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>
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conf/text_heavy.gin
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conf/text_heavy.gin
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# Text-heavy configuration — stress test of caption contribution.
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# L = 0.5 * L_img_img + 0.5 * L_sat_cap + 0.5 * L_drone_cap + 0.2 * L_cap_cap
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include 'balanced.gin'
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MultiTermInfoNCE.lambda_ii = 0.5
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MultiTermInfoNCE.lambda_sc_max = 0.5
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MultiTermInfoNCE.lambda_dc_max = 0.5
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MultiTermInfoNCE.lambda_cc_max = 0.2
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TrainConfig.output_dir = "out/caption_test/text_heavy"
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