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import os
import gradio as gr
from face import _FACE_MODELS, _DEFAULT_FACE_MODEL, _gr_detect_faces
if __name__ == '__main__':
with gr.Blocks() as demo:
with gr.Tabs():
with gr.Tab('Face Detection'):
with gr.Row():
with gr.Column():
gr_face_input_image = gr.Image(type='pil', label='Original Image')
gr_face_model = gr.Dropdown(_FACE_MODELS, value=_DEFAULT_FACE_MODEL, label='Model')
gr_face_infer_size = gr.Slider(480, 1600, value=1216, step=32, label='Max Infer Size')
with gr.Row():
gr_face_iou_threshold = gr.Slider(0.0, 1.0, 0.7, label='IOU Threshold')
gr_face_score_threshold = gr.Slider(0.0, 1.0, 0.25, label='Score Threshold')
gr_face_submit = gr.Button(value='Submit', variant='primary')
with gr.Column():
gr_face_output_image = gr.Image(type='pil', label="Labeled")
gr_face_submit.click(
_gr_detect_faces,
inputs=[
gr_face_input_image, gr_face_model,
gr_face_infer_size, gr_face_score_threshold, gr_face_iou_threshold,
],
outputs=[gr_face_output_image],
)
demo.queue(os.cpu_count()).launch()
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