from ultralytics import YOLO
from PIL import Image
import gradio as gr
import numpy as np
def function(image):
  model = YOLO('best_yolo_2.pt')
  image = np.array(image)
  results = model.predict(image)
  img=Image.fromarray(results[0].plot())
  num_result=len(results[0].boxes.cls)
  names_output=[]
  for i in range(num_result):
    name=results[0].names[int(results[0].boxes.cls[i])]
    names_output.append(name)
  return names_output,img
demo=gr.Interface(fn=function,inputs="image",outputs=["text","image"])
demo.launch()