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download_coil100-binary.py

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+import os
+import zipfile
+import requests
+import argparse
+from huggingface_hub import HfApi
+
+# Parameters
+repo_id = "dappu97/Coil100-Augmented/coil-100-augmented-binary"  # Replace with your Hugging Face repo ID
+temp_zip_folder = "./temp_zips"  # Temporary folder to store downloaded ZIPs
+
+
+
+# Initialize Hugging Face API
+api = HfApi()
+
+# Step 1: List and download all ZIP files from the Hugging Face repository
+def download_zip_files(repo_id, temp_zip_folder):
+    files = api.list_repo_files(repo_id, repo_type="dataset")
+    zip_files = [file for file in files if file.endswith(".zip")]
+
+    for zip_file in zip_files:
+        url = f"https://huggingface.co/datasets/{repo_id}/resolve/main/{zip_file}"
+        local_path = os.path.join(temp_zip_folder, zip_file)
+        os.makedirs(os.path.dirname(local_path), exist_ok=True)
+        print(f"Downloading {zip_file}...")
+        response = requests.get(url, stream=True)
+        if response.status_code == 200:
+            with open(local_path, "wb") as f:
+                f.write(response.content)
+            print(f"Downloaded {zip_file} to {local_path}.")
+        else:
+            print(f"Failed to download {zip_file}. HTTP status code: {response.status_code}")
+
+# Step 2: Extract all ZIP files and save images in a single folder
+def extract_zip_files(temp_zip_folder, output_folder):
+    os.makedirs(temp_zip_folder, exist_ok=True)
+
+    for zip_file in os.listdir(temp_zip_folder):
+
+        zip_path = os.path.join(temp_zip_folder, zip_file)
+        if not zipfile.is_zipfile(zip_path):
+            continue  # Skip non-ZIP files
+
+        print(f"Extracting {zip_file}...")
+        with zipfile.ZipFile(zip_path, "r") as z:
+            for file_name in z.namelist():
+                # Extract only files (skip directories)
+                if not file_name.endswith("/"):
+                    file_data = z.read(file_name)
+                    output_path = os.path.join(output_folder, os.path.basename(file_name))
+                    with open(output_path, "wb") as f:
+                        f.write(file_data)
+
+
+if __name__ == '__main__':
+
+    parser = argparse.ArgumentParser(description="Download and unzip ZIP files from a Hugging Face dataset.")
+    parser.add_argument("output_folder", help="Path to the folder where extracted files will be saved.")
+    args = parser.parse_args()
+
+    # Folder to save all images
+    output_folder = args.output_folder
+
+    # Create output directories
+    os.makedirs(output_folder, exist_ok=True)
+    os.makedirs(temp_zip_folder, exist_ok=True)
+
+
+    # Download and extract the dataset
+    download_zip_files(repo_id, temp_zip_folder)
+    extract_zip_files(os.path.join(temp_zip_folder, "coil-100-augmented-binary"), output_folder)
+
+    print(f"All images have been saved to {output_folder}.")

download_coil100.py

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+
+
+
+
+
+
+
+import os
+import zipfile
+import requests
+import argparse
+from huggingface_hub import HfApi
+
+# Parameters
+repo_id = "dappu97/Coil100-Augmented/coil-100-augmented"  # Replace with your Hugging Face repo ID
+temp_zip_folder = "./temp_zips"  # Temporary folder to store downloaded ZIPs
+
+
+
+# Initialize Hugging Face API
+api = HfApi()
+
+# Step 1: List and download all ZIP files from the Hugging Face repository
+def download_zip_files(repo_id, temp_zip_folder):
+    files = api.list_repo_files(repo_id, repo_type="dataset")
+    zip_files = [file for file in files if file.endswith(".zip")]
+
+    for zip_file in zip_files:
+        url = f"https://huggingface.co/datasets/{repo_id}/resolve/main/{zip_file}"
+        local_path = os.path.join(temp_zip_folder, zip_file)
+        os.makedirs(os.path.dirname(local_path), exist_ok=True)
+        print(f"Downloading {zip_file}...")
+        response = requests.get(url, stream=True)
+        if response.status_code == 200:
+            with open(local_path, "wb") as f:
+                f.write(response.content)
+            print(f"Downloaded {zip_file} to {local_path}.")
+        else:
+            print(f"Failed to download {zip_file}. HTTP status code: {response.status_code}")
+
+# Step 2: Extract all ZIP files and save images in a single folder
+def extract_zip_files(temp_zip_folder, output_folder):
+    os.makedirs(temp_zip_folder, exist_ok=True)
+
+    for zip_file in os.listdir(temp_zip_folder):
+
+        zip_path = os.path.join(temp_zip_folder, zip_file)
+        if not zipfile.is_zipfile(zip_path):
+            continue  # Skip non-ZIP files
+
+        print(f"Extracting {zip_file}...")
+        with zipfile.ZipFile(zip_path, "r") as z:
+            for file_name in z.namelist():
+                # Extract only files (skip directories)
+                if not file_name.endswith("/"):
+                    file_data = z.read(file_name)
+                    output_path = os.path.join(output_folder, os.path.basename(file_name))
+                    with open(output_path, "wb") as f:
+                        f.write(file_data)
+
+
+if __name__ == '__main__':
+
+    parser = argparse.ArgumentParser(description="Download and unzip ZIP files from a Hugging Face dataset.")
+    parser.add_argument("output_folder", help="Path to the folder where extracted files will be saved.")
+    args = parser.parse_args()
+
+    # Folder to save all images
+    output_folder = args.output_folder
+
+    # Create output directories
+    os.makedirs(output_folder, exist_ok=True)
+    os.makedirs(temp_zip_folder, exist_ok=True)
+
+
+    # Download and extract the dataset
+    download_zip_files(repo_id, temp_zip_folder)
+    extract_zip_files(os.path.join(temp_zip_folder, "coil-100-augmented"), output_folder)
+
+    print(f"All images have been saved to {output_folder}.")