带有Face_Recognition编码图像的Python
带有Face_Recognition编码图像的Python
提问于 2021-03-14 12:11:19
我使用识别软件包进行人脸识别
输入图像文件是base64编码的，
我试着破译数据
face_recognition.face_encodings(decodedBase64Data)我有脸编码的数据列表要比较。
问题是，我需要将base64数据转换为可以使用face_encodings编码的图像。
我试过
decodedData = base64.b64decode(data)
encodeFace = np.frombuffer(decodedData, np.uint8)并将encodedFace传递给
face_recognition.face_encodings(decodedBase64Data)我得到了错误Unsupported image type, must be 8bit gray or RGB image.
如何将base64转换成与face_encodings兼容的图像？
编辑:
附供参考的代码
import base64
import numpy as np
import json
import face_recognition as fr
with open('Face_Encoding_Data.json') as f:
EncodeJsonData = json.load(f)
personName = list(EncodeJsonData.keys())
encodedImgList = list(EncodeJsonData.values())
"""
EncodeJsonData = {"name1" : [encoded data 1], "name2" : [encoded data 2]}
128 byte
"""
base64Data = """ base64 encoded image with face """
encodeFace = np.frombuffer(base64.b64decode(base64Data), np.uint8)
matches = fr.compare_faces(encodedImgList, encodeFace, tolerance=0.5)
faceDist = fr.face_distance(encodedImgList, encodeFace)
matchIndex = np.argmin(faceDist)
name = "unknown"
if matches[matchIndex]:
name = personName[matchIndex]
print(name)Stack Overflow用户
发布于 2021-03-14 12:24:19
请共享代码以更好地理解问题，或者您可以使用下面的代码作为参考
import cv2
import os
import numpy as np
from PIL import Image
import time
cap = cv2.VideoCapture(1)
count=1
path='dataset2'
img=[]
imagepath = [os.path.join(path,f)for f in os.listdir(path)]
c=len(imagepath)
#for i in imagepath: i access the each images from my folder of images
while count<=c:
image = face_recognition.load_image_file("dataset2/vrushang."+str(count)+".jpg")
#now i will make list of the encoding parts to compare it runtime detected face
img.append(face_recognition.face_encodings(image)[0])
time.sleep(1)
count=count+1
face_locations = []
face_encodings = []
face_names = []
process_this_frame = True
img2 = []
img2 = img[0]
print"this is img2"
print img
while True:
ret, frame = cap.read()
small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
if process_this_frame:
face_locations = face_recognition.face_locations(small_frame)
face_encodings = face_recognition.face_encodings(small_frame, face_locations)
face_names = []
for face_encoding in face_encodings:
match = face_recognition.compare_faces(img, face_encoding)
print match
if match[0]==True:
name = "vrushang"
elif match[1]==True:
name = "hitu"
elif match[3]==True:
name = "sardar patel"
elif match[2]==True:
name = "yaksh"
else:
name = "unknown"
face_names.append(name)
process_this_frame = not process_this_frame
for (top, right, bottom, left), name in zip(face_locations, face_names):
top *= 4
right *= 4
bottom *= 4
left *= 4
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)
cv2.imshow('Video', frame)
if cv2.waitKey(1)==27:
break```页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/66624383
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