Update app.py

app.py

@@ -1,26 +1,12 @@
 from fastai.vision.all import *
 import gradio as gr
 
-def get_x(row, is_test=False):
-    image_path = path_image_combined / (row['id_code'])
-    transformed_image = custom_transform(image_path)
-
-    # Check the label of the current image and apply augmentations if it belongs to the minority class
-    if not is_test and row['label'] == 1:
-        transformed_image = additional_augmentations(transformed_image)        
-    
-    return Image.fromarray(transformed_image)
-    pass
-
-def get_y(row):
-    return row['label']  # adjust this depending on how your csv is structured
-    pass
+def is_glaucoma(x): return x[0].isupper()
     
 learn = load_learner('your_model.pkl')
 
 categories = ('Glaucoma Present','Glaucoma Absent')
 
-labels = learn.dls.vocab
 def predict(img):
     pred,pred_idx,probs = learn.predict(img)
     return dict(zip(categories, map(float,probs)))