Moved Music_Splitter contents into the main repository

.gitattributes

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-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ckpt filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
-*.joblib filter=lfs diff=lfs merge=lfs -text
-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.mlmodel filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.npy filter=lfs diff=lfs merge=lfs -text
-*.npz filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
-*.pb filter=lfs diff=lfs merge=lfs -text
-*.pickle filter=lfs diff=lfs merge=lfs -text
-*.pkl filter=lfs diff=lfs merge=lfs -text
-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-*.safetensors filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tar filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
-*.tgz filter=lfs diff=lfs merge=lfs -text
-*.wasm filter=lfs diff=lfs merge=lfs -text
-*.xz filter=lfs diff=lfs merge=lfs -text
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-*tfevents* filter=lfs diff=lfs merge=lfs -text

.gitignore

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+__pycache__/
+*.pyc
+.env

.gitmodules

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+[submodule "Music_Splitter"]
+	path = Music_Splitter
+	url = https://huggingface.co/spaces/Omar-youssef/Music_Splitter

.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml
+# Editor-based HTTP Client requests
+/httpRequests/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml

.idea/.name

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+app.py

.idea/audio_splitter.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/.venv" />
+    </content>
+    <orderEntry type="jdk" jdkName="Python 3.9 virtualenv at C:\Users\abdom\PycharmProjects\pushToHuggingface\.venv" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.9 (audio_splitter)" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9 virtualenv at C:\Users\abdom\PycharmProjects\pushToHuggingface\.venv" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/audio_splitter.iml" filepath="$PROJECT_DIR$/.idea/audio_splitter.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+    <mapping directory="$PROJECT_DIR$/Music_Splitter" vcs="Git" />
+  </component>
+</project>

Dockerfile

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+# Use Python 3.9 as base image
+FROM python:3.9-slim
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    ffmpeg \
+    && rm -rf /var/lib/apt/lists/*
+
+# Set working directory
+WORKDIR /app
+
+# Copy requirements first to leverage Docker cache
+COPY requirements.txt .
+
+# Install Python dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the application code
+COPY . .
+
+# Expose the port Streamlit runs on
+EXPOSE 8501
+
+# Command to run the application
+CMD ["streamlit", "run", "main.py", "--server.address", "0.0.0.0"]

README.md

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----
-title: Music Splitter
-emoji: 📈
-colorFrom: pink
-colorTo: gray
-sdk: streamlit
-sdk_version: 1.41.1
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🎵 Audio/Video Music Splitter
+
+A Streamlit-based web application that allows users to separate vocals from audio files and videos. This tool uses the Demucs model for high-quality audio source separation.
+
+![Screenshot 2025-01-10 150722](https://github.com/user-attachments/assets/5d74204f-0c54-44c3-acb9-e3eaa633ded7)
+
+
+## 🌟 Features
+
+- **Audio Processing**: Extract vocals from audio files (MP3, WAV, OGG)
+- **Video Processing**: Separate vocals from video files (MP4, MKV, AVI)
+- **Download Options**: 
+  - Download isolated vocals
+  - Download processed video with isolated vocals
+- **User-Friendly Interface**: Simple drag-and-drop file upload
+- **Multiple Format Support**: Works with various audio and video formats
+
+## 🚀 Getting Started
+
+### Prerequisites
+
+- Docker installed on your system
+- At least 4GB of available RAM
+- 2GB of free disk space
+
+### Quick Start with Docker
+
+1. Clone the repository:
+```bash
+git clone https://github.com/yourusername/Omar-YYoussef-Audio_Video_Music_Splitter.git
+cd Omar-YYoussef-Audio_Video_Music_Splitter
+```
+
+2. Build the Docker image:
+```bash
+docker build -t audio-video-splitter .
+```
+
+3. Run the container:
+```bash
+docker run -p 8501:8501 audio-video-splitter
+```
+
+4. Open your browser and navigate to:
+```
+http://localhost:8501
+```
+
+### Manual Installation
+
+1. Install system dependencies:
+```bash
+# Ubuntu/Debian
+sudo apt-get update && sudo apt-get install -y ffmpeg
+
+# MacOS
+brew install ffmpeg
+
+# Windows
+# Download and install ffmpeg from https://ffmpeg.org/download.html
+```
+
+2. Install Python dependencies:
+```bash
+pip install -r requirements.txt
+```
+
+3. Run the application:
+```bash
+streamlit run main.py
+```
+
+## 💡 Usage
+
+### Processing Audio Files
+
+1. Select the "Audio Processing 🎧" tab
+2. Upload your audio file (MP3, WAV, or OGG format)
+3. Click "Process Audio"
+4. Download the separated vocals
+
+### Processing Video Files
+
+1. Select the "Video Processing 🎥" tab
+2. Upload your video file (MP4, MKV, or AVI format)
+3. Click "Process Video"
+4. Download either:
+   - The processed video with isolated vocals
+   - The separated vocals as an audio file
+
+![Screenshot 2025-01-10 150909](https://github.com/user-attachments/assets/755dc95c-bbeb-4356-a3af-2c2694cd5fd8)
+
+
+## 🔧 Technical Details
+
+The application uses several key technologies:
+
+- **Streamlit**: For the web interface
+- **Demucs**: For audio source separation
+- **FFmpeg**: For audio/video processing
+- **Python 3.9**: As the base programming language
+
+
+## 🤝 Contributing
+
+1. Fork the repository
+2. Create your feature branch (`git checkout -b feature/AmazingFeature`)
+3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)
+4. Push to the branch (`git push origin feature/AmazingFeature`)
+5. Open a Pull Request
+
+## 📝 License
+
+This project is licensed under the MIT License - see the LICENSE file for details.
+
+## 👏 Acknowledgments
+
+- [Demucs](https://github.com/facebookresearch/demucs) for the audio separation model
+- [Streamlit](https://streamlit.io/) for the web app framework
+- [FFmpeg](https://ffmpeg.org/) for media processing capabilities
+

app.py

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+import streamlit as st
+import tempfile
+import os
+from pathlib import Path
+from video_processor import VideoProcessor
+from audio_processor import AudioProcessor
+
+# Utility functions
+def save_uploaded_file(uploaded_file, temp_dir):
+    file_path = Path(temp_dir) / uploaded_file.name
+    with open(file_path, 'wb') as f:
+        f.write(uploaded_file.read())
+    return file_path
+
+def download_file_button(file_path, label, file_name, mime_type):
+    with open(file_path, 'rb') as f:
+        st.download_button(
+            label=label,
+            data=f.read(),
+            file_name=file_name,
+            mime=mime_type
+        )
+
+def process_audio(audio_file):
+    with tempfile.TemporaryDirectory() as temp_dir:
+        # Save uploaded file
+        input_path = save_uploaded_file(audio_file, temp_dir)
+
+        # Create output directory
+        output_dir = Path(temp_dir) / "output"
+        output_dir.mkdir(exist_ok=True)
+
+        with st.spinner("Processing audio..."):
+            try:
+                audio_proc = AudioProcessor(input_path, output_dir)
+
+                # Run Demucs
+                if not audio_proc.run_demucs():
+                    raise RuntimeError("Demucs processing failed.")
+
+                # Retrieve processed files
+                vocals_path = audio_proc.get_vocals_path()
+                no_vocals_path = audio_proc.get_no_vocals_path()
+
+                if not vocals_path or not no_vocals_path:
+                    raise FileNotFoundError("Processed files not found.")
+
+                # Download buttons
+                col1, col2 = st.columns(2)
+                download_file_button(vocals_path, "Download Vocals", f"vocals_{audio_file.name.rsplit('.', 1)[0]}.wav", "audio/wav")
+               # download_file_button(no_vocals_path, "Download Instrumental", f"instrumental_{audio_file.name.rsplit('.', 1)[0]}.wav", "audio/wav")
+
+                st.success("Audio processing completed!")
+
+            except Exception as e:
+                st.error(f"An error occurred: {str(e)}")
+
+def process_video(video_file):
+    with tempfile.TemporaryDirectory() as temp_dir:
+        # Save uploaded file
+        input_path = save_uploaded_file(video_file, temp_dir)
+
+        # Create output directory
+        output_dir = Path(temp_dir) / "output"
+        output_dir.mkdir(exist_ok=True)
+
+        with st.spinner("Processing video..."):
+            try:
+                # Extract audio from video
+                video_proc = VideoProcessor(input_path, output_dir)
+                audio_path = video_proc.extract_audio()
+                if not audio_path:
+                    raise RuntimeError("Audio extraction from video failed.")
+
+                # Process extracted audio
+                audio_proc = AudioProcessor(audio_path, output_dir)
+                if not audio_proc.run_demucs():
+                    raise RuntimeError("Demucs processing failed.")
+
+                # Retrieve processed audio files
+                vocals_path = audio_proc.get_vocals_path()
+                no_vocals_path = audio_proc.get_no_vocals_path()
+                if not vocals_path or not no_vocals_path:
+                    raise FileNotFoundError("Processed audio files not found.")
+
+                # Combine video with vocals
+                final_video_path = video_proc.combine_video_audio(vocals_path)
+
+                # Download buttons
+                col1, col2, col3 = st.columns(3)
+                if final_video_path:
+                    download_file_button(final_video_path, "Download Processed Video", f"processed_{video_file.name}", "video/mp4")
+                download_file_button(vocals_path, "Download Vocals", f"vocals_{video_file.name.rsplit('.', 1)[0]}.wav", "audio/wav")
+                #download_file_button(no_vocals_path, "Download Instrumental", f"instrumental_{video_file.name.rsplit('.', 1)[0]}.wav", "audio/wav")
+
+                st.success("Video processing completed!")
+
+            except Exception as e:
+                st.error(f"An error occurred: {str(e)}")
+
+# Streamlit App Layout
+st.title("🎵 Audio/Video Vocal Separator")
+
+# Tabs for different processing types
+tab1, tab2 = st.tabs(["Audio Processing 🎧", "Video Processing 🎥"])
+
+with tab1:
+    st.header("Process Your Audio File")
+    with st.expander("Instructions", expanded=True):
+        st.markdown("""
+        1. Upload an audio file in MP3, WAV, or OGG format.
+        2. Click the **Process Audio** button.
+        3. Download the separated vocals.
+        """)
+    audio_file = st.file_uploader("Upload your audio file", type=['mp3', 'wav', 'ogg'])
+    if audio_file and st.button("Process Audio"):
+        process_audio(audio_file)
+
+with tab2:
+    st.header("Process Your Video File")
+    with st.expander("Instructions", expanded=True):
+        st.markdown("""
+        1. Upload a video file in MP4, MKV, or AVI format.
+        2. Click the **Process Video** button.
+        3. Download the processed video or vocals.
+        """)
+    video_file = st.file_uploader("Upload your video file", type=['mp4', 'mkv', 'avi'])
+    if video_file and st.button("Process Video"):
+        process_video(video_file)
+
+# Footer
+st.markdown("""
+---
+Made with ❤️ using [Streamlit](https://streamlit.io)
+""")

audio_processor.py

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+from pathlib import Path
+import subprocess
+
+class AudioProcessor:
+    def __init__(self, input_audio, output_dir):
+        self.input_audio = Path(input_audio)
+        self.output_dir = Path(output_dir)
+        self.output_dir.mkdir(parents=True, exist_ok=True)
+
+    def run_demucs(self):
+        """Process audio using Demucs to separate vocals"""
+        try:
+            # Use default model (htdemucs) without MP3 output to avoid diffq dependency
+            subprocess.run([
+                "demucs",
+                "--two-stems=vocals",
+                "-o", str(self.output_dir),
+                str(self.input_audio)
+            ], check=True)
+            print("Demucs processing completed successfully")
+            return True
+        except subprocess.CalledProcessError as e:
+            print(f"Error during Demucs execution: {e}")
+            return False
+
+    def get_vocals_path(self):
+        """Get path to the separated vocals file"""
+        # Path for htdemucs model output
+        vocals_path = self.output_dir / "htdemucs" / Path(self.input_audio.stem) / "vocals.wav"
+        if vocals_path.exists():
+            print(f"Vocals found at: {vocals_path}")
+            return str(vocals_path)
+        print("Vocals file not found")
+        return None
+
+    def get_no_vocals_path(self):
+        """Get path to the no-vocals (instrumental) file"""
+        # Path for htdemucs model output
+        no_vocals_path = self.output_dir / "htdemucs" / Path(self.input_audio.stem) / "no_vocals.wav"
+        if no_vocals_path.exists():
+            print(f"No-vocals track found at: {no_vocals_path}")
+            return str(no_vocals_path)
+        print("No-vocals file not found")
+        return None
+
+    def cleanup(self):
+        """Remove temporary audio files"""
+        if self.input_audio.exists():
+            self.input_audio.unlink()
+        print("Temporary audio files cleaned up")

requirements.txt

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+streamlit>=1.24.0
+demucs
+ffmpeg-python
+pathlib

video_processor.py

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+from pathlib import Path
+import subprocess
+
+class VideoProcessor:
+    def __init__(self, input_video, output_dir):
+        self.input_video = Path(input_video)
+        self.output_dir = Path(output_dir)
+        self.output_dir.mkdir(parents=True, exist_ok=True)
+        self.temp_audio = self.output_dir / "extracted_audio.wav"
+        self.final_video = self.output_dir / "final_video.mp4"
+
+    def extract_audio(self):
+        """Extract audio from video file"""
+        try:
+            subprocess.run([
+                "ffmpeg", "-i", str(self.input_video),
+                "-vn", "-acodec", "pcm_s16le", "-ar", "44100",
+                str(self.temp_audio)
+            ], check=True)
+            print(f"Audio extracted successfully to {self.temp_audio}")
+            return str(self.temp_audio)
+        except subprocess.CalledProcessError as e:
+            print(f"Error extracting audio: {e}")
+            return None
+
+    def combine_video_audio(self, vocals_path):
+        """Combine original video with vocals only"""
+        try:
+            subprocess.run([
+                "ffmpeg",
+                "-i", str(self.input_video),
+                "-i", vocals_path,
+                "-c:v", "copy",
+                "-c:a", "aac",
+                "-map", "0:v:0",
+                "-map", "1:a:0",
+                str(self.final_video)
+            ], check=True)
+            return str(self.final_video)
+        except subprocess.CalledProcessError as e:
+            print(f"Error combining video and audio: {e}")
+            return None