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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()
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