caption-test

Pikaliov/caption-test

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Author	SHA1	Message	Date
pikaliov	29a09349e7	Add ML diagnostics tooling (W&B, TensorBoard, Grad-CAM, profiler) and gin configs - Add unified experiment tracker (W&B + TensorBoard) with graceful fallback - Add gradient norm monitoring per param group (MONA, LoRA, MLP, gates, tau) - Add Grad-CAM visualization for DINOv3 drone/satellite encoders - Add PyTorch Profiler wrapper + torchinfo model summary - Add gin-config support to train_gtauav.py with CLI overrides - Add v3 gin configs: gtauav_balanced, gtauav_baseline, gtauav_text_heavy, gtauav_image_heavy - Generate metric plots every epoch (not just on eval) - Set default epochs to 10 - Update README and CLAUDE.md with new tooling and usage docs Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-04-21 20:30:50 +03:00
pikaliov	abb3337f8d	Rewrite: GatedFusion architecture + UAV-GeoLoc dataset Architecture v2: - Query branch: drone + text -> GatedFusion -> proj -> query_emb - Gallery branch: satellite -> proj -> gallery_emb - Single InfoNCE loss (asymmetric 0.6/0.4) - GatedFusion: learnable gated addition (sigma(alpha)img + (1-sigma(alpha))text) - Baseline mode: gate=1.0 (text ignored) Dataset: - UAV-GeoLoc loader with template captions from path metadata - 27 terrain types with predefined features - Random positive crop sampling per epoch Configs: balanced (gate=0.7), baseline (no text), text_heavy (gate=0.3) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	2026-04-17 17:13:00 +03:00
Pikaliov	2ce4017ebd	Initial commit: caption quality test on UAV-VisLoc Self-contained experimental track validating generated text captions via retrieval R@1 lift on UAV-VisLoc. Architecture: GeoRSCLIP ViT-B/32 dual encoder, 512-dim shared space. Loss: 4-term InfoNCE (img-img + sat-cap + drone-cap + cap-cap) with cosine temperature decay, PALW-like curriculum. Metric: delta R@1 (with text - without text) >= +3% => PASS. Gin-configured (balanced / baseline_no_text / text_heavy variants). Follows NADEZHDA code style. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-17 00:04:46 +03:00

Author

SHA1

Message

Date

pikaliov

29a09349e7

Add ML diagnostics tooling (W&B, TensorBoard, Grad-CAM, profiler) and gin configs

- Add unified experiment tracker (W&B + TensorBoard) with graceful fallback
- Add gradient norm monitoring per param group (MONA, LoRA, MLP, gates, tau)
- Add Grad-CAM visualization for DINOv3 drone/satellite encoders
- Add PyTorch Profiler wrapper + torchinfo model summary
- Add gin-config support to train_gtauav.py with CLI overrides
- Add v3 gin configs: gtauav_balanced, gtauav_baseline, gtauav_text_heavy, gtauav_image_heavy
- Generate metric plots every epoch (not just on eval)
- Set default epochs to 10
- Update README and CLAUDE.md with new tooling and usage docs

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-21 20:30:50 +03:00

pikaliov

abb3337f8d

Rewrite: GatedFusion architecture + UAV-GeoLoc dataset

Architecture v2:
- Query branch: drone + text -> GatedFusion -> proj -> query_emb
- Gallery branch: satellite -> proj -> gallery_emb
- Single InfoNCE loss (asymmetric 0.6/0.4)
- GatedFusion: learnable gated addition (sigma(alpha)*img + (1-sigma(alpha))*text)
- Baseline mode: gate=1.0 (text ignored)

Dataset:
- UAV-GeoLoc loader with template captions from path metadata
- 27 terrain types with predefined features
- Random positive crop sampling per epoch

Configs: balanced (gate=0.7), baseline (no text), text_heavy (gate=0.3)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-17 17:13:00 +03:00

Pikaliov

2ce4017ebd

Initial commit: caption quality test on UAV-VisLoc

Self-contained experimental track validating generated text captions
via retrieval R@1 lift on UAV-VisLoc.

Architecture: GeoRSCLIP ViT-B/32 dual encoder, 512-dim shared space.
Loss: 4-term InfoNCE (img-img + sat-cap + drone-cap + cap-cap)
      with cosine temperature decay, PALW-like curriculum.
Metric: delta R@1 (with text - without text) >= +3% => PASS.

Gin-configured (balanced / baseline_no_text / text_heavy variants).
Follows NADEZHDA code style.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-04-17 00:04:46 +03:00

3 Commits