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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() |