vlm-inference 0.1.36

Vision language models for robotics

vlm_inference

This repository contains code for performing inference using a Vision-Language Model (VLM) for robotic navigation tasks.

Setup Instructions

Follow these steps to use the library, it is already available by PyP:

1. Intall library:

Here you have two options, install twrought the PyP:

    pip install openai==1.78.1 opencv-python==4.11.0.86 pyyaml dotenv==0.9.9 pillow==9.0.1

    pip install vlm_inference

You can try the library in action using this Colab notebook:
📎

Install since the repostitory:

    git clone ssh://[e-mail]:2202/mobile_robotics/moonshot_project/vlm/vlm_inference.git

    cd vlm_inference

    python3 pip install -r requirements.txt

Install by the repository

    pip install -e .

2. Create a .env file and add your OpenAI API key and the VLM configuration path:

   Create a file named .env in the root directory of the repository and add the following content, replacing sk-proj-_HFJE2I64........... with your actual OpenAI API key and ensuring the VLM_CONFIG_PATH points to your configuration file:

    # .env
    OPENAI_API_KEY=sk-proj-_HFJE2I64...........
    VLM_CONFIG_PATH=vlm_inference/config.yaml

If you have can´t not modify the python version use the following command:

    python3 pip install -r requirements.txt

5. Set the navigation goal (optional):

   If you want to specify a navigation goal as an object or person with a description, open the following file:

    vlm_navigation/prompt_manager/navigation_prompt.txt

Locate line 7, which defines the `navigation_goal` variable, and modify it according to your desired goal. For example:

    navigation_goal = "a red chair near the window"

6. Run the inference script:

   Execute the main inference script using Python 3:

    python3 vlm_navigation/inference.py

This script will load the VLM, potentially process images (depending on the script's functionality), and output the inference results based on the configuration and any specified navigation goal.