Datasets:
Tasks:
Feature Extraction
Modalities:
Image
Formats:
imagefolder
Size:
10K - 100K
Tags:
climate
License:
File size: 1,199 Bytes
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import os
import random
# Change the static percentage parameter to scale down
def remove_random_images(base_path, percentage=5):
"""Removes 5% percentage of images randomly from each class subdirectory."""
subsets = ['test', 'train', 'val']
for subset in subsets:
subset_path = os.path.join(base_path, subset)
if not os.path.exists(subset_path):
continue
for class_name in os.listdir(subset_path):
class_path = os.path.join(subset_path, class_name)
if os.path.isdir(class_path):
images = [f for f in os.listdir(class_path) if f.endswith('.jpg')]
num_to_remove = int(len(images) * (percentage / 100))
if num_to_remove > 0:
images_to_remove = random.sample(images, num_to_remove)
for img in images_to_remove:
os.remove(os.path.join(class_path, img))
print(f"Removed {num_to_remove} images from {subset}/{class_name}")
# Define base path
base_directory = "classify"
# Run the function
remove_random_images(base_directory) |