Upload upload_to_hf.py with huggingface_hub

upload_to_hf.py

@@ -0,0 +1,60 @@
+from huggingface_hub import HfApi
+import os
+from pathlib import Path
+
+def upload_dataset_to_hf():
+    # Configuration
+    dataset_name = "cv_proj"  #  Replace with your dataset name
+    username = "Sean676"  # Replace with your Hugging Face username
+    repo_id = f"{username}/{dataset_name}"
+    
+    # Initialize API
+    api = HfApi()
+    
+    # Create dataset repository
+    try:
+        repo_url = api.create_repo(
+            repo_id=repo_id,
+            repo_type="dataset",
+            private=False,  # Set to True if you want private dataset
+            exist_ok=True
+        )
+        print(f"Repository created/verified: {repo_url}")
+    except Exception as e:
+        print(f"Error creating repository: {e}")
+        print("Please check:")
+        print("1. You are logged in with correct token")
+        print("2. Your username 'ys' is correct")
+        print("3. You have permission to create datasets")
+        return
+    
+    # Upload files
+    dataset_path = Path(".")
+    files_to_upload = []
+    
+    # Add all files recursively
+    for file_path in dataset_path.rglob("*"):
+        if file_path.is_file() and not file_path.name.startswith('.'):
+            files_to_upload.append(str(file_path))
+    
+    # Upload each file
+    for file_path in files_to_upload:
+        try:
+            # Get relative path
+            rel_path = os.path.relpath(file_path, dataset_path)
+            
+            # Upload file
+            api.upload_file(
+                path_or_fileobj=file_path,
+                path_in_repo=rel_path,
+                repo_id=repo_id,
+                repo_type="dataset"
+            )
+            print(f"Uploaded: {rel_path}")
+        except Exception as e:
+            print(f"Failed to upload {file_path}: {e}")
+    
+    print("Upload completed!")
+
+if __name__ == "__main__":
+    upload_dataset_to_hf()