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Update app.py
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app.py
CHANGED
@@ -1,12 +1,14 @@
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import PIL.Image as Image
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import gradio as gr
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from ultralytics import ASSETS, YOLO
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model = YOLO("./best.pt")
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def predict_image(img, conf_threshold, iou_threshold):
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results = model.predict(
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source=img,
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conf=conf_threshold,
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@@ -22,22 +24,19 @@ def predict_image(img, conf_threshold, iou_threshold):
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return im
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iface = gr.Interface(
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fn=predict_image,
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inputs=[
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gr.Image(type="pil", label="Upload Image"),
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gr.Slider(minimum=0, maximum=1, value=0.25, label="Confidence threshold"),
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gr.Slider(minimum=0, maximum=1, value=0.45, label="IoU threshold")
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],
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outputs=gr.Image(type="pil", label="Result"),
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title="Ultralytics Gradio",
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description="Upload images for inference. The Ultralytics YOLOv8n model is used by default.",
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examples=[
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["1.jpg"
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["2.jpg"
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]
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)
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if __name__ == '__main__':
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iface.launch()
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import PIL.Image as Image
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import gradio as gr
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from ultralytics import ASSETS, YOLO
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model = YOLO("./best.pt")
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def predict_image(img):
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# Set your default confidence and IoU thresholds here if needed
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conf_threshold = 0.25
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iou_threshold = 0.45
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results = model.predict(
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source=img,
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conf=conf_threshold,
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return im
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iface = gr.Interface(
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fn=predict_image,
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inputs=[
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gr.Image(type="pil", label="Upload Image"),
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],
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outputs=gr.Image(type="pil", label="Result"),
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title="Ultralytics Gradio",
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description="Upload images for inference. The Ultralytics YOLOv8n model is used by default.",
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examples=[
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["1.jpg"],
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["2.jpg"],
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]
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)
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if __name__ == '__main__':
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iface.launch()
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