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README.md

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+
+---
+language: en
+tags:
+- image-processing
+- image-denoising
+- deep-learning
+license: apache-2.0
+model_name: Image Denoising Model
+---
+
+# RIDNet Model 
+
+This Repo contains the weights and config of RIDNet Model that can be used for image denoising.
+
+# Datasets
+
+- LOL Dataset
+- Smartphone Image Denoising Dataset
+
+# References
+https://arxiv.org/pdf/1904.07396v2.pdf
+

config.json

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+{"architecture": "RIDNet", "input_channels": 3, "output_channels": 3, "num_features": 64, "layers": [{"type": "Conv2d", "in_channels": 3, "out_channels": 64, "kernel_size": [3, 3], "stride": 1, "padding": 1}, {"type": "ReLU", "inplace": false}, {"type": "EAM", "in_channels": 64, "out_channels": 64}, {"type": "EAM", "in_channels": 64, "out_channels": 64}, {"type": "EAM", "in_channels": 64, "out_channels": 64}, {"type": "EAM", "in_channels": 64, "out_channels": 64}, {"type": "Conv2d", "in_channels": 64, "out_channels": 3, "kernel_size": [3, 3], "stride": 1, "padding": 1, "dilation": 1}], "skip_connections": [{"type": "long", "from": "input", "to": "eam1"}, {"type": "long", "from": "input", "to": "output"}], "initialization": {"Conv2d": "xavier_uniform", "BatchNorm2d": {"weight": 1, "bias": 0}}}

pytorch_model.bin

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