app.py

import gradio as gr
from openvino.runtime import Core
from PIL import Image
import numpy as np


core = Core()


model = core.read_model("openvino_model/best.xml") 
compiled_model = core.compile_model(model, "CPU")
output_layer = compiled_model.output(0)


def preprocess_image(image):
   
    image = image.resize((640, 640))
    input_data = np.array(image).transpose(2, 0, 1) 
    input_data = np.expand_dims(input_data, axis=0)  
    input_data = input_data.astype(np.float32) / 255.0  
    return input_data


def predict(image):
    input_data = preprocess_image(image)
    results = compiled_model([input_data])[output_layer] 

   
    print("Raw results:", results)
    output_image = image.copy()  
    return output_image


interface = gr.Interface(
    fn=predict,
    inputs=gr.Image(type="pil"),
    outputs=gr.Image(type="pil"),
    title="Object Detection",
    description="Upload an image to detect objects using the OpenVINO 2024 model."
)


if __name__ == "__main__":
    interface.launch()