app.py

from ultralytics import YOLO
from PIL import Image
import gradio as gr
from huggingface_hub import snapshot_download
import os

MODEL_REPO_ID = "mintheinwin/3907578Y"

def load_model(repo_id):
    download_dir = snapshot_download(repo_id)
    print(download_dir)
    path  = os.path.join(download_dir, "best_int8_openvino_model")
    print(path)
    detection_model = YOLO(path, task='detect')
    return detection_model
detection_model = load_model(MODEL_REPO_ID)

# Student ID
student_info = "Student Id: 3907578Y, Name: Min Thein Win"

def predict(pilimg):
    source = pilimg
    result = detection_model.predict(source, conf=0.5, iou=0.5)
    img_bgr = result[0].plot()
    out_pilimg = Image.fromarray(img_bgr[..., ::-1])  # RGB-order PIL image
    return out_pilimg

gr.Interface(fn=predict,
             inputs=gr.Image(type="pil"),
             outputs=gr.Image(type="pil"),
             title="Detect tiger and lion",
             description=student_info,
             ).launch(share=True)