Merge branch 'main' of https://huggingface.co/datasets/BGLab/FlowBench

README.md

@@ -73,32 +73,25 @@ pip install huggingface_hub
 The following script demonstrates how to download a directory from the Hugging Face Hub:
 
 ```python 
-from huggingface_hub import HfApi, hf_hub_download
-import os
-import shutil
+from huggingface_hub import login, snapshot_download
 
-REPO_ID = "BGLab/FlowBench"
-DIRECTORY = "LDC_NS_2D"
+# Hugging Face access token (replace with your token)
+hf_token = ""
 
-# Initialize the Hugging Face API
-api = HfApi()
+# Login to Hugging Face using the token
+print("Logging into Hugging Face...")
+login(token=hf_token)
 
-# List files in the directory
-files_list = api.list_repo_files(repo_id=REPO_ID, repo_type="dataset")
+# Specify repository and folder details
+repo_id = "BGLab/FlowBench"  # Repository ID on Hugging Face
+dataset_path = "FPO_NS_2D_1024x256"  # Folder path within the repository
+output_dir = "./downloaded_folder"  # Local directory to save the folder
 
-# Filter the files in the specified directory
-files_to_download = [f for f in files_list if f.startswith(DIRECTORY)]
+# Download the entire repository or specific folder
+print(f"Downloading folder '{dataset_path}' from repository '{repo_id}'...")
+snapshot_download(repo_id, repo_type="dataset", local_dir=output_dir, allow_patterns=[f"{dataset_path}/*"])
 
-# Create local directory if it doesn't exist
-os.makedirs(DIRECTORY, exist_ok=True)
-
-# Download each file
-for file in files_to_download:
-    file_path = hf_hub_download(repo_id=REPO_ID, filename=file, repo_type="dataset")
-    # Copy the file to the local directory using shutil.copy2
-    shutil.copy2(file_path, os.path.join(DIRECTORY, os.path.basename(file_path)))
-
-print("Files downloaded successfully.")
+print(f"Folder downloaded successfully to {output_dir}!")
 
 ```