Updated error images to black

app.py

@@ -159,19 +159,19 @@ model.eval()
 examples = [
     [
         "Where can the driver see the car speed in this image? Please output segmentation mask.",
-        "./resources/imgs/example1.jpg",
+        "./imgs/example1.jpg",
     ],
     [
         "Can you segment the food that tastes spicy and hot?",
-        "./resources/imgs/example2.jpg",
+        "./imgs/example2.jpg",
     ],
     [
         "Assuming you are an autonomous driving robot, what part of the diagram would you manipulate to control the direction of travel? Please output segmentation mask and explain why.",
-        "./resources/imgs/example1.jpg",
+        "./imgs/example1.jpg",
     ],
     [
         "What can make the woman stand higher? Please output segmentation mask and explain why.",
-        "./resources/imgs/example3.jpg",
+        "./imgs/stand_higher.jpg",
     ],
 ]
 output_labels = ["Segmentation Output"]
@@ -214,10 +214,10 @@ def inference(input_str, input_image):
 
     ## input valid check
     if not re.match(r"^[A-Za-z ,.!?\'\"]+$", input_str) or len(input_str) < 1:
-        output_str = "[Error] Invalid input: ", input_str
-        # output_image = np.zeros((128, 128, 3))
-        ## error happened
-        output_image = cv2.imread("./resources/error_happened.png")[:, :, ::-1]
+        output_str = f"[Error] Invalid input: {input_str}"
+        # Create a red placeholder image to indicate an error
+        output_image = np.zeros((128, 128, 3), dtype=np.uint8)
+        output_image[:] = (0, 0, 0)  # Red color in RGB
         return output_image, output_str
 
     # Model Inference
@@ -334,8 +334,8 @@ def inference(input_str, input_image):
     if save_img is not None:
         output_image = save_img  # input_image
     else:
-        ## no seg output
-        output_image = cv2.imread("./resources/no_seg_out.png")[:, :, ::-1]
+        ## no segmentation output, return a black placeholder image
+        output_image = np.zeros((128, 128, 3), dtype=np.uint8)
     return output_image, output_str