Spaces:
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import gradio as gr
import os
from spaces_utils import authenticate
# Load tokens
GRADIO_TOKEN = os.environ.get("READ_TOKEN") # read
# Logs repo path
dataset_url = "https://huggingface.co/datasets/sandl/upload_particles_segmentation"
dataset_path = "logs_particles_segmentation.csv"
def authenticate_from_public(username, password):
return authenticate(username, password, dataset_url, dataset_path)
css_styling = """#submit {background: #1eccd8}
#submit:hover {background: #a2f1f6}
.output-image, .input-image, .image-preview {height: 250px !important}
.output-plot {height: 250px !important}"""
light_theme_colors = gr.themes.Color(c50="#e4f3fa", # Dataframe background cell content - light mode only
c100="#e4f3fa", # Top corner of clear button in light mode + markdown text in dark mode
c200="#a1c6db", # Component borders
c300="#FFFFFF", #
c400="#e4f3fa", # Footer text
c500="#0c1538", # Text of component headers in light mode only
c600="#a1c6db", # Top corner of button in dark mode
c700="#475383", # Button text in light mode + component borders in dark mode
c800="#0c1538", # Markdown text in light mode
c900="#a1c6db", # Background of dataframe - dark mode
c950="#0c1538") # Background in dark mode only
# secondary color used for highlight box content when typing in light mode, and download option in dark mode
# primary color used for login button in dark mode
osium_theme = gr.themes.Default(primary_hue="cyan", secondary_hue="cyan", neutral_hue=light_theme_colors)
page_title = "Nanoparticles characterization"
favicon_path = "osiumai_favicon.ico"
logo_path = "osiumai_logo.jpg"
html = f"""<html> <link rel="icon" type="image/x-icon" href="file={favicon_path}">
<img src='file={logo_path}' alt='Osium AI logo' width='200' height='100'> </html>"""
with gr.Blocks(css=css_styling, theme=osium_theme, title=page_title, show_progress=True) as demo_from_private:
gr.Interface.load("spaces/sandl/private_particles_segmentation", api_key=GRADIO_TOKEN, enable_queue=True)
if __name__ == "__main__":
demo_from_private.queue(concurrency_count=2)
demo_from_private.launch(debug=True, enable_queue=True) |