Reputation: 148
I have a folder that contains 10000 images, and 3 subfolders , each folder contains different number of images. I want to import a small portion of these images for training, that the limited size i chose manually each time i want to pick a portion of the data. I have already this python code :
train_dir = 'folder/train/' # This folder contains 10.000 images and 3 subfolders , each folder contains different number of images
from tqdm import tqdm
def get_data(folder):
"""
Load the data and labels from the given folder.
"""
X = []
y = []
for folderName in os.listdir(folder):
if not folderName.startswith('.'):
if folderName in ['Name1']:
label = 0
elif folderName in ['Name2']:
label = 1
elif folderName in ['Name3']:
label = 2
else:
label = 4
for image_filename in tqdm(os.listdir(folder + folderName)):
img_file = cv2.imread(folder + folderName + '/' + image_filename)
if img_file is not None:
img_file = skimage.transform.resize(img_file, (imageSize, imageSize, 1))
img_arr = np.asarray(img_file)
X.append(img_arr)
y.append(label)
X = np.asarray(X) # Keras only accepts data as numpy arrays
y = np.asarray(y)
return X,y
X_test, y_test= get_data(train_dir)
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X_test, y_test, test_size=0.2)
i want to specify Size
parameter so that i can choose the number of images to import. the number of imported images from each subfolder should be equal
Upvotes: 1
Views: 1509
Reputation: 370
You can read and store every paths from each folder in a separate list and select equal number of them.
folder1_files = []
for root, dirs, files in os.walk('path/folder1', topdown=False):
for i in files:
folder1_files.append("path/folder1/"+i)
to select:
train = folder1[:n] + folder2[:n] + folder3[:n]
n - number of images from each folder
Upvotes: 1