diff --git a/TROUBLESHOOTING.md b/TROUBLESHOOTING.md new file mode 100644 index 0000000..9410542 --- /dev/null +++ b/TROUBLESHOOTING.md @@ -0,0 +1,79 @@ +# Troubleshooting Guide + +## āŒ "Sizes of tensors must match" Error + +If you're getting this error: +``` +Error in object detection: Sizes of tensors must match except in dimension 0. Expected size 732 but got size 450 for tensor number 1 in the list. +``` + +### šŸ”§ Solution Steps: + +#### 1. **Restart ComfyUI** (Most Important) +ComfyUI needs to be completely restarted to load updated custom nodes: +- Close ComfyUI completely +- Restart ComfyUI +- Load your workflow again + +#### 2. **Update from GitHub** +Make sure you have the latest version: +```bash +cd ComfyUI/custom_nodes/ComfyUI_Detection_List +git pull origin main +``` + +#### 3. **Check Debug Output** +After restarting, you should see these debug messages in the console: +``` +YOLOv8 Detection: Model inference complete +YOLOv8 Detection: Found X objects, resizing to (width, height) +Object 1 tensor shape: torch.Size([1, height, width, 3]) +Object 2 tensor shape: torch.Size([1, height, width, 3]) +Successfully created batch tensor with shape: torch.Size([X, height, width, 3]) +``` + +If you **don't see these messages**, ComfyUI is still using the old version. + +#### 4. **Manual Reload** (Alternative) +If restarting doesn't work, try: +```bash +cd ComfyUI/custom_nodes/ComfyUI_Detection_List +python reload_node.py +``` + +### šŸŽÆ What Was Fixed: + +- **Tensor Standardization**: All cropped objects are now resized to the same dimensions +- **Shape Verification**: Added checks to ensure all tensors match before concatenating +- **Fallback Handling**: If concatenation still fails, returns single object instead of crashing +- **Debug Logging**: Added detailed console output to track the process + +### šŸ” Verification: + +The node is working correctly when you see: +1. āœ… Objects detected (e.g., "1 person, 1 tie") +2. āœ… Debug messages showing tensor shapes +3. āœ… "Successfully created batch tensor" message +4. āœ… Multiple images output in the batch + +### šŸš« Common Issues: + +1. **Old Node Version**: ComfyUI not restarted after update +2. **Installation Issues**: Node not properly installed in custom_nodes folder +3. **Dependencies**: Missing ultralytics or torch packages + +### šŸ“ž Still Having Issues? + +1. Check the [GitHub Issues](https://github.com/mangobyed/ComfyUI_Detection_List/issues) +2. Create a new issue with: + - ComfyUI console output + - Your workflow JSON + - Python/ComfyUI versions + - Full error message + +### šŸ’” Pro Tips: + +- Always restart ComfyUI after updating custom nodes +- Use lower confidence thresholds (0.1-0.3) to detect more objects +- Increase max_size parameter for higher quality crops +- Check console output for debug information diff --git a/reload_node.py b/reload_node.py new file mode 100644 index 0000000..fe2df01 --- /dev/null +++ b/reload_node.py @@ -0,0 +1,42 @@ +#!/usr/bin/env python3 +""" +Simple script to help reload the YOLOv8 detection node in ComfyUI +Run this script after making changes to the node code. +""" + +import importlib +import sys +import os + +def reload_node(): + """Attempt to reload the YOLOv8 detection node""" + try: + # Add current directory to Python path + current_dir = os.path.dirname(os.path.abspath(__file__)) + if current_dir not in sys.path: + sys.path.insert(0, current_dir) + + # Try to reload the module + module_name = 'yolov8_object_detection_node' + if module_name in sys.modules: + print(f"Reloading {module_name}...") + importlib.reload(sys.modules[module_name]) + print("āœ… Module reloaded successfully!") + else: + print(f"Module {module_name} not found in sys.modules") + print("Available modules:", [m for m in sys.modules.keys() if 'yolo' in m.lower()]) + + # Also try reloading the main init module + init_module = '__init__' + if init_module in sys.modules: + importlib.reload(sys.modules[init_module]) + print("āœ… Init module reloaded!") + + except Exception as e: + print(f"āŒ Error reloading module: {e}") + print("You may need to restart ComfyUI to load the updated node.") + +if __name__ == "__main__": + print("šŸ”„ Attempting to reload YOLOv8 detection node...") + reload_node() + print("\nšŸ“ If this doesn't work, please restart ComfyUI completely.") diff --git a/yolov8_object_detection_node.py b/yolov8_object_detection_node.py index d965d7c..f776b00 100644 --- a/yolov8_object_detection_node.py +++ b/yolov8_object_detection_node.py @@ -189,12 +189,34 @@ class YOLOv8ObjectDetectionNode: print(f"YOLOv8 Detection: Found {len(cropped_objects)} objects, resizing to {target_size}") # Second pass: resize all objects to the same size and convert to tensors - for cropped_object in cropped_objects: + for i, cropped_object in enumerate(cropped_objects): object_tensor = self.pil_to_tensor(cropped_object, target_size) + print(f"Object {i+1} tensor shape: {object_tensor.shape}") detected_images.append(object_tensor) + # Verify all tensors have the same shape before concatenating + if len(detected_images) > 1: + first_shape = detected_images[0].shape + for i, tensor in enumerate(detected_images): + if tensor.shape != first_shape: + print(f"WARNING: Tensor {i} shape mismatch: {tensor.shape} vs expected {first_shape}") + # Force resize the tensor to match + detected_images[i] = torch.nn.functional.interpolate( + tensor.permute(0, 3, 1, 2), + size=(first_shape[1], first_shape[2]), + mode='bilinear', + align_corners=False + ).permute(0, 2, 3, 1) + # Concatenate all detected objects into a batch - batch_tensor = torch.cat(detected_images, dim=0) + try: + batch_tensor = torch.cat(detected_images, dim=0) + print(f"Successfully created batch tensor with shape: {batch_tensor.shape}") + except Exception as cat_error: + print(f"Error concatenating tensors: {cat_error}") + # Fallback: return first detected object only + batch_tensor = detected_images[0] + print(f"Fallback: returning single object with shape: {batch_tensor.shape}") class_names_str = ", ".join(class_names) detection_info_str = "; ".join(detection_info_list) object_count = len(detected_images)