app.py

import PIL.Image as Image
import gradio as gr
from ultralytics import ASSETS, YOLO

model = YOLO("./best.pt")

def predict_image(img):
    # Set your default confidence and IoU thresholds here if needed
    conf_threshold = 0.25
    iou_threshold = 0.45

    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"),
    ],
    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"],
        ["2.jpg"],
    ]
)

if __name__ == '__main__':
    iface.launch()