Learnable Test Time Augmentation (TTA) in PyTorch (Code + Evaluation)

Описание: In this tutorial, we’ll explore how to enhance image segmentation performance during inference using Learnable Test Time Augmentation (Learnable TTA). Unlike Traditional TTA, which blindly averages predictions from augmented views, Learnable TTA uses a small trainable module to intelligently combine outputs — resulting in significantly improved accuracy and smarter model behavior.

📌 We’ll be using a pre-trained U-Net model in PyTorch and evaluating it on a multi-class weed segmentation dataset. The results show how Learnable TTA can deliver better segmentation masks without changing the model or retraining on new data.

This technique is especially useful in high-stakes domains like medical imaging, agriculture, and autonomous driving, where prediction confidence and clarity matter.

⏱️ Timestamps:
00:00 - Introduction
00:15 - What is Test Time Augmentation (TTA)?
00:43 - Limitations of Traditional TTA
01:25 - What is Learnable TTA?
02:03 - Performance Comparison
03:27 - Implementing Learnable TTA with PyTorch
04:50 - Image & Mask Processing
07:41 - Apply Augmentations & Make Predictions
09:14 - Building a Learnable TTA Module
11:00 - Training Learnable TTA on Validation Set
13:38 - Evaluating Results: Traditional vs Learnable
17"09 - Execution of the Program
20:04 - Visualizing Predictions and Accuracy Boost
21:19 - Final Thoughts

📘 In this video, you’ll learn:
What is Test Time Augmentation, and how does it work
Why Traditional TTA has limitations
How to design and train a Learnable TTA module
Combine multiple predictions more intelligently
Visualize and compare segmentation improvements
Analyze performance using F1 Score and IoU

💡 Smarter Fusion = Better Segmentation!

🔗 GitHub Repo: https://github.com/nikhilroxtomar/Mul...
📸 Dataset: https://figshare.com/articles/dataset...

🎥 Related Videos:
Multiclass Image Segmentation in PyTorch:    • Multiclass Image Segmentation in PyTorch |...  
Implementing GradCAM on UNet with PyTorch for Multi-Class Segmentation:    • Implementing GradCAM on UNet with PyTorch ...  
Test Time Augmentation in Segmentation (TTA):    • Test Time Augmentation(TTA) for Multiclass...  

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