app.py

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

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

def predict(pilimg):
    source = pilimg
    # x = np.asarray(pilimg)
    # print(x.shape)
    result = detection_model.predict(source, conf=0.5, iou=0.6)
    img_bgr = result[0].plot()
    out_pilimg = Image.fromarray(img_bgr[..., ::-1])  # RGB-order PIL image
    
    return out_pilimg

REPO_ID = "ITI121-25S2/7080274J"
detection_model = load_model(REPO_ID)

gr.Interface(fn=predict,
            inputs=gr.Image(type="pil", label="Input Image"),
            outputs=gr.Image(type="pil", label="Detected Image"),
            title="Durian and Mangosteen Detector",
            description="Upload an image to detect durians and mangosteens using a YOLOv11 model trained on a custom dataset. Developed by Cheng Soon Teck."
).launch(share=True)