Clean up imports + small fixes.

VITA-Group · Sep 30, 2022 · 8dcc115 · 8dcc115
1 parent af53a1e
commit 8dcc115
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Showing 4 changed files with 15 additions and 27 deletions.
diff --git a/run_nih-cxr-lt_experiments.sh b/run_nih-cxr-lt_experiments.sh
@@ -3,7 +3,7 @@
 echo "Training CE on NIH-LT..."
 python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
  --out_dir nih_results \
- --dataset nih-lt \
+ --dataset nih-cxr-lt \
  --loss ce \
  --max_epochs 60 \
  --patience 15 \
@@ -13,7 +13,7 @@ python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
 echo "Training class-balanced CE on NIH-LT..."
 python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
  --out_dir nih_results \
- --dataset nih-lt \
+ --dataset nih-cxr-lt \
  --loss ce \
  --rw_method cb \
  --max_epochs 60 \
@@ -24,7 +24,7 @@ python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
 echo "Training sklearn re-weighted CE on NIH-LT..."
 python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
  --out_dir nih_results \
- --dataset nih-lt \
+ --dataset nih-cxr-lt \
  --loss ce \
  --rw_method sklearn \
  --max_epochs 60 \
@@ -35,7 +35,7 @@ python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
 echo "Training focal loss on NIH-LT..."
 python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
  --out_dir nih_results \
- --dataset nih-lt \
+ --dataset nih-cxr-lt \
  --loss focal \
  --max_epochs 60 \
  --patience 15 \
@@ -45,7 +45,7 @@ python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
 echo "Training class-balanced focal loss on NIH-LT..."
 python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
  --out_dir nih_results \
- --dataset nih-lt \
+ --dataset nih-cxr-lt \
  --loss focal \
  --rw_method cb \
  --max_epochs 60 \
@@ -56,7 +56,7 @@ python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
 echo "Training sklearn re-weighted focal loss on NIH-LT..."
 python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
  --out_dir nih_results \
- --dataset nih-lt \
+ --dataset nih-cxr-lt \
  --loss focal \
  --rw_method sklearn \
  --max_epochs 60 \
@@ -67,7 +67,7 @@ python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
 echo "Training LDAM loss on NIH-LT..."
 python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
  --out_dir nih_results \
- --dataset nih-lt \
+ --dataset nih-cxr-lt \
  --loss ldam \
  --max_epochs 60 \
  --patience 15 \
@@ -77,7 +77,7 @@ python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
 echo "Training class-balanced LDAM loss on NIH-LT..."
 python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
  --out_dir nih_results \
- --dataset nih-lt \
+ --dataset nih-cxr-lt \
  --loss ldam \
  --rw_method cb \
  --max_epochs 60 \
@@ -88,7 +88,7 @@ python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
 echo "Training class-balanced LDAM loss w/ DRW on NIH-LT..."
 python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
  --out_dir nih_results \
- --dataset nih-lt \
+ --dataset nih-cxr-lt \
  --loss ldam \
  --rw_method cb \
  --drw \
@@ -100,7 +100,7 @@ python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
 echo "Training sklearn re-weighted LDAM loss on NIH-LT..."
 python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
  --out_dir nih_results \
- --dataset nih-lt \
+ --dataset nih-cxr-lt \
  --loss ldam \
  --rw_method sklearn \
  --max_epochs 60 \
@@ -111,7 +111,7 @@ python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
 echo "Training sklearn re-weighted LDAM loss w/ DRW on NIH-LT..."
 python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
  --out_dir nih_results \
- --dataset nih-lt \
+ --dataset nih-cxr-lt \
  --loss ldam \
  --rw_method sklearn \
  --drw \
@@ -123,7 +123,7 @@ python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
 echo "Training mixup on NIH-LT..."
 python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
  --out_dir nih_results \
- --dataset nih-lt \
+ --dataset nih-cxr-lt \
  --loss ce \
  --max_epochs 60 \
  --patience 15 \
@@ -135,7 +135,7 @@ python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
 echo "Training balanced mixup on NIH-LT..."
 python src/main.py --data_dir /ssd1/greg/NIH_CXR/images \
  --out_dir nih_results \
- --dataset nih-lt \
+ --dataset nih-cxr-lt \
  --loss ce \
  --max_epochs 60 \
  --patience 15 \

diff --git a/src/losses.py b/src/losses.py
@@ -2,8 +2,6 @@
 import torch
 import torch.nn.functional as F
 
-from copy import deepcopy
-
 def get_loss(args, weights, train_dataset):
  if args.loss == 'ce':
  loss_fxn = torch.nn.CrossEntropyLoss(weight=weights, reduction='mean')

diff --git a/src/main.py b/src/main.py
@@ -1,17 +1,12 @@
 import os
 import shutil
-import time
 
 import argparse
-import cv2
 import numpy as np
 import pandas as pd
 import torch
-import torch.nn.functional as F
 import torchvision
-import tqdm
 
-from sklearn.metrics import accuracy_score, roc_auc_score, classification_report
 from sklearn.utils import class_weight
 
 from datasets import *
@@ -47,7 +42,7 @@ def main(args):
  set_seed(args.seed)
 
  # Create datasets + loaders
- if args.dataset == 'nih-lt':
+ if args.dataset == 'nih-cxr-lt':
  dataset = NIH_CXR_Dataset
  N_CLASSES = 20
  else:

diff --git a/src/utils.py b/src/utils.py
@@ -1,22 +1,17 @@
 import os
 import random
-import shutil
 
-import cv2
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
 import torch
-import torch.nn.functional as F
-import torchvision
 import tqdm
 
 from copy import deepcopy
 
 from mlxtend.plotting import plot_confusion_matrix
-from sklearn.metrics import roc_auc_score, balanced_accuracy_score, classification_report, confusion_matrix, matthews_corrcoef, ConfusionMatrixDisplay
+from sklearn.metrics import roc_auc_score, balanced_accuracy_score, classification_report, confusion_matrix, matthews_corrcoef
 from sklearn.preprocessing import LabelBinarizer
-from sklearn.utils import compute_class_weight
 
 def set_seed(seed):
  """Set all random seeds and settings for reproducibility (deterministic behavior)."""