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cungudafa authored 2020-08-08 09:50 . sign
# 从人脸图像文件中提取人脸特征存入 CSV
# Features extraction from images and save into features_all.csv
# return_128d_features() 获取某张图像的128D特征
# compute_the_mean() 计算128D特征均值
from cv2 import cv2 as cv2
import os
import csv
import numpy as np
import time
from pose_hand import getImgInfo
from yolo import YOLO
from pose.coco import general_coco_model
# ----------------------------------------------------------------------------------
# 第一步 读取标签Y和图片路径X
# ----------------------------------------------------------------------------------
X = [] # 定义图像名称
Y = [] # 定义图像分类类标
# Z = [] #定义图像像素
path = 'D:/myworkspace/dataset/My_test/dataset/test'
for idx, labelname in enumerate(os.listdir(path)):
if ".txt" not in labelname:
f = os.path.join(path, labelname)
for i, imgname in enumerate(os.listdir(f)):
imgpath = os.path.join(f, imgname)
X.append(imgpath)
Y.append(labelname)
X = np.array(X)
Y = np.array(Y)
# ----------------------------------------------------------------------------------
# 第二步 识别infolist
# ----------------------------------------------------------------------------------
# coco
modelpath = "model/"
start = time.time()
pose_model = general_coco_model(modelpath) # 1.加载模型
print("[INFO]Pose Model loads time: ", time.time() - start)
# yolo
start = time.time()
_yolo = YOLO() # 1.加载模型
print("[INFO]yolo Model loads time: ", time.time() - start)
infolist = []
for i in X:
hist = getImgInfo(i, pose_model, _yolo) # 识别
infolist.append(hist)
# ----------------------------------------------------------------------------------
# 第三步 存储信息docs/feature/features_all.csv
# ----------------------------------------------------------------------------------
# 路径存储到txt
orb = open('D:/myworkspace/dataset/My_test/bagofwords/y_train.txt', 'w')
for i, img_path in enumerate(X):
orb.write(img_path)
#orb.write('\n'+str(info)+str(infolist[i]))
orb.close()
# 特征存储到 csv
with open("docs/feature/features_all.csv", "w", newline="") as csvfile:
writer = csv.writer(csvfile)
for i in infolist:
writer.writerow(i)
print("所有录入手语特征数据存入 / Save all the features of sign registered into: docs/feature/features_all.csv")

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