Update app.py

app.py

@@ -10,7 +10,7 @@ import itertools
 import matplotlib.pyplot as plt
 from utils import LitCIFAR10
 
-model = LitCIFAR10.load_from_checkpoint("model.ckpt")
+model = LitCIFAR10.load_from_checkpoint("model/model.ckpt")
 model.eval()
 
 classes = ('plane', 'car', 'bird', 'cat',
@@ -120,7 +120,7 @@ def inference(wants_gradcam, n_gradcam, target_layer_number, transparency, wants
 
 title = "CIFAR10 trained on Custom ResNet Model with GradCAM"
 description = "A simple Gradio interface to infer on ResNet model, and get GradCAM results"
-examples = [[None, None, None, None, None, None, 'test_'+str(i)+'.jpg', None] for i in range(10)]
+examples = [[None, None, None, None, None, None, 'Images/test_'+str(i)+'.jpg', None] for i in range(10)]
 
 demo = gr.Interface(inference,
                     inputs = [gr.Checkbox(False, label='Do you want to see GradCAM outputs?'),