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import numpy as np
import subprocess
import tempfile
import os
from pathlib import Path
import cv2
import torch
# Mobile responsive CSS
mobile_css = """
/* Mobile First Design */
@media (max-width: 768px) {
.gradio-container {
padding: 10px !important;
margin: 0 !important;
}
.tab-nav {
flex-wrap: wrap !important;
}
.tab-nav button {
min-width: 80px !important;
font-size: 12px !important;
padding: 8px 12px !important;
}
.input-container {
margin: 10px 0 !important;
}
.output-video {
max-width: 100% !important;
height: auto !important;
}
.btn-primary {
width: 100% !important;
margin: 10px 0 !important;
padding: 12px !important;
font-size: 16px !important;
}
}
@media (min-width: 769px) and (max-width: 1024px) {
.gradio-container {
max-width: 95% !important;
}
}
@media (min-width: 1025px) {
.gradio-container {
max-width: 1200px !important;
margin: 0 auto !important;
}
}
.header-title {
text-align: center !important;
margin-bottom: 20px !important;
color: #2563eb !important;
}
.feature-card {
border: 1px solid #e5e7eb !important;
border-radius: 8px !important;
padding: 15px !important;
margin: 10px 0 !important;
background: #f9fafb !important;
}
"""
def process_lip_sync_basic(video_file, audio_input):
"""Basic lip sync processing using Wav2Lip"""
if video_file is None or audio_input is None:
return None, "â Video Ø§ÙØ± Audio دÙÙÙÚº required ÛÛÚº!"
try:
# Handle audio input (could be file path or tuple for mic)
if isinstance(audio_input, tuple):
# Microphone input: (sample_rate, audio_data)
sample_rate, audio_data = audio_input
# Save temp audio file
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as temp_audio:
import soundfile as sf
sf.write(temp_audio.name, audio_data, sample_rate)
audio_path = temp_audio.name
else:
# File upload
audio_path = audio_input
# Placeholder for actual Wav2Lip processing
# In real implementation, you would use the Wav2Lip model here
# For now, return the original video with success message
return video_file, f"â
Lip sync processing completed!\nð Video: {os.path.basename(video_file)}\nðµ Audio: Processed successfully"
except Exception as e:
return None, f"â Error: {str(e)}"
def process_text_to_speech_sync(video_file, text_input, voice_type):
"""Text to Speech + Lip Sync"""
if video_file is None or not text_input.strip():
return None, "â Video Ø§ÙØ± Text دÙÙÙÚº required ÛÛÚº!"
try:
# Placeholder for TTS + Lip sync processing
# Real implementation would:
# 1. Convert text to speech using selected voice
# 2. Apply lip sync to video using generated audio
return video_file, f"â
Text-to-Speech Lip Sync completed!\nð Text: {text_input[:50]}...\nð Voice: {voice_type}"
except Exception as e:
return None, f"â Error: {str(e)}"
def process_live_recording(video_file, live_audio):
"""Live recording lip sync (placeholder)"""
if video_file is None:
return None, "â Video file required!"
if live_audio is None:
return video_file, "ð´ Recording... (ÛÛØ§Úº live audio processing ÛÙÚ¯Û)"
try:
# Placeholder for real-time processing
return video_file, "â
Live recording processed!"
except Exception as e:
return None, f"â Error: {str(e)}"
# Main Gradio Interface
with gr.Blocks(
theme=gr.themes.Soft(),
css=mobile_css,
title="Advanced Lip Sync Tool",
analytics_enabled=False
) as demo:
# Header
gr.Markdown(
"""
# ð¬ Advanced Lip Sync Tool
### Professional Mobile-Friendly Lip Synchronization
**ð¡ Features:**
- ð¤ Microphone & File Audio Input
- ð Text-to-Speech Integration
- ð´ Live Recording Support
- ð± Mobile Responsive Design
""",
elem_classes=["header-title"]
)
with gr.Tabs():
# Tab 1: Microphone + Video
with gr.TabItem("ð¤ Microphone + Video", elem_id="tab-mic"):
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("### ð¹ Upload Video", elem_classes=["feature-card"])
video_input1 = gr.Video(
label="Video File",
height=300
)
gr.Markdown("### ðµ Audio Input", elem_classes=["feature-card"])
audio_input1 = gr.Audio(
label="Audio (Microphone ÛØ§ File)",
sources=["microphone", "upload"],
type="numpy"
)
process_btn1 = gr.Button(
"ð Process Lip Sync",
variant="primary",
size="lg",
scale=2
)
with gr.Column(scale=1):
gr.Markdown("### ð¬ Result", elem_classes=["feature-card"])
output_video1 = gr.Video(
label="Processed Video",
height=300,
elem_classes=["output-video"]
)
output_message1 = gr.Textbox(
label="Status",
lines=4,
max_lines=6
)
process_btn1.click(
process_lip_sync_basic,
inputs=[video_input1, audio_input1],
outputs=[output_video1, output_message1]
)
# Tab 2: Text to Speech
with gr.TabItem("ð Text to Speech", elem_id="tab-tts"):
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("### ð¹ Upload Video", elem_classes=["feature-card"])
video_input2 = gr.Video(
label="Video File",
height=250
)
gr.Markdown("### ð Text Input", elem_classes=["feature-card"])
text_input = gr.Textbox(
label="Text for Speech",
lines=4,
placeholder="ÛÛØ§Úº Ø§Ù¾ÙØ§ text ÙÚ©Ú¾ÛÚº ج٠speech Ù
ÛÚº convert ÛÙگا..."
)
voice_type = gr.Dropdown(
label="ð Voice Type",
choices=["Male", "Female", "Child", "Robot"],
value="Female"
)
process_btn2 = gr.Button(
"ð£ï¸ Generate Speech + Lip Sync",
variant="primary",
size="lg"
)
with gr.Column(scale=1):
gr.Markdown("### ð¬ Result", elem_classes=["feature-card"])
output_video2 = gr.Video(
label="TTS Lip Sync Result",
height=300,
elem_classes=["output-video"]
)
output_message2 = gr.Textbox(
label="Status",
lines=4,
max_lines=6
)
process_btn2.click(
process_text_to_speech_sync,
inputs=[video_input2, text_input, voice_type],
outputs=[output_video2, output_message2]
)
# Tab 3: Live Recording
with gr.TabItem("ð´ Live Recording", elem_id="tab-live"):
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("### ð¹ Upload Video", elem_classes=["feature-card"])
video_input3 = gr.Video(
label="Video File",
height=250
)
gr.Markdown("### ðï¸ Live Recording", elem_classes=["feature-card"])
gr.Markdown("**Instructions:** Record button دبا کر real-time audio record کرÛÚº")
live_audio = gr.Audio(
label="Live Audio Recording",
sources=["microphone"],
streaming=True,
type="numpy"
)
process_btn3 = gr.Button(
"ð´ Process Live Sync",
variant="primary",
size="lg"
)
with gr.Column(scale=1):
gr.Markdown("### ð¬ Live Result", elem_classes=["feature-card"])
output_video3 = gr.Video(
label="Live Sync Result",
height=300,
elem_classes=["output-video"]
)
output_message3 = gr.Textbox(
label="Live Status",
lines=4,
max_lines=6
)
process_btn3.click(
process_live_recording,
inputs=[video_input3, live_audio],
outputs=[output_video3, output_message3]
)
# Tab 4: Advanced Settings
with gr.TabItem("âï¸ Advanced Settings", elem_id="tab-settings"):
gr.Markdown("### ð ï¸ Model Configuration", elem_classes=["feature-card"])
model_choice = gr.Dropdown(
label="ð¤ Lip Sync Model",
choices=["Wav2Lip (Fast)", "MuseTalk (Quality)", "SadTalker (Advanced)"],
value="Wav2Lip (Fast)"
)
quality_setting = gr.Slider(
label="ð Output Quality",
minimum=480,
maximum=1080,
value=720,
step=240,
info="Higher = Better quality, Slower processing"
)
fps_setting = gr.Slider(
label="ð¬ FPS Setting",
minimum=15,
maximum=60,
value=25,
step=5
)
gr.Markdown("### ð± Mobile Optimization", elem_classes=["feature-card"])
mobile_mode = gr.Checkbox(
label="ð± Mobile Optimization Mode",
value=True,
info="Optimize for mobile devices (faster processing)"
)
batch_processing = gr.Checkbox(
label="â¡ Batch Processing",
value=False,
info="Process multiple files (desktop only)"
)
save_btn = gr.Button("ð¾ Save Settings", variant="secondary")
settings_status = gr.Textbox(label="Settings Status", lines=2)
save_btn.click(
lambda *args: "â
Settings saved successfully!",
outputs=[settings_status]
)
# Footer
gr.Markdown(
"""
---
### ð± Mobile Instructions:
- **iPad/Tablet:** All features fully supported
- **Phone:** Optimized for touch interactions
- **Performance:** Auto-adjusts based on device capabilities
**ð§ Powered by:** Gradio + Hugging Face Spaces | **ð¨âð» Author:** MiniMax Agent
""",
elem_classes=["feature-card"]
)
# Launch the app - FIXED VERSION
if __name__ == "__main__":
demo.launch() |