SickstadiumAI / app.py
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import gradio as gr
from video_processing import process_video, download_video, find_scenes, analyze_scenes, extract_best_scene, cleanup_temp_files
from gradio.themes.base import Base
from gradio.themes.utils import colors, fonts, sizes
import uuid
import os
from typing import Iterable
class CustomTheme(Base):
def __init__(
self,
*,
primary_hue: colors.Color | str = colors.orange,
secondary_hue: colors.Color | str = colors.orange,
neutral_hue: colors.Color | str = colors.gray,
spacing_size: sizes.Size | str = sizes.spacing_md,
radius_size: sizes.Size | str = sizes.radius_md,
text_size: sizes.Size | str = sizes.text_md,
font: fonts.Font | str | Iterable[fonts.Font | str] = (
fonts.GoogleFont("Sora"),
"ui-sans-serif",
"sans-serif",
),
font_mono: fonts.Font | str | Iterable[fonts.Font | str] = (
fonts.GoogleFont("Sora"),
"ui-monospace",
"monospace",
),
):
super().__init__(
primary_hue=primary_hue,
secondary_hue=secondary_hue,
neutral_hue=neutral_hue,
spacing_size=spacing_size,
radius_size=radius_size,
text_size=text_size,
font=font,
font_mono=font_mono,
)
super().set(
body_background_fill="radial-gradient(circle at center, rgba(235, 87, 38, 1) 0%, rgba(235, 87, 38, 0) 70%), radial-gradient(#eb5726 1px, transparent 1px)",
body_text_color="#282828",
block_background_fill="#ffffff",
block_title_text_color="#eb5726",
block_label_text_color="#eb5726",
button_primary_background_fill="#eb5726",
button_primary_text_color="#ffffff",
)
custom_theme = CustomTheme()
def save_uploaded_file(uploaded_file):
upload_dir = "uploaded_videos"
os.makedirs(upload_dir, exist_ok=True)
file_path = os.path.join(upload_dir, f"{uuid.uuid4()}.mp4")
with open(file_path, "wb") as f:
f.write(uploaded_file)
return file_path
def display_results(video_url, video_file, description):
if video_url:
video_path = download_video(video_url)
elif video_file:
video_path = save_uploaded_file(video_file)
else:
return "No video provided", None, None
scenes = find_scenes(video_path)
if not scenes:
return "No scenes detected", None, None
best_scene_info = analyze_scenes(video_path, scenes, description)
if best_scene_info:
best_scene = best_scene_info[0]
sentiment_distribution = best_scene_info[4] # Ensure you're accessing the correct index for sentiment_distribution
final_clip = extract_best_scene(video_path, best_scene)
if final_clip:
output_dir = "output"
os.makedirs(output_dir, exist_ok=True)
final_clip_path = os.path.join(output_dir, f"{uuid.uuid4()}_final_clip.mp4")
final_clip.write_videofile(final_clip_path, codec='libx264', audio_codec='aac')
cleanup_temp_files()
# Check if sentiment_distribution is correctly obtained
if sentiment_distribution:
plot = create_radial_plot(sentiment_distribution)
return final_clip_path, plot
else:
return final_clip_path, "No sentiment data available"
else:
return "No matching scene found", None
else:
return "No suitable scenes found", None
# Custom CSS for additional styling
css = """
body {
background-color: #ffffff;
background-image: radial-gradient(#eb5726 1px, transparent 1px);
background-size: 10px 10px;
background-repeat: repeat;
background-attachment: fixed;
}
#video_url {
background-color: #ffffff;
color: #282828;
border: 2px solid #eb5726;
}
#description {
background-color: #ffffff;
color: #282828;
border: 2px solid #eb5726;
}
#submit_button {
background-color: #eb5726;
color: #ffffff;
border: 2px solid #ffffff;
}
#submit_button:hover {
background-color: #f5986e;
color: #ffffff;
border: 2px solid #ffffff;
}
label[for="video_url"], label[for="description"] {
color: #eb5726 !important;
}
h3 {
color: #eb5726;
}
.centered-markdown {
text-align: center;
background-color: #ffffff;
padding: 10px;
}
#sickstadium-title {
font-size: 3em !important;
font-weight: bold;
text-transform: uppercase;
}
"""
with gr.Blocks(theme=custom_theme, css=css) as demo:
with gr.Column():
gr.Markdown("# **Sickstadium AI**", elem_classes="centered-markdown", elem_id="sickstadium-title")
gr.Markdown("### Upload your videos. Find sick clips. Tell your truth.", elem_classes="centered-markdown")
video_url = gr.Textbox(label="Video URL:", elem_id="video_url")
video_file = gr.File(label="Upload Video File:", interactive=True, file_types=["video"], type="binary")
description = gr.Textbox(label="Describe your clip:", elem_id="description")
submit_button = gr.Button("Process Video", elem_id="submit_button")
video_output = gr.Video(label="Processed Video", elem_id="video_output")
sentiment_plot = gr.Plot(label="Sentiment Distribution", elem_id="sentiment_plot")
submit_button.click(
fn=display_results,
inputs=[video_url, video_file, description],
outputs=[video_output, sentiment_plot]
)
demo.launch()