Installing OpenCV, TensorFlow Lite, and Mediapipe on Raspberry Pi
If you’re looking to do some machine learning or computer vision projects on your Raspberry Pi, you’ll need to install OpenCV, TensorFlow Lite, and Mediapipe. These libraries will allow you to work with images, videos, and AI models on your Raspberry Pi.
Installing OpenCV
OpenCV is a popular library for computer vision tasks. To install OpenCV on your Raspberry Pi, you can use the following commands:
sudo apt-get update sudo apt-get install libopencv-dev python3-opencv
Installing TensorFlow Lite
TensorFlow Lite is a lightweight version of TensorFlow that is optimized for running on mobile and edge devices like the Raspberry Pi. To install TensorFlow Lite, you can use the following commands:
pip3 install --extra-index-url https://google-coral.github.io/py-repo tflite_runtime
Installing Mediapipe
Mediapipe is a machine learning framework developed by Google that allows you to build complex pipelines for processing multimedia data. To install Mediapipe on your Raspberry Pi, you can use the following commands:
pip3 install mediapipe
Using OpenCV, TensorFlow Lite, and Mediapipe
Once you have installed these libraries on your Raspberry Pi, you can start using them in your projects. For example, you can use OpenCV to process images and videos, TensorFlow Lite to run AI models, and Mediapipe to build complex pipelines for multimedia processing.
By combining these libraries, you can create powerful computer vision and machine learning applications on your Raspberry Pi. Have fun experimenting with these tools and building cool projects!
Hi, the bullseye version is only available on legacy systems. Does it work the same way?
thank you so much. its work. you save my time💪🧡
Thanks sir. I take much time to install opencv and it's don't work. But, I forget that i am using os 32 bit. Therefore i use 64 bit and it worked. Thank u so much!
Hello teacher!
Does this installation of OPENCV work well for an easy recognition program? No need build installation?
Please make a video on how to do a custom object detection in tensor flow lite.Your prevoius videos seems to get error due to compatibility issue
But that was showing 32bit?!!