Update README.md

README.md

@@ -108,7 +108,128 @@ dataset = load_dataset("Maazwaheed/set_SHAPES")
 print(f"Dataset size: {len(dataset['train'])}")
 print(f"Sample caption: {dataset['train'][0]['caption']}")
 ```
-
+### fast load
+```python
+import os
+import logging
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from datasets import load_dataset
+from PIL import Image
+import pandas as pd
+from tqdm import tqdm
+import io
+import threading
+
+# Configuration
+DATASET_NAME = "Maazwaheed/set_SHAPES"
+OUTPUT_DIR = "advanced_motion_dataset"
+IMAGES_DIR = os.path.join(OUTPUT_DIR, "images")
+MAX_WORKERS = 16  # Adjust based on system capabilities
+HF_TOKEN = os.getenv("HF_TOKEN")  # Ensure HF_TOKEN is set in environment
+LOG_DIR = "logs"
+LOG_FILE = os.path.join(LOG_DIR, "download.log")
+
+# Setup logging
+os.makedirs(LOG_DIR, exist_ok=True)
+logging.basicConfig(
+    filename=LOG_FILE,
+    level=logging.INFO,
+    format="%(asctime)s - %(levelname)s - %(message)s"
+)
+
+# Thread-safe counter for tracking downloaded images
+download_counter = 0
+counter_lock = threading.Lock()
+
+def setup_directories():
+    """Create output directories if they don't exist."""
+    try:
+        os.makedirs(OUTPUT_DIR, exist_ok=True)
+        os.makedirs(IMAGES_DIR, exist_ok=True)
+        logging.info(f"Created directories: {OUTPUT_DIR}, {IMAGES_DIR}")
+    except Exception as e:
+        logging.error(f"Failed to create directories: {e}")
+        raise
+
+def download_image(item, index):
+    """Download and save a single image with its filename."""
+    try:
+        image = item["image"]
+        filename = item.get("filename", f"{str(index+1).zfill(5)}.jpg")
+        image_path = os.path.join(IMAGES_DIR, filename)
+
+        # Convert to RGB if needed and save as JPEG
+        if image.mode != "RGB":
+            image = image.convert("RGB")
+        image.save(image_path, "JPEG", quality=95)
+
+        # Increment counter thread-safely
+        global download_counter
+        with counter_lock:
+            download_counter += 1
+
+        return filename, item.get("caption", ""), None
+    except Exception as e:
+        logging.error(f"Failed to download image at index {index}: {e}")
+        return None, None, str(e)
+
+def download_dataset():
+    """Download the dataset efficiently using parallel processing."""
+    try:
+        # Load dataset
+        logging.info(f"Loading dataset: {DATASET_NAME}")
+        dataset = load_dataset(DATASET_NAME, split="train", use_auth_token=HF_TOKEN)
+        logging.info(f"Dataset loaded with {len(dataset)} items")
+
+        # Setup directories
+        setup_directories()
+
+        # Prepare metadata
+        metadata = []
+
+        # Download images in parallel
+        logging.info(f"Starting parallel download with {MAX_WORKERS} workers")
+        with ThreadPoolExecutor(max_workers=MAX_WORKERS) as executor:
+            future_to_index = {executor.submit(download_image, dataset[i], i): i for i in range(len(dataset))}
+            progress_bar = tqdm(total=len(dataset), desc="Downloading images")
+
+            for future in as_completed(future_to_index):
+                index = future_to_index[future]
+                filename, caption, error = future.result()
+                if filename and caption is not None:
+                    metadata.append([filename, caption])
+                else:
+                    logging.warning(f"Skipped item at index {index} due to error: {error}")
+                progress_bar.update(1)
+
+            progress_bar.close()
+
+        # Save captions.csv
+        try:
+            csv_path = os.path.join(OUTPUT_DIR, "captions.csv")
+            with open(csv_path, "w", newline="", encoding="utf-8") as f:
+                writer = pd.DataFrame(metadata, columns=["filename", "caption"])
+                writer.to_csv(f, index=False)
+            logging.info(f"Saved captions to {csv_path}")
+        except Exception as e:
+            logging.error(f"Failed to save captions.csv: {e}")
+            raise
+
+        logging.info(f"Downloaded {download_counter} images to {IMAGES_DIR}")
+        print(f"Dataset downloaded successfully! {download_counter} images saved to {IMAGES_DIR}, captions saved to {csv_path}")
+
+    except Exception as e:
+        logging.error(f"Dataset download failed: {e}")
+        raise
+
+if __name__ == "__main__":
+    try:
+        download_dataset()
+    except Exception as e:
+        print(f"Error downloading dataset: {e}")
+        logging.error(f"Main execution failed: {e}")
+        raise
+```
 ### Advanced Usage
 ```python
 # Filter motion scenes