Update app.py

app.py

@@ -55,17 +55,22 @@ def binary_decision(confidence):
     return 1 if confidence >= 0.5 else 0
 
 def predict_braintumor(img):
-    # Save the uploaded file
-    filename = "temp_image.png"
-    file_path = os.path.join(UPLOAD_FOLDER, filename)
+    # Save the uploaded file if it's a file-like object
+    if hasattr(img, 'read'):
+        filename = "temp_image.png"
+        file_path = os.path.join(UPLOAD_FOLDER, filename)
 
-    # Convert Gradio image data to bytes
-    img_bytes = img.read()
-    
-    with open(file_path, "wb") as f:
-        f.write(img_bytes)
+        # Convert Gradio image data to bytes
+        img_bytes = img.read()
 
-    img_gray = cv2.imread(file_path, cv2.IMREAD_GRAYSCALE)
+        with open(file_path, "wb") as f:
+            f.write(img_bytes)
+
+        img_gray = cv2.imread(file_path, cv2.IMREAD_GRAYSCALE)
+
+    # If it's a NumPy array, use it directly
+    elif isinstance(img, np.ndarray):
+        img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
 
     # Crop and preprocess the grayscale image
     img_processed = crop_imgs([img_gray])
@@ -78,6 +83,7 @@ def predict_braintumor(img):
     confidence = pred[0][0]
     return "Brain Tumor Found!" if binary_decision(confidence) == 1 else "Brain Tumor Not Found!"
 
+
 def main():
     st.title("Brain Tumor Prediction App")