updated libraries

model.py

@@ -187,10 +187,6 @@ class TrackImagesCallback(pl.callbacks.base.Callback):
             self.callback_track_images(trainer.model, save_loc)
 
 
-from utils.debug import debug
-
-
-# @debug
 def log_tensor(batch, path, save_tensors=True, nrow=8):
     if save_tensors:
         torch.save(batch, path)

processing/pipeline_torch.py

@@ -10,8 +10,6 @@ from utils.base import np2torch, torch2np
 
 import segmentation_models_pytorch as smp
 
-from utils.debug import debug
-
 K_G = torch.Tensor([[0, 1, 0],
                     [1, 4, 1],
                     [0, 1, 0]]) / 4

train.py

@@ -16,7 +16,6 @@ import pytorch_lightning as pl
 from pytorch_lightning.callbacks import ModelCheckpoint
 
 from utils.base import AuxLoss, WeightedLoss, display_mlflow_run_info, l2_regularization, str2bool, fetch_from_mlflow, get_name, data_loader_mean_and_std
-from utils.debug import debug
 from utils.dataset_utils import k_fold
 from utils.augmentation import get_augmentation
 from dataset import Subset, get_dataset

utils/dataset_utils.py

@@ -1,11 +1,18 @@
+"""
+Dataset Import/Download Tools
+"""
 
+import os
 import random
 import numpy as np
+import rawpy
+from PIL import Image
 
 import torch
 
 from skimage.util.shape import view_as_windows
 
+IMAGE_FILE_TYPES = ['dng', 'png', 'tif', 'tiff']
 
 def load_image(path):
     file_type = path.split('.')[-1].lower()