6ad9c4d149
V3 architecture for CVGL caption validation on GTA-UAV-LR dataset: - AsymmetricEncoder: DINOv3 ViT-L/16 (LVD drone + SAT satellite, frozen) + LRSCLIP/DGTRS-CLIP ViT-L-14 text encoder (248 tok, partial unfreeze) - L1/L2/L3 hierarchical captions from VLM-generated descriptions - TextFusionMLP (concat 3x768 -> MLP -> 512) + GatedFusion - Segmentation filter: exclude images with >=90% background+water - 10.9M trainable / 733M total params, 256x256 input - coloredlogs + tqdm + emoji for training UX - Baseline mode (--baseline): image-only, no text encoder loaded Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
8 lines
212 B
Python
8 lines
212 B
Python
"""Dataset loaders for caption quality test."""
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from src.datasets.visloc_with_captions import (
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GeoLocCaptionDataset,
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collate_caption_batch,
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)
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__all__ = ["GeoLocCaptionDataset", "collate_caption_batch"]
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