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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()
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