Merge branch 'main' of https://github.com/Arshad221b/NeRF-from-scratch

Author: Arshad221b

README.md

@@ -54,7 +54,7 @@ python source/train.py
 Training parameters:
 - Learning rate: 1e-4 with exponential decay (gamma=0.995)
 - Batch size: 1 (processes multiple rays per batch)
-- Number of epochs: 200
+- Number of epochs: 200 * 2 (trainning best checkpoint again for 200 epochs)
 - Positional encoding frequencies: 10 (positions), 4 (directions)
 - Network size: 256 hidden units
 
@@ -174,8 +174,8 @@ nerf_synthetic/
 
 This implementation has been tested on:
 - NVIDIA T4 GPU
-- Training time: ~3 hours for 200 epochs on the chair dataset
-- Inference time: ~2-3 minutes for rendering a complete 360° view
+- Training time: ~3 hours for 200 epochs on the chair dataset (for 400 epochs, took around 5-6 hrs)
+- Inference time: ~2-3 seconds/image for rendering a complete 360° view
 
 Note: Performance can vary based on:
 - Scene complexity