Simple image classification (persons, animals, other) on raspberry pi using custom model tflite (output to terminal), using TensorFlow Lite
Short summary:
In this article, I will explain how to create a solution for simple image classification (persons, animals, others) on raspberry pi using a custom model tflite (output to terminal).
I will use a custom model tflite which I converted from h5.
And all results will be shown in the terminal. Code for this article is available here.
Note before you start:
So, let’s start :)
Hardware preparation:
Software preparation:
1. Create a neural network model to predict 3 classes persons, animals, others.
I have already done it in the article below. So in this article, you do not need to do this.
2 Convert h5 model to tflite model
I have already done it in the article below. So in this article, you do not need to do this.
3 So, let’s implement our model to Simple image classification (persons, animals, other) on raspberry pi using custom model tflite (output to terminal)
For that, you need to run the next code:
#clone my repo
git clone https://github.com/oleksandr-g-rock/image_lassify_tflite_simple.git#go to folder
cd image_lassify_tflite_simple#download tflite model
wget https://github.com/oleksandr-g-rock/how_to_convert_h5_model_to_tflite/raw/main/animall_person_other_v2_fine_tuned.tflite#run script
python3 classify_image_used_tflite.py
4 You should see something like that.
Result:
In this article, we created a solution for simple image classification (persons, animals, others) on raspberry pi using custom model tflite (output to terminal).
I using a custom model tflite which I converted from h5.
And all results will be shown in the terminal. Code for this article is available here.
