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import os
import gradio as gr
from gradio_client import Client, handle_file
from pathlib import Path
from gradio.utils import get_cache_folder
class Examples(gr.helpers.Examples):
def __init__(self, *args, cached_folder=None, **kwargs):
super().__init__(*args, **kwargs, _initiated_directly=False)
if cached_folder is not None:
self.cached_folder = cached_folder
# self.cached_file = Path(self.cached_folder) / "log.csv"
self.create()
HF_TOKEN = os.environ.get('HF_KEY')
client = Client("Canyu/Diception",
max_workers=3,
hf_token=HF_TOKEN)
def process_image_check(path_input):
if path_input is None:
raise gr.Error(
"Missing image in the left pane: please upload an image first."
)
def infer_image_matting(matting_image_input):
return client.predict(
prompt=handle_file(matting_image_input),
api_name="/infer_image_matting"
)
def clear_cache():
return None, None
def run_demo_server():
gradio_theme = gr.themes.Default()
with gr.Blocks(
theme=gradio_theme,
title="Matting",
) as demo:
with gr.Row():
gr.Markdown("# Matting Demo")
with gr.Row():
gr.Markdown("### Due to the GPU quota limit, if an error occurs, please wait for 5 minutes before retrying.")
with gr.Row():
with gr.Column():
matting_image_input = gr.Image(
label="Input Image",
type="filepath",
)
with gr.Row():
matting_image_submit_btn = gr.Button(
value="Estimate Matting", variant="primary"
)
matting_image_reset_btn = gr.Button(value="Reset")
with gr.Row():
img_clear_button = gr.Button("Clear Cache")
with gr.Column():
# matting_image_output = gr.Image(label='Output')
matting_image_output = gr.Image(label='Matting Output')
# label="Matting Output",
# type="filepath",
# show_download_button=True,
# show_share_button=True,
# interactive=False,
# elem_classes="slider",
# position=0.25,
# )
img_clear_button.click(clear_cache, outputs=[matting_image_input, matting_image_output])
matting_image_submit_btn.click(
fn=process_image_check,
inputs=matting_image_input,
outputs=None,
preprocess=False,
queue=False,
).success(
# fn=process_pipe_matting,
fn=infer_image_matting,
inputs=[
matting_image_input,
],
outputs=[matting_image_output],
concurrency_limit=1,
)
matting_image_reset_btn.click(
fn=lambda: (
None,
None,
),
inputs=[],
outputs=[
matting_image_input,
matting_image_output,
],
queue=False,
)
gr.Examples(
fn=infer_image_matting,
examples=[
"assets/person.jpg",
],
inputs=[matting_image_input],
outputs=[matting_image_output],
cache_examples=True,
# cache_examples=False,
# cached_folder="cache_dir",
)
demo.queue(
api_open=False,
).launch()
if __name__ == '__main__':
run_demo_server() |