-
./model
- block.py
- define the encoder(now only resnet50), mff, decoder and refinement block, which are modules of the model
- model.py
- define the model, utilizing the blocks in block.py
- resnet_module.py
- self-defined resnet for encoding blocks
- credit to https://github.com/JunjH/
- self-defined resnet for encoding blocks
- block.py
-
nyu2_train
- only part of the dataset, used to check whether the code is runnable
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load_data.py
- load the data by making pairs of path, the output is a list of pair [x_tr_path, y_tr_path]
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loss.py
- define the gradient computation and loss computation
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utils.py
- currently, only loading and saving the params of model is defined
-
train.py
- define the training procedure
-
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Res-Unet for Depth Estimation
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