app.py

import gradio as gr
from image_resizer import ImageResizer

MODEL_PATH = "face_detection_yunet_2023mar.onnx"
image_resizer = ImageResizer(modelPath=MODEL_PATH)


def face_detector(input_image, target_size=512):
    return image_resizer.resize(input_image, target_size)


inputs = [
    gr.Image(sources=["upload", "clipboard"], type="numpy"),
    gr.Dropdown(
        choices=[512, 768, 1024],
        value=512,
        allow_custom_value=True,
        info="Target size of images",
    ),
]
outputs = [
    gr.Image(label="face detection", format="JPEG"),
    gr.Image(label="focused resized", format="JPEG"),
]
demo = gr.Interface(
    fn=face_detector,
    inputs=inputs,
    outputs=outputs,
    title="Image Resizer",
    theme="gradio/monochrome",
    api_name="resize",
    submit_btn=gr.Button("Resize", variant="primary"),
    allow_flagging="never",
)
demo.queue(
    max_size=10,
)

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