Update main.py

main.py

@@ -371,7 +371,6 @@
 
 
 
-
 import os
 import json
 import torch
@@ -451,11 +450,13 @@ def get_available_videos_from_hf():
         videos = []
         for file in files:
             if file.startswith(f"{HF_DATASET_SUBFOLDER}/") and file.endswith('.npz'):
+                # Extract the full filename without extension
+                # For files like "I3D/OP02-R02-TurkeySandwich.npz"
                 video_name = os.path.basename(file).replace('.npz', '')
                 videos.append(video_name)
         
         videos = sorted(videos)
-        print(f"Found {len(videos)} videos in dataset")
+        print(f"Found {len(videos)} videos in dataset: {videos[:5]}{'...' if len(videos) > 5 else ''}")
         return videos
         
     except Exception as e:
@@ -472,18 +473,31 @@ class HFVideoDataSet(VideoDataSet):
         
         # Create temporary directory for this session
         self.temp_dir = tempfile.mkdtemp(prefix="hf_video_")
-        opt['video_feature_all_test'] = self.temp_dir
         
         # Download the specific video file if video_name is provided
         if video_name:
             try:
+                print(f"Downloading features for video: {video_name}")
                 downloaded_path = download_npz_file(video_name)
+                
+                # Ensure the temp directory exists
+                os.makedirs(self.temp_dir, exist_ok=True)
+                
                 # Copy to temp directory with expected structure
                 temp_file_path = os.path.join(self.temp_dir, f"{video_name}.npz")
                 shutil.copy2(downloaded_path, temp_file_path)
                 print(f"Video file ready: {temp_file_path}")
+                
+                # Verify file exists
+                if not os.path.exists(temp_file_path):
+                    raise Exception(f"Failed to copy file to {temp_file_path}")
+                    
             except Exception as e:
-                print(f"Warning: Could not download video {video_name}: {str(e)}")
+                print(f"Error downloading video {video_name}: {str(e)}")
+                raise e
+        
+        # Set the feature path to our temp directory
+        opt['video_feature_all_test'] = self.temp_dir
         
         # Initialize parent class
         super().__init__(opt, subset, video_name)
@@ -493,8 +507,9 @@ class HFVideoDataSet(VideoDataSet):
         try:
             if hasattr(self, 'temp_dir') and os.path.exists(self.temp_dir):
                 shutil.rmtree(self.temp_dir)
-        except:
-            pass
+                print(f"Cleaned up temp directory: {self.temp_dir}")
+        except Exception as e:
+            print(f"Warning: Could not clean up temp directory: {e}")
 
 def eval_frame(opt, model, dataset):
     """Evaluate model frame by frame"""
@@ -635,6 +650,9 @@ def load_ground_truth(opt, video_name):
 def process_video(video_name, split_number, progress=gr.Progress()):
     """Process a single video for action localization"""
     try:
+        if not video_name or video_name in ["Error: Could not load videos from HF dataset", "Error loading videos"]:
+            return "Error: Please select a valid video name"
+            
         progress(0.1, desc="Initializing...")
         
         # Parse options
@@ -680,10 +698,13 @@ def process_video(video_name, split_number, progress=gr.Progress()):
         progress(0.4, desc=f"Downloading video features for {video_name}...")
         
         # Create dataset with HF integration
-        dataset = HFVideoDataSet(opt, subset='test', video_name=video_name)
+        try:
+            dataset = HFVideoDataSet(opt, subset='test', video_name=video_name)
+        except Exception as e:
+            return f"Error downloading or loading video '{video_name}': {str(e)}\n\nPlease check:\n1. Video name is correct\n2. File exists in HF dataset\n3. Network connection is stable"
         
         if len(dataset.video_list) == 0:
-            return f"Error: No video found with name '{video_name}' in dataset or failed to download"
+            return f"Error: No video found with name '{video_name}' in dataset after download"
         
         progress(0.6, desc="Running inference...")
         
@@ -778,7 +799,9 @@ def process_video(video_name, split_number, progress=gr.Progress()):
         return output_text
         
     except Exception as e:
-        return f"Error processing video: {str(e)}\n\nPlease check:\n1. Model checkpoint exists\n2. Video exists in HF dataset\n3. All dependencies are installed"
+        import traceback
+        error_details = traceback.format_exc()
+        return f"Error processing video: {str(e)}\n\nDetailed error:\n{error_details}\n\nPlease check:\n1. Model checkpoint exists\n2. Video exists in HF dataset\n3. All dependencies are installed"
 
 def refresh_video_list():
     """Refresh the list of available videos"""