x1, y1 = abs(x1), abs(y1)
x2, y2 = x1 + width, y1 + height
face = img[y1:y2, x1:x2]
return face, (x1, y1), (x2, y2)
def get_encode(face_encoder, face, size):
face = normalize(face)
face = cv2.resize(face, size)
encode = face_encoder.predict(np.expand_dims(face, axis=0))[0]
return encode

def load_pickle(path):
with open(path, 'rb') as f:
encoding_dict = pickle.load(f)
return encoding_dict

#required_shape = (160,160)
face_encoder = InceptionResNetV2()
path_m = "facenet_keras_weights.h5"
face_encoder.load_weights(path_m)
people_dir = 'Faces'
encodings_path = 'encodings/encodings.pkl'
test_img_path = 'friends.jpg'
test_res_path = 'result/friends.jpg'

recognition_t = 0.3
required_size = (160, 160)
face_detector = mtcnn.MTCNN()
encoding_dict = load_pickle(encodings_path)

img = cv2.imread(test_img_path)
# plt_show(img)
def detect(img ,detector,encoder,encoding_dict):
img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
results = detector.detect_faces(img_rgb)
for res in results:
face, pt_1, pt_2 = get_face(img_rgb, res['box'])
encode = get_encode(encoder, face, required_size)
encode = l2_normalizer.transform(np.expand_dims(encode, axis=0))[0]
name = 'unknown'
distance = float("inf")
for db_name, db_encode in encoding_dict.items():
dist = cosine(db_encode, encode)
if dist < recognition_t and dist < distance:
name = db_name
distance = dist
if name == 'unknown':
cv2.rectangle(img, pt_1, pt_2, (0, 0, 255), 2)
cv2.putText(img, name, pt_1, cv2.FONT_HERSHEY_PLAIN, 2, (0, 0, 255), 2)
else:
cv2.rectangle(img, pt_1, pt_2, (0, 255, 0), 2)
cv2.putText(img, name + f'__{distance:.2f}', pt_1, cv2.FONT_HERSHEY_PLAIN, 2, (0, 255, 0), 2)
cv2.imwrite(test_res_path, img)
cv2.imshow('Image', img)
cv2.waitKey(0)

Answer 1

为什么不在python的deepface框架中运行它？

这将验证两个图像是同一个人还是不同的人。

#!pip install deepface
from deepface import DeepFace
res = DeepFace.verify("img1.jpg", "img2.jpg", model_name = 'Facenet')

这将在数据库文件夹中查找img1.jpg的标识，并以pandas数据帧格式返回候选者。

df = DeepFace.find("img1.jpg", db_path = "C:/database")
print(df.head())

Deepface构建Facenet模型，下载预先训练的权重，在后台应用人脸识别管道的预处理阶段(检测和对齐(。您只需要调用它的验证或查找函数。