Python implementation (often using PyTorch or TensorFlow).

Settings for hyperparameters and directory paths used during the "comp" (computation/comparison) phase of the research. Performance and Impact

The architecture uses recurrence to reuse parameters across different stages of the de-raining process, which reduces the model size while improving its ability to handle complex rain patterns.

.pth or .ckpt files that allow users to run the de-rain algorithm without training from scratch.

Instead of attempting to remove all rain in a single step, the model decomposes the rain layer into multiple stages. It progressively removes rain streaks by grouping them based on their physical characteristics.

Code to run the de-rainer on the provided sample "Rain200L" or "Rain200H" datasets.

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Didrpg2emtl_comp.rar (2025)

Python implementation (often using PyTorch or TensorFlow).

Settings for hyperparameters and directory paths used during the "comp" (computation/comparison) phase of the research. Performance and Impact DIDRPG2EMTL_comp.rar

The architecture uses recurrence to reuse parameters across different stages of the de-raining process, which reduces the model size while improving its ability to handle complex rain patterns. Python implementation (often using PyTorch or TensorFlow)

.pth or .ckpt files that allow users to run the de-rain algorithm without training from scratch. DIDRPG2EMTL_comp.rar

Instead of attempting to remove all rain in a single step, the model decomposes the rain layer into multiple stages. It progressively removes rain streaks by grouping them based on their physical characteristics.

Code to run the de-rainer on the provided sample "Rain200L" or "Rain200H" datasets.