Python method to read all images in a specified folder

不言
Release: 2018-04-27 11:18:31
Original
6903 people have browsed it

The following is a Python method for reading all images in a specified folder. It has a good reference value and I hope it will be helpful to everyone. Let’s take a look together

(1) Data preparation

Data set introduction:

The data set stores 1223 There are 756 negative samples (image names are 0.1~0.756) and 458 positive samples (image names are 1.1~1.458), among which: the label before "." is the sample label, and the label after "." is the sample Serial number

(2) Use python to read all images in the folder

'''
Load the image files form the folder
input:
  imgDir: the direction of the folder
  imgName:the name of the folder
output:
  data:the data of the dataset
  label:the label of the datset
'''
def load_Img(imgDir,imgFoldName):
  imgs = os.listdir(imgDir+imgFoldName)
  imgNum = len(imgs)
  data = np.empty((imgNum,1,12,12),dtype="float32")
  label = np.empty((imgNum,),dtype="uint8")
  for i in range (imgNum):
    img = Image.open(imgDir+imgFoldName+"/"+imgs[i])
    arr = np.asarray(img,dtype="float32")
    data[i,:,:,:] = arr
    label[i] = int(imgs[i].split('.')[0])
  return data,label
Copy after login

The data and label obtained here are both ndarray data

data: (1223,1,12,12)

##label:(1223,)

Note: The nddary data type is a data type provided by numpy, that is, N-dimensional array, which makes up for the defect that array in python does not support multi-dimensionality

(3) Calling method

craterDir = "./data/CraterImg/Adjust/"
foldName = "East_CraterAdjust12"
data, label = load_Img(craterDir,foldName)
Copy after login

Related recommendations:


An example of how python reads a csv file and puts the file into a list

Python implements the method of generating a txt file with labels for the pictures in the file

The above is the detailed content of Python method to read all images in a specified folder. For more information, please follow other related articles on the PHP Chinese website!

Related labels:
source:php.cn
Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
Popular Tutorials
More>
Latest Downloads
More>
Web Effects
Website Source Code
Website Materials
Front End Template
About us Disclaimer Sitemap
php.cn:Public welfare online PHP training,Help PHP learners grow quickly!