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Hailo-10H AI HAT +2📖
1.Product Introduction
  • Product Introduction
2. Local Deployment Tutorial for LLM and VLM
  • 1. Environment Installation
  • 2. Text-based interactive LLM
  • 3. Visual and text interaction VLM
3. AI Vision Model Acceleration Tutorial
  • 1. Environment Setup
  • 2. rpicam-apps
  • 3.Test case
  • 4. Instance segmentation
  • 5.Pose estimation
  • 6.Segmented application
  • 7.Monocular depth
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Welcome to Hailo-10H AI HAT +2 repository

3. Visual and text interaction VLM

3. Visual and text interaction VLM

3. Visual and text interaction VLM1. Introduction2. StartupInteractive Mode

1. Introduction

An interactive computer vision application using the Hailo Visual Language Model (VLM) for real-time image analysis and question answering.

2. Startup

For USB cameras, run the following command:

python -m hailo_apps.python.gen_ai_apps.vlm_chat.vlm_chat --input usb

If it's a Raspberry Pi CSI camera, run the following command.

xxxxxxxxxx
python -m hailo_apps.python.gen_ai_apps.vlm_chat.vlm_chat --input rpi

Note: After starting the command, you will see a live camera window.

Interactive Mode

  • Click on the terminal and press Enter to capture the current frame and enter question-and-answer mode.

    image-20260130155638415

 

  • Enter a question about capturing images (or press Enter to use the default question).

image-20260130155556589

  • Press Enter to submit your question and get a VLM response.Press Enter again to continue with a new round of questions.

    image-20260130155556589

  • Press Enter again to continue with a new round of questions.

    image-20260130155700894

  • Click on the camera view window, then press the 'q' key in the video window to exit.

For more information on interactive graphic and text content, please refer to: hailo-apps/hailo_apps/python/gen_ai_apps/vlm_chat at main · hailo-ai/hailo-apps · GitHub

Text-based interactive LLM
Environment Setup

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