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>
58 lines
571 B
Plaintext
58 lines
571 B
Plaintext
# Python
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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.Python
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.pytest_cache/
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.mypy_cache/
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.ruff_cache/
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.venv/
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venv/
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env/
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# PyTorch / ML artefacts
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*.pt
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*.pth
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*.ckpt
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*.onnx
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*.engine
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*.safetensors
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checkpoints/
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nn_models/
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out/
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outputs/
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runs/
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wandb/
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lightning_logs/
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# Data (too large / confidential — keep manifests only if < 10 MB)
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data/
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*.json.gz
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*.h5
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*.hdf5
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*.parquet
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*.npy
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*.npz
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# Gin / config logs
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*.gin.log
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operative_config-*.gin
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# Editors / IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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*~
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.DS_Store
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Thumbs.db
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# Secrets (never commit)
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.env
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.env.*
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*credentials*
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*secret*
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*.pem
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*.key
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