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Configuration error
Configuration error
Update app.py
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app.py
CHANGED
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@@ -3,6 +3,8 @@ import sahi
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import torch
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from ultralyticsplus import YOLO, render_model_output
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model_names = [
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"yolov8n-seg.pt",
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"yolov8s-seg.pt",
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@@ -14,12 +16,13 @@ model_names = [
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current_model_name = "yolov8m-seg.pt"
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model = YOLO(current_model_name)
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def yolov8_inference(
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image: gr.inputs.Image = None,
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model_name:
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image_size:
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conf_threshold:
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iou_threshold:
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):
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"""
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YOLOv8 inference function
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@@ -33,8 +36,10 @@ def yolov8_inference(
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Rendered image
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"""
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global model
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if model_name != current_model_name:
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model = YOLO(model_name)
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model.overrides["conf"] = conf_threshold
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model.overrides["iou"] = iou_threshold
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results = model.predict(image, imgsz=image_size, return_outputs=True)
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@@ -47,8 +52,9 @@ def yolov8_inference(
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return renders[0]
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inputs = [
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gr.Image(type="
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gr.Dropdown(
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model_names,
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value=current_model_name,
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@@ -61,21 +67,21 @@ inputs = [
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gr.Slider(minimum=0.0, maximum=1.0, value=0.45, step=0.05, label="IOU Threshold"),
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]
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outputs = gr.Image(type="
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title = "Ultralytics YOLOv8 Segmentation Demo"
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demo_app = gr.Interface(
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fn=yolov8_inference,
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inputs=inputs,
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outputs=outputs,
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title=title,
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examples=
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cache_examples=True,
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theme="default",
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)
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# 运行应用,并设置live=True
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demo_app.launch(debug=True, enable_queue=True, live=True)
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import torch
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from ultralyticsplus import YOLO, render_model_output
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model_names = [
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"yolov8n-seg.pt",
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"yolov8s-seg.pt",
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current_model_name = "yolov8m-seg.pt"
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model = YOLO(current_model_name)
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def yolov8_inference(
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image: gr.inputs.Image = None,
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model_name: gr.inputs.Dropdown = None,
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image_size: gr.inputs.Slider = 640,
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conf_threshold: gr.inputs.Slider = 0.25,
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iou_threshold: gr.inputs.Slider = 0.45,
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):
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"""
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YOLOv8 inference function
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Rendered image
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"""
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global model
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global current_model_name
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if model_name != current_model_name:
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model = YOLO(model_name)
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current_model_name = model_name
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model.overrides["conf"] = conf_threshold
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model.overrides["iou"] = iou_threshold
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results = model.predict(image, imgsz=image_size, return_outputs=True)
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return renders[0]
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inputs = [
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gr.Image(type="filepath", label="Input Image"),
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gr.Dropdown(
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model_names,
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value=current_model_name,
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gr.Slider(minimum=0.0, maximum=1.0, value=0.45, step=0.05, label="IOU Threshold"),
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]
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outputs = gr.Image(type="filepath", label="Output Image")
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title = "Ultralytics YOLOv8 Segmentation Demo"
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examples = [
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["ikun.jpg", "yolov8m-seg.pt", 640, 0.6, 0.45],
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["people.jpg", "yolov8m-seg.pt", 640, 0.25, 0.45],
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]
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demo_app = gr.Interface(
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fn=yolov8_inference,
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inputs=inputs,
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outputs=outputs,
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title=title,
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examples=examples,
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cache_examples=True,
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theme="default",
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)
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demo_app.launch(debug=True, enable_queue=True)
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