TODO: Add random sampling to patch-based training

Added note for future enhancement: mix salient + random samples.

Rationale:
- Salient point detection focuses on edges/corners
- Random samples improve generalization across entire image
- Prevents overfitting to only high-gradient regions

Proposed implementation:
- Default: 90% salient points, 10% random samples
- Configurable: --random-sample-percent parameter
- Example: 64 patches = 58 salient + 6 random

Location: train_cnn_v2.py
- TODO in _detect_salient_points() method
- TODO in argument parser

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

1 files changed, 11 insertions, 1 deletions

diff --git a/training/train_cnn_v2.py b/training/train_cnn_v2.py
index 3ab1c0f..5c93f20 100755
--- a/training/train_cnn_v2.py
+++ b/training/train_cnn_v2.py
@@ -120,7 +120,15 @@ class PatchDataset(Dataset):
         return len(self.input_paths) * self.patches_per_image
 
     def _detect_salient_points(self, img_array):
-        """Detect salient points on original image."""
+        """Detect salient points on original image.
+
+        TODO: Add random sampling to training vectors
+        - In addition to salient points, incorporate randomly-located samples
+        - Default: 10% random samples, 90% salient points
+        - Prevents overfitting to only high-gradient regions
+        - Improves generalization across entire image
+        - Configurable via --random-sample-percent parameter
+        """
         gray = cv2.cvtColor((img_array * 255).astype(np.uint8), cv2.COLOR_RGB2GRAY)
         h, w = gray.shape
         half_patch = self.patch_size // 2
@@ -342,6 +350,8 @@ def main():
     parser.add_argument('--detector', type=str, default='harris',
                         choices=['harris', 'fast', 'shi-tomasi', 'gradient'],
                         help='Patch mode: salient point detector (default: harris)')
+    # TODO: Add --random-sample-percent parameter (default: 10)
+    # Mix salient points with random samples for better generalization
 
     # Model architecture
     parser.add_argument('--kernel-sizes', type=int, nargs=3, default=[1, 3, 5],