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myGenerator.py
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import csv
import json
import os
import numpy as np
import cv2
from matplotlib import pyplot
def cv_imread(filePath):
cv_img = cv2.imdecode(np.fromfile(filePath, dtype=np.uint8), -1)
return cv_img
def show_array_to_image(arrayData):
pyplot.imshow(arrayData)
pyplot.show()
def load_train(csvDir, width, height, batch_size):
fx = 0.0
fy = 0.0
# 处理列表得到数组
images_path = []
labels_path = []
csvFile = open(csvDir, "r")
reader = csv.reader(csvFile)
content = list(reader)
for item in content:
images_path.append(item[0])
labels_path.append(item[1])
# 进入循环读取照片
# print(len(images_path))
# for image, label in zip(images_path, labels_path):
while True:
image_data_array = []
label_data_array = []
index_group = np.random.randint(0, len(images_path), batch_size)
# print("batch_size:", str(index_group))
for index in index_group:
image = images_path[index]
label = labels_path[index]
image_data = cv_imread(image)
image_data = cv2.resize(image_data, (width, height), fx=fx, fy=fy, interpolation=cv2.INTER_CUBIC)
image_data = image_data.astype(np.float32)
image_data = np.multiply(image_data, 1.0 / 255.0)
image_data_array.append(image_data)
label_data = cv_imread(label)
# label_data = cv2.cvtColor(label_data, cv2.COLOR_GRAY2BGR) # 颜色转化
label_data = cv2.resize(label_data, (width, height), fx=fx, fy=fy, interpolation=cv2.INTER_CUBIC)
label_data = label_data.astype(np.float32)
label_data = np.multiply(label_data, 1.0 / 255.0)
label_data_array.append(label_data)
image_data_r = np.array(image_data_array)
label_data_r = np.array(label_data_array)
yield image_data_r, label_data_r
# image_data_array.append(image_data)
# label_data_array.append(label_data)
# return image_data_array, label_data_array
def load_test(csvDir, width, height, batch_size):
fx = 0.0
fy = 0.0
# 处理列表得到数组
images_path = []
labels_path = []
csvFile = open(csvDir, "r")
reader = csv.reader(csvFile)
content = list(reader)
for item in content:
images_path.append(item[0])
labels_path.append(item[1])
# 进入循环读取照片
# for image, label in zip(images_path, labels_path):
image_data_array = []
label_data_array = []
index_group = np.random.randint(0, len(images_path), batch_size)
# print("batch_size:", str(index_group))
for index in index_group:
image = images_path[index]
label = labels_path[index]
image_data = cv_imread(image)
image_data = cv2.resize(image_data, (width, height), fx=fx, fy=fy, interpolation=cv2.INTER_CUBIC)
image_data = image_data.astype(np.float32)
image_data = np.multiply(image_data, 1.0 / 255.0)
image_data_array.append(image_data)
label_data = cv_imread(label)
# label_data = cv2.cvtColor(label_data, cv2.COLOR_GRAY2BGR) # 颜色转化
label_data = cv2.resize(label_data, (width, height), fx=fx, fy=fy, interpolation=cv2.INTER_CUBIC)
label_data = label_data.astype(np.float32)
label_data = np.multiply(label_data, 1.0 / 255.0)
label_data_array.append(label_data)
image_data_r = np.array(image_data_array)
label_data_r = np.array(label_data_array)
return image_data_r, label_data_r
# image_data_array.append(image_data)
# label_data_array.append(label_data)
# return image_data_array, label_data_array
def load_validate(validate_path, width, height):
root = os.getcwd()
with open(validate_path, 'r') as load_f:
load_dict = json.load(load_f)
# num_image = len(load_dict)
# 只产生512个数据，避免内存过大
while True:
images = []
labels = []
classes = np.zeros(61)
number = np.random.random_integers(0, len(load_dict) - 1, 512)
for image in number:
index = load_dict[image]["disease_class"]
path = load_dict[image]['image_id']
img_path = os.path.join(root, 'AgriculturalDisease_validationset', 'images', path)
image_data = cv_imread(img_path)
image_data = cv2.resize(image_data, (width, height), 0, 0, cv2.INTER_LINEAR)
image_data = image_data.astype(np.float32)
image_data = np.multiply(image_data, 1.0 / 255.0)
images.append(image_data)
label = np.zeros(len(classes))
label[index] = 1
labels.append(label)
images = np.array(images)
labels = np.array(labels)
yield images, labels
if __name__ == '__main__':
lt = load_train(r"E:\train_data\carChallenge\mycsv.csv", 512, 512)
# print(next(lt)[0].shape)
# 将图片转化为jpg格式
# images_path = []
# labels_path = []
# csvFile = open(r"E:\train_data\carChallenge\mycsv.csv", "r")
# reader = csv.reader(csvFile)
# content = list(reader)
# for item in content:
# labels_path_one =item[1]
# # print(type(labels_path_one))
# name = labels_path_one.split("\\")
# # print(name[4])
# name = name[4].split(".")
# name = name[0]+".jpg"
# url = r"E:\train_data\carChallenge\train_maskss"
# path = os.path.join(url, name)
# from PIL import Image
# im = Image.open(labels_path_one)
# im = im.convert('RGB')
# im.save(path)