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from ultralytics import ASSETS, YOLO, RTDETR |
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import gradio as gr |
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from huggingface_hub import snapshot_download |
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model_dir = snapshot_download("omarelsayeed/DETR-ARABIC-DOCUMENT-LAYOUT-ANALYSIS") + "/Model.pt" |
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model = RTDETR(model_dir) |
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def predict_image(img, conf_threshold, iou_threshold): |
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"""Predicts objects in an image using a YOLO11 model with adjustable confidence and IOU thresholds.""" |
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results = model.predict( |
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source=img, |
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conf=conf_threshold, |
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iou=iou_threshold, |
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show_labels=True, |
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show_conf=True, |
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imgsz=640, |
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) |
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for r in results: |
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im_array = r.plot() |
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im = Image.fromarray(im_array[..., ::-1]) |
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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 YOLO11n model is used by default.", |
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examples=[ |
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[ASSETS / "bus.jpg", 0.25, 0.45], |
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[ASSETS / "zidane.jpg", 0.25, 0.45], |
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], |
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) |
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if __name__ == "__main__": |
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iface.launch(share = True) |
