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https://github.com/muhfaridansutariya/llava-1.5-liveness-7b
Resigned Yann-LeCun
https://github.com/muhfaridansutariya/llava-1.5-liveness-7b
gradio llava openai
Last synced: 14 days ago
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Resigned Yann-LeCun
- Host: GitHub
- URL: https://github.com/muhfaridansutariya/llava-1.5-liveness-7b
- Owner: MuhFaridanSutariya
- Created: 2024-05-04T15:28:44.000Z (8 months ago)
- Default Branch: master
- Last Pushed: 2024-06-10T13:57:44.000Z (6 months ago)
- Last Synced: 2024-06-10T15:30:17.634Z (6 months ago)
- Topics: gradio, llava, openai
- Language: Jupyter Notebook
- Homepage:
- Size: 522 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Llava-1.5-Liveness-7b : A Vision Language Model for Liveness Detection
- Team Leader: [Firqa Aqila Noor Arasyi](https://github.com/firqaaa)
- Team Member: [Muhammad Hasnan Ramadhan](https://github.com/hasnanmr), [Muhammad Faridan Sutariya](https://github.com/MuhFaridanSutariya) and [Rasyidan Akbar Fayrussani](https://github.com/0xrsydn)
## Vision Language Model Workflow for User Registration and Inference
## Hardware Requirements for Efficient Model Inference
### RAM Requirements:
- **Minimum 32GB of RAM:** Provides sufficient memory to handle the large datasets and model parameters during inference, ensuring smooth and efficient data processing.
### VRAM Requirements:
- **Minimum 24GB of VRAM:** Ensures the GPU can effectively manage the high computational and memory demands of the model, facilitating faster and more efficient inference operations.
## How to run
### 1. Clone this repository
To get started, clone this repository onto your local machine. Follow the instructions below:
1. Open a terminal or Command Prompt.
2. Change to the directory where you want to clone the repository.
3. Enter the following command to clone the repository:
```bash
git clone https://github.com/MuhFaridanSutariya/llava-1.5-liveness-7b.git
```
4. Once the cloning process is complete, navigate into the cloned directory using the `cd` command:
```bash
cd llava-1.5-liveness-7b
```
### 2. System Requirements
Make sure your system meets the following requirements before proceeding:
- Python 3.10+ is installed on your computer.
- Pip (Python package installer) is installed.
### 3. Create a Virtual Environment
A virtual environment will allow you to separate this project from the global Python installation. Follow these steps to create a virtual environment:
**On Windows:**
Open Command Prompt and enter the following command:
```bash
python -m venv virtualenv_name
```
Replace `virtualenv_name` with the desired name for your virtual environment.
**On macOS and Linux:**
Open the terminal and enter the following command:
```bash
python3 -m venv virtualenv_name
```
Replace `virtualenv_name` with the desired name for your virtual environment.
### 4. Activate the Virtual Environment
After creating the virtual environment, you need to activate it before installing the requirements. Use the following steps:
**On Windows:**
In Command Prompt, enter the following command:
```bash
virtualenv_name\Scripts\activate
```
Replace `virtualenv_name` with the name you provided in the previous step.
**On macOS and Linux:**
In the terminal, enter the following command:
```bash
source virtualenv_name/bin/activate.bat
```
Replace `virtualenv_name` with the name you provided in the previous step.
### 5. Install Requirements
Once the virtual environment is activated, you can install the project requirements from the `requirements.app.txt` file. Follow these steps:
**On Windows, macOS, and Linux:**
In the activated virtual environment, navigate to the directory where the `requirements.app.txt` file is located. Then, enter the following command:
```bash
pip install -r requirements.app.txt
```
This command will install all the required packages specified in the `requirements.app.txt` file
### 6. Run Gradio
How to run Web App:
``python frontend/app.py``
## Reference
- [Blog Tutorial Finetuning Vision Language Model](https://huggingface.co/blog/vlms)
- [Base Vision Language Model](https://huggingface.co/llava-hf/llava-1.5-7b-hf)
- [Paper Vision Language Model](https://arxiv.org/abs/2304.08485)