Update app.py

app.py

@@ -1,18 +1,22 @@
-pip install fastai
-
 from fastai.vision.all import *
 import gradio as gr
 
-# Assuming models are loaded into a dictionary named `models` as before
+# Load your models here. Example:
+# models = {'Ultrasound': load_learner('path_to_ultrasound_model.pkl'),
+#           'OCT': load_learner('path_to_oct_model.pkl'),
+#           'Fundus': load_learner('path_to_fundus_model.pkl'),
+#           'Fluorescence': load_learner('path_to_fluorescence_model.pkl')}
+
+modality_keys = ['Ultrasound', 'OCT', 'Fundus', 'Fluorescence']
 
 def classify_images(img_ultrasound, img_oct, img_fundus, img_fluorescence):
     imgs = [img_ultrasound, img_oct, img_fundus, img_fluorescence]
-    modality_keys = ['Ultrasound', 'OCT', 'Fundus', 'Fluorescence']
     predictions = []
     
-    # Predict with each model
+    # Convert images to PILImage and Predict with each model
     for img, key in zip(imgs, modality_keys):
-        pred, _, _ = models[key].predict(img)
+        pil_img = PILImage.create(img)
+        pred, _, _ = models[key].predict(pil_img)
         predictions.append(pred)
     
     # Majority vote for final decision
@@ -27,4 +31,4 @@ output = gr.outputs.Text(label="Final Decision")
 intf = gr.Interface(fn=classify_images, inputs=inputs, outputs=output,
                     title="ODD Detection from Multiple Imaging Modalities",
                     description="Upload images for each modality and receive a binary prediction for Optic Disk Drusen presence.")
-intf.launch(inline=False)
+intf.launch(share=True)