Update app.py

app.py

@@ -3,8 +3,8 @@ import torch
 from PIL import Image
 from ultralytics import YOLO
 
-model = YOLO(r'pcb-best.pt')
 
+model = YOLO(r'pcb-best.pt')
 def predict(img, conf, iou):
     results = model.predict(img, conf=conf, iou=iou)
     for i, r in enumerate(results):
@@ -19,6 +19,9 @@ def predict(img, conf, iou):
 base_conf, base_iou = 0.25, 0.45
 title = "基于YOLO-V8的PCB电路板缺陷检测"
 des = "鼠标点击上传图片即可检测缺陷，可通过鼠标调整预测置信度，还可点击网页最下方示例图片进行预测"
-gr.Interface(inputs=['image',gr.Slider(maximum=1, minimum=0, value=base_conf), gr.Slider(maximum=1, minimum=0, value=base_iou)],
-             outputs=["image"], fn=predict, title=title, description=des).launch()
+interface = gr.Interface(inputs=['image',gr.Slider(maximum=1, minimum=0, value=base_conf), gr.Slider(maximum=1, minimum=0, value=base_iou)],
+             outputs=["image"],  fn=predict, title=title, description=des, examples=[["example1.jpg", base_conf, base_iou],
+                                                                                     ["example2.jpg", base_conf, base_iou],
+                                                                                     ["example3.jpg", base_conf, base_iou]])
 
+interface.launch()