app.py

import os
from ultralytics import YOLO
import gradio as gr
import PIL.Image as Image

path="bestn.pt"

model=YOLO(path)

def predict_image(img, conf_threshold, iou_threshold):
    """Predicts objects in an image using a YOLOv8 model with adjustable confidence and IOU thresholds."""
    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

example_list = [["examples/" + example, 0.25, 0.45] for example in os.listdir("examples")]
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"),
    examples=example_list,
    title="Object Detection",
    description="Upload Valid Images:Traffic Sign/Light & Fire Hydrant|Select threshold value while uploading images.",
)

iface.launch()