-

app.py

@@ -1,4 +1,42 @@
 import gradio as gr
+from monai.utils import first, set_determinism
+from monai.transforms import(
+ Compose,
+ AddChanneld,
+ LoadImaged,
+ Resized,
+ ToTensord,
+ Spacingd,
+ Orientationd,
+ ScaleIntensityRanged,
+ CropForegroundd,
+ Activations,
+)
+
+from monai.networks.nets import UNet
+from monai.networks.layers import Norm
+from monai.data import CacheDataset, DataLoader, Dataset
+
+import torch
+import matplotlib.pyplot as plt
+
+import os
+from glob import glob
+import numpy as np
+
+from monai.inferers import sliding_window_inference
+
+in_dir = 'Data_Train_Test'
+model_dir = ''
+
+train_loss = np.load(os.path.join(model_dir, 'loss_train.npy'))
+train_metric = np.load(os.path.join(model_dir, 'metric_train.npy'))
+test_loss = np.load(os.path.join(model_dir, 'loss_test.npy'))
+test_metric = np.load(os.path.join(model_dir, 'metric_test.npy'))
+
+
+
+
 
 def segment(image):
  pass # Implement your image segmentation model here...