POSEatSea β€” model weights

Weights for the POSEatSea maritime oil-spill detection and vessel attribution console (SIH Problem Statement 26143, NTRO).

File Architecture Notes
best_sar_model.pth U-Net + MiT-B2 encoder, 5 classes Expects 512Γ—512 input. See caveat below.
trajectory_lstm_baseline.pth LSTM(6β†’128)Γ—2 + Linear(128β†’2) Mauritius AOI, ~60 s ping cadence
ais_phase1_autoencoder.pth Autoencoder 11β†’16β†’8β†’4β†’8β†’16β†’11 Threshold 1.104481
ais_phase1_scaler.joblib StandardScaler, 11 features Mandatory β€” the model returns nonsense on unscaled input

Code: https://github.com/23f2003521/SIH2026

SAR checkpoint

Expects 512x512 input. Running inference at another resolution does not degrade gracefully -- it returns incoherent noise.

An earlier export of this file carried a trained encoder with an untrained decoder and head, and emitted noise on every input. The current file is trained through (BatchNorm num_batches_tracked = 7530) and reproduces the reference outputs at 0.81 oil IoU.

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