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

#model_path = "/Users/markk/Downloads/best_int8_openvino_model"
#model_path1 = "C:\Users\aungh\Downloads\6319250G\best_int8_openvino_model"

# Define the path to the YOLOv8 mo
model_path = "best_int8_openvino_model"   

#Organizations model path location
MODEL_REPO_ID = "aunghlaing/testmodel"

#load model
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: 6319250G, Name: AUNG HTUN"

#prdeict 
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
    
#UI interface
gr.Markdown("# Two Object Detection (Shark/Mask)")
gr.Markdown(student_info)
gr.Interface(fn=predict,
             inputs=gr.Image(type="pil",label="Input"),
             outputs=gr.Image(type="pil",label="Output"),
             title="Two Object Detection (Shark/Mask)",
             description=student_info,
             ).launch(share=True)