Initial commit

app.py

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+import gradio as gr
+import PIL.Image as Image
+
+from ultralytics import 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=[
+        "examples/healthy.jpg",
+        "examples/aculus_2.jpg",
+        "examples/aculus_1.jpg",
+        "examples/peacock_2.jpg",
+        "examples/peacock_3.jpg",
+    ],
+)
+
+if __name__ == "__main__":
+    iface.launch()

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4a088db8573378e1149dab4bac8c7ab4bb1bcc174e18a30b1ec477bf0e1e7f41
+size 22491555

requirements.txt

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+gradio
+ultralytics