Update app.py

app.py

@@ -80,7 +80,7 @@ def inference(input_img, transparency=0.5, target_layer_number=-1, num_images=1,
 
 title = "CIFAR10 trained on ResNet18 Model with GradCAM"
 description = "A simple Gradio interface to infer on ResNet model, and get GradCAM results"
-examples = [["/content/examples/car_1.jpg",0.5,-1],["/content/examples/car_2.jpg",0.5,-1],["/content/examples/cat_1.jpg",0.5,-1],["/content/examples/cat_2.jpg",0.5,-1],["/content/examples/dog_1.jpg",0.5,-1],["/content/examples/dog_2.jpg",0.5,-1],["/content/examples/frog_1.jpg",0.5,-1],["/content/examples/frog_2.jpg",0.5,-1],["/content/examples/horse_1.jpg",0.5,-1],["/content/examples/horse_2.jpg",0.5,-1]]
+examples = [["car_1.jpg",0.5,-1],["car_2.jpg",0.5,-1],["cat_1.jpg",0.5,-1],["cat_2.jpg",0.5,-1],["dog_1.jpg",0.5,-1],["dog_2.jpg",0.5,-1],["frog_1.jpg",0.5,-1],["frog_2.jpg",0.5,-1],["horse_1.jpg",0.5,-1],["horse_2.jpg",0.5,-1]]
 demo = gr.Interface(
     inference,
     inputs = [gr.Image(shape=(32, 32), label="Input Image"),