Upload 4 files

app.py

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+import PIL.Image as Image
+import gradio as gr
+
+from ultralytics import ASSETS, YOLO
+
+model = YOLO("./best.pt")
+
+
+def predict_image(img, conf_threshold, iou_threshold):
+    results = model.predict(
+        source=img,
+        conf=conf_threshold,
+        iou=iou_threshold,
+        show_labels=True,
+        show_conf=True,
+        imgsz=640,
+    )
+
+    for r in results:
+        im_array = r.plot()
+        im = Image.fromarray(im_array[..., ::-1])
+
+    return im
+
+
+iface = gr.Interface(
+    fn=predict_image,
+    inputs=[
+        gr.Image(type="pil", label="Upload Image"),
+        gr.Slider(minimum=0, maximum=1, value=0.25, label="Confidence threshold"),
+        gr.Slider(minimum=0, maximum=1, value=0.45, label="IoU threshold")
+    ],
+    outputs=gr.Image(type="pil", label="Result"),
+    title="Ultralytics Gradio",
+    description="Upload images for inference. The Ultralytics YOLOv8n model is used by default.",
+    examples=[
+        ["1.jpg", 0.25, 0.45],
+        ["2.jpg", 0.25, 0.45],
+    ]
+)
+
+if __name__ == '__main__':
+    iface.launch()

gitattributes (2)

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ovarian.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0e6ae0460acb0905cc14717f6455a2ee4ccc8379913227ea26064c3dba74b310
+size 22547225

requirements.txt

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+gradio
+torch
+torchvision
+Pillow
+ultralytics
+render