Update app.py

app.py

@@ -2,6 +2,7 @@ from custom_torch_module.deploy_utils import Onnx_deploy_model
 import gradio as gr
 import time
 from PIL import Image
+import os
 
 model_path = "deploying model/" + "vit_xsmall_patch16_clip_224(trainble_0.15) (Acc 98.44%, Loss 0.168152).onnx"
 input_size = [1, 3, 224, 224]
@@ -23,12 +24,14 @@ def predict(img):
     return pred_label_and_probs, prediction_fps
 
 onnx_model = Onnx_deploy_model(model_path=model_path, img_size=img_size)
+example_list = [["examples/" + example] for example in os.listdir("examples")]
 
 # Create the Gradio demo
 demo = gr.Interface(fn=predict, 
                     inputs=gr.Image(type="pil"),
                     outputs=[gr.Label(num_top_classes=2, label="Predictions"),
                              gr.Number(label="Prediction speed(FPS)")], 
+                    examples=example_list,
                     title=title,
                     description=description,
                     article=article)