Update code.txt

code.txt

@@ -1,56 +1,59 @@
 import os
+import random
 import shutil
-from concurrent.futures import ThreadPoolExecutor, as_completed
-
-# Function to copy images to respective folders based on their labels
-def copy_image(file_info):
-    src, dst_folder = file_info
-    dst = os.path.join(dst_folder, os.path.basename(src))
-    try:
-        shutil.copy2(src, dst)  # Copy file to destination folder
-    except Exception as e:
-        print(f"Error copying {src}: {e}")
-
-# Function to organize images into good and bad folders
-def organize_images(image_folder, labels, destination_folder, num_threads=100):
-    # Create destination directories if they don't exist
-    good_folder = os.path.join(destination_folder, 'good')
-    bad_folder = os.path.join(destination_folder, 'bad')
-    os.makedirs(good_folder, exist_ok=True)
-    os.makedirs(bad_folder, exist_ok=True)
-
-    file_info_list = []
-    
-    # Iterate over the labels and create file_info for each image
-    for image_name, label in labels.items():
-        src = os.path.join(image_folder, image_name)
-        if label == "good":
-            dst_folder = good_folder
-        else:
-            dst_folder = bad_folder
-        
-        file_info_list.append((src, dst_folder))
-    
-    # Use ThreadPoolExecutor to copy files in parallel
+from concurrent.futures import ThreadPoolExecutor
+
+# Define paths
+dataset_folder = 'path/to/dataset'
+train_folder = os.path.join(dataset_folder, 'train')
+val_folder = os.path.join(dataset_folder, 'validation')
+
+# Create validation folder if it doesn't exist
+os.makedirs(val_folder, exist_ok=True)
+
+# Get all label folders inside train folder
+label_folders = [f for f in os.listdir(train_folder) if os.path.isdir(os.path.join(train_folder, f))]
+
+# Function to move images from a specific label folder
+def process_label_folder(label_folder, num_threads):
+    train_label_folder = os.path.join(train_folder, label_folder)
+    val_label_folder = os.path.join(val_folder, label_folder)
+
+    # Create corresponding validation label folder
+    os.makedirs(val_label_folder, exist_ok=True)
+
+    # Get all images in the train/label_folder
+    all_images = os.listdir(train_label_folder)
+    total_images = len(all_images)
+
+    # Calculate 20% of images for validation
+    val_size = int(total_images * 0.2)
+
+    # Randomly select 20% of the images for validation
+    val_images = random.sample(all_images, val_size)
+
+    # Function to move a single image
+    def move_image(image):
+        src = os.path.join(train_label_folder, image)
+        dest = os.path.join(val_label_folder, image)
+        shutil.move(src, dest)
+
+    # Use ThreadPoolExecutor to move images in parallel
     with ThreadPoolExecutor(max_workers=num_threads) as executor:
-        futures = [executor.submit(copy_image, file_info) for file_info in file_info_list]
-        
-        # Optional: Track the progress
-        for future in as_completed(futures):
-            future.result()  # Wait for all threads to complete
+        executor.map(move_image, val_images)
+
+    print(f"Moved {val_size} images from {label_folder} to validation folder.")
+
+# Main function to get user input for number of threads and process folders
+def main():
+    # Ask user for the number of threads
+    num_threads = int(input("Enter the number of threads to use: "))
+
+    # Process each label folder using the input number of threads
+    for label_folder in label_folders:
+        process_label_folder(label_folder, num_threads)
+
+    print("Validation dataset created.")
 
 if __name__ == "__main__":
-    # Define your image folder and destination folder
-    image_folder = "/path/to/your/image_folder"
-    destination_folder = "/path/to/your/destination_folder"
-    
-    # Your labels dictionary (image_name: label)
-    labels = {
-        "image1.jpg": "good",
-        "image2.jpg": "bad",
-        "image3.jpg": "good",
-        # Add the rest of your image labels here (1M entries)
-    }
-
-    # Organize images using 100 threads
-    organize_images(image_folder, labels, destination_folder, num_threads=100)
+    main()