使用使用npy转转image图像并保存的实例图像并保存的实例
主要介绍了使用npy转image图像并保存的实例,具有很好的参考价值,希望对大家有所帮助。一起跟随小编过
来看看吧
1. 用于分类模型:
import numpy as np
import scipy.misc
import cv2
import os
# DF1
path = "/home/pi/工作/predict1/"
npy_list = os.listdir(path)
save_path = "/home/pi/predict1_img/"
if not os.path.exists(save_path):
os.mkdir(save_path)
for i in range(0, len(npy_list)):
print(i)
print(npy_list[i])
npy_full_path = os.path.join(path, npy_list[i])
img = np.load(npy_full_path) # load进来
save_full_path = os.path.join(save_path, npy_list[i][:-4])
scipy.misc.imsave(save_full_path, img) # 保存
2. 用于分割模型
"""
将数据集随机分成训练集、测试集
传入参数:
ratio = 0.7 # 训练样本比例
path = "/home/pi/20190701_0705" # 数据路径
new_path = "/home/pi/20190701_0705_new2" # 保存路径
使用方法:
temp = Generate_Train_and_Test(path, new_path, ratio)
temp.splict_data()
"""
import random
import os
import cv2
def makeDir(path):
try:
if not os.path.exists(path):
if not os.path.isfile(path):
# os.mkdir(path)
os.makedirs(path)
return 0
else:
return 1
except Exception as e:
print(str(e))
return -2
class Generate_Train_and_Test:
def __init__(self, path, new_path, ratio):
if not os.path.exists(new_path):
makeDir(new_path)
self.path = path
self.new_path = new_path
self.ratio = ratio
self.train_sample_path = os.path.join(new_path, "train")
self.test_sample_path = os.path.join(new_path, "test")
makeDir(self.train_sample_path)
makeDir(self.test_sample_path)
def splict_data(self):
class_names = os.listdir(self.path) # 类别:bg and ng10
for name in class_names:
print("process class name=%s" % name)
tmp_class_name = os.path.join(self.path, name)
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