-
Download
install.sh
(Linux/macOS) orinstall.ps1
(Windows) from https://raw.githubusercontent.com/guglielmopescatore/filmocredit-pipeline/refactoring-monorepo/ -
Create a folder where you want to install FilmoCredit and place the downloaded script there.
-
Open a terminal and run the script:
- Linux/macOS:
chmod +x install.sh && ./install.sh
- Windows:
powershell -ExecutionPolicy Bypass -File install.ps1
- Linux/macOS:
-
Activate the virtual environment:
- Linux/macOS:
source FilmoCredit/.venv/bin/activate
- Windows:
.\FilmoCredit\.venv\Scripts\activate
(or, if you are in the FilmoCredit folder, you can run 'source .venv/bin/activate' on Linux/macOS or '.venv\Scripts\activate' on Windows)
- Linux/macOS:
-
Create the .env file in the FilmoCredit folder with your Azure AI credentials (see below for details).
-
Run FilmoCredit on Stremlit:
- Linux/macOS:
streamlit run FilmoCredit/app.py
- Windows:
streamlit run FilmoCredit\app.py
(or, if you are in the FilmoCredit folder, you can run 'streamlit run app.py' directly) s
- Linux/macOS:
FilmoCredit installs in the same directory where you run the installer:
📁 Your-Folder/
├── 📄 install.ps1 (or install.sh) # The installer script
├── 📄 run-filmocredit.bat/.sh # Runner (created automatically)
└── 📁 FilmoCredit/ # Installation directory (created automatically)
├── 📁 .venv/ # Virtual environment
├── 📄 app.py # FilmoCredit application
└── 📄 FilmoCredit.bat # Launcher
- Platform: Windows, Linux, macOS
- Python Version: Requires Python 3.9+
- GPU Support: Automatically detects NVIDIA GPU and CUDA
- Dependencies: Installs PyTorch, PaddleOCR, and other requirements
- GPU Version: If NVIDIA GPU + CUDA 12.6 detected
- CPU Version: If no GPU/CUDA detected
- Self-Contained: Creates isolated virtual environment
For GPU acceleration, install before running the installer:
- NVIDIA GPU with 4GB+ VRAM
- Latest NVIDIA drivers
- CUDA 12.6 from NVIDIA website
Most systems already have these, but install if missing:
- Python 3.11+ (preferably 3.11) from python.org
- On Windows: Check "Add Python to PATH" during installation
- Git from git-scm.com
Place your video files in: FilmoCredit/data/raw/
You will already find a sample video named TEST.mp4 in the data/raw
folder to let you test the software.
Supported formats: .mp4
, .mkv
, .avi
, .mov
- Download:
name.basics.tsv.gz
from https://datasets.imdbws.com/ - Extract the file: Open and extract the content from the archive: you will get a file named
name.basics.tsv
- Place: The extracted
name.basics.tsv
file inFilmoCredit/db/
The system currently works only with Azure AI models. Create a .env
file in the FilmoCredit/
root folder with your Azure credentials:
📁 FilmoCredit/
├── 📄 .env # ← Azure AI configuration file
├── 📁 data/raw/ # ← Video files
└── 📁 db/ # ← IMDB database
└── name.basics.tsv
The .env
file should contain:
AZURE_OPENAI_KEY=your_azure_openai_key
AZURE_OPENAI_ENDPOINT=your_azure_endpoint
AZURE_OPENAI_API_VERSION=2023-12-01-preview
AZURE_OPENAI_DEPLOYMENT_NAME=your_deployment_name
Run the installer again to update to the latest version.
# Linux/macOS
./install.sh --force
# Windows
./install.ps1 -Force
# Linux/macOS
GPU_AVAILABLE=false ./install.sh
# Windows
# Edit install.ps1 and set $hasGPU = $false
Most systems include Python, but if not detected:
- Install Python 3.11+ from python.org
- On Windows: Check "Add Python to PATH" during installation
chmod +x install.sh
# If needed: sudo apt install python3 python3-pip python3-venv
- Install NVIDIA drivers
- Install CUDA 12.6
- Verify with
nvidia-smi
- OS: Windows 10, macOS 10.15, Linux (Ubuntu 18.04+)
- RAM: 4GB (8GB recommended)
- Storage: 2GB free space
- Python: 3.11+
- GPU: NVIDIA GPU with 4GB+ VRAM
- CUDA: Version 12.6
- Drivers: Latest NVIDIA drivers
For issues:
- Check the Issues page
- Run installer with verbose output:
bash -x install.sh
- Include system info and error messages when reporting bugs