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# Image colorization
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A UNet architecture, utilizing transfer learning by using a pretrained ResNet-34 as an encoder.
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Try the model on [Colab](https://colab.research.google.com/drive/1JYbSLtDuFSw2NYe-YW-kZHLNkt4-v7jd) or [Huggingface space](https://huggingface.co/spaces/ayushshah/imagecolorization).
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6318256d212fce5a3cde0fe3/To7FVLusBz1kl8g9HhPIf.png" width="800px"/>
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The model takes a 1x224x224 L tensor as input and outputs 2x224x224 ab channels. The decoder has been trained from scratch. The encoder (ResNet-34) was initially frozen for the decoder to adapt to the task, then it was progressively unfreezed layer by layer. Initial layers were not unfreezed, only deeper layers were fine-tuned. Read various research papers. It took 20+ hours of training on Google Colab and Kaggle T4 GPUs to train the model.
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# Image colorization
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A UNet architecture, utilizing transfer learning by using a pretrained ResNet-34 as an encoder.
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Try the model on [Google Colab](https://colab.research.google.com/drive/1JYbSLtDuFSw2NYe-YW-kZHLNkt4-v7jd) or [Huggingface space](https://huggingface.co/spaces/ayushshah/imagecolorization).
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6318256d212fce5a3cde0fe3/To7FVLusBz1kl8g9HhPIf.png" width="800px"/>
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The model takes a 1x224x224 L tensor as input and outputs 2x224x224 ab channels. The decoder has been trained from scratch. The encoder (ResNet-34) was initially frozen for the decoder to adapt to the task, then it was progressively unfreezed layer by layer. Initial layers were not unfreezed, only deeper layers were fine-tuned. Read various research papers. It took 20+ hours of training on Google Colab and Kaggle T4 GPUs to train the model.
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