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Caltech-101/create_csv.py

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+import os
+import csv
+
+def generate_csv(dataset_path, csv_filename):
+    # Define the columns of the CSV file
+    columns = ['id', 'path', 'label']
+    
+    # Initialize a list to hold the rows for the CSV
+    rows = []
+
+    # Function to process a directory
+    def process_directory(directory, label):
+        for root, _, files in os.walk(directory):
+            for filename in files:
+                if filename.endswith(('.jpg', '.jpeg', '.png')):  # Add other image extensions if needed
+                    file_id = os.path.splitext(filename)[0]
+                    file_path = os.path.join(root, filename)
+                    rows.append([file_id, file_path, label])
+
+    # Process train and test directories
+    for subdir in ['train']:
+        subdir_path = os.path.join(dataset_path, subdir)
+        if os.path.isdir(subdir_path):
+            for label in os.listdir(subdir_path):
+                label_path = os.path.join(subdir_path, label)
+                if os.path.isdir(label_path):
+                    process_directory(label_path, label)
+
+    # Write the collected data to a CSV file
+    csv_path = os.path.join(dataset_path, csv_filename)
+    with open(csv_path, mode='w', newline='') as file:
+        writer = csv.writer(file)
+        writer.writerow(columns)  # Write the header
+        writer.writerows(rows)    # Write the rows
+
+# Example usage
+dataset_path = '.'  # Replace with the actual path to the dataset folder
+csv_filename = 'image_search.csv'
+generate_csv(dataset_path, csv_filename)