Update app.py

app.py

@@ -3,21 +3,6 @@ import sahi
 import torch
 from ultralyticsplus import YOLO, render_model_output
 
-# # Images
-# sahi.utils.file.download_from_url(
-#     "https://raw.githubusercontent.com/obss/sahi/main/tests/data/small-vehicles1.jpeg",
-#     "highway.jpg",
-# )
-# sahi.utils.file.download_from_url(
-#     "https://raw.githubusercontent.com/obss/sahi/main/tests/data/small-vehicles1.jpeg",
-#     "small-vehicles1.jpeg",
-# )
-# sahi.utils.file.download_from_url(
-#     "https://raw.githubusercontent.com/ultralytics/yolov5/master/data/images/zidane.jpg",
-#     "zidane.jpg",
-# )
-
-
 model_names = [
     "yolov8n-seg.pt",
     "yolov8s-seg.pt",
@@ -29,13 +14,12 @@ model_names = [
 current_model_name = "yolov8m-seg.pt"
 model = YOLO(current_model_name)
 
-
 def yolov8_inference(
     image: gr.inputs.Image = None,
-    model_name: gr.inputs.Dropdown = None,
-    image_size: gr.inputs.Slider = 640,
-    conf_threshold: gr.inputs.Slider = 0.25,
-    iou_threshold: gr.inputs.Slider = 0.45,
+    model_name: str = current_model_name,
+    image_size: int = 640,
+    conf_threshold: float = 0.25,
+    iou_threshold: float = 0.45,
 ):
     """
     YOLOv8 inference function
@@ -49,10 +33,8 @@ def yolov8_inference(
         Rendered image
     """
     global model
-    global current_model_name
     if model_name != current_model_name:
         model = YOLO(model_name)
-        current_model_name = model_name
     model.overrides["conf"] = conf_threshold
     model.overrides["iou"] = iou_threshold
     results = model.predict(image, imgsz=image_size, return_outputs=True)
@@ -65,9 +47,8 @@ def yolov8_inference(
 
     return renders[0]
 
-
 inputs = [
-    gr.Image(type="filepath", label="Input Image"),
+    gr.Image(type="file", label="Input Image"),
     gr.Dropdown(
         model_names,
         value=current_model_name,
@@ -80,21 +61,21 @@ inputs = [
     gr.Slider(minimum=0.0, maximum=1.0, value=0.45, step=0.05, label="IOU Threshold"),
 ]
 
-outputs = gr.Image(type="filepath", label="Output Image")
+outputs = gr.Image(type="file", label="Output Image")
 title = "Ultralytics YOLOv8 Segmentation Demo"
 
-examples = [
-    ["ikun.jpg", "yolov8m-seg.pt", 640, 0.6, 0.45],
-    ["people.png", "yolov8m-seg.pt", 640, 0.25, 0.45],
-   
-]
+# 设置默认输入参数
+default_input = ["ikun.jpg", current_model_name, 640, 0.6, 0.45]
+
 demo_app = gr.Interface(
     fn=yolov8_inference,
     inputs=inputs,
     outputs=outputs,
     title=title,
-    examples=examples,
+    examples=[default_input],
     cache_examples=True,
     theme="default",
 )
+
+# 运行应用，并设置live=True
 demo_app.launch(debug=True, enable_queue=True, live=True)