Upload app.py

app.py

@@ -70,18 +70,18 @@ net.eval()
 path = "uploads"  # Define path for uploads
 os.makedirs(path, exist_ok=True)  # Ensure directory exists
 
-def predict_image(img):
-    img_path = os.path.join(path, img.name)
-    img.save(img_path)
+def predict_image(path):
+    # img_path = os.path.join(path, img.name)
+    # img.save(img_path)
 
-    image_tensor = preprocess_image(img_path, get_test_transforms(224))
+    image_tensor = preprocess_image(path, get_test_transforms(224))
     pred = net(image_tensor)
     y_pred = 1 - nn.functional.softmax(pred, dim=1).data.cpu().numpy()[:, 0]
     return float(y_pred.item())
 
 iface = gr.Interface(
     fn=predict_image,
-    inputs=gr.Image(type="file"),
+    inputs=gr.Image(type="filepath"),
     outputs="number",
     title="Image Prediction App",
     description="Upload an image and get a model prediction."