Update app.py

app.py

@@ -10,9 +10,9 @@ class_labels = ["NORMAL", "PNEUMONIA"]  # Update if you have more classes
 
 # Preprocessing function for uploaded images
 def preprocess_image(img):
-    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-    img = cv2.resize(img, (150, 150)) / 255.0
-    img = np.expand_dims(img, axis=0)
+    img = cv2.resize(img, (150, 150))  # Resize
+    img = img.astype(np.float32) / 255.0  # Normalize and ensure dtype
+    img = np.expand_dims(img, axis=0)  # Add batch dimension
     return img
 
 # Prediction function
@@ -26,7 +26,7 @@ def predict_chest_xray(img):
 # Create Gradio UI
 interface = gr.Interface(
     fn=predict_chest_xray,
-    inputs=gr.Image(type="numpy"),
+    inputs=gr.Image(type="numpy"),  # Expect NumPy array
     outputs="text",
     title="Chest X-Ray Diagnosis",
     description="Upload a chest X-ray image to get a diagnosis prediction."