Image segmentation with raspberry pi - raspberry-pi

I have been trying to perform image segmentation with raspberry Pi. I searched for different pre-trained models to perform it and came across tensorflow lite, it has a deeplab model in it, it is very less in size (2.7 Mb) and can be used for IOT devices. But in my case, I have a custom dataset and I need to train the model on my dataset (i.e training deeplab with custom dataset). My issue is raspberry Pi has less RAM and storage (comparatively). So, if I train deeplab with the custom dataset, can I run it on raspberry Pi. If so, is there any tutorial or a research paper about it?

You can use this training script. Clone the repository and run model.py from model/research/deeplab.
I wouldn´t train the model on the Raspberry Pi, because it´s damn slow. A better approach would be to train it on a PC (maybe with GPU support) and export the model to the Raspberry Pi.

Related

Deploy my own quantized model on Raspberry Pi

I am facing a problem about deploying the quantized model on Raspberry Pi.
I build my own model and convert it by the TensorFlow Lite. In this case, how could I deploy this quantized model to Rasberry, or is it possible to deploy my own created model?
Thank for helps!
I was struggling deploying the quantized model on Rasberry Pi, however, some online blogs said must used the pretrained one. SO I was wondering how could I solve this problem.

How to load custom image segmentation tensorflow lite model in raspberry pi 3 B?

I build my own custom tensorflow lite model. Now I want to deploy in on my raspberry pi to segment images. Can anyone help me with this problem. How do i proceed to complete this task?

How to train a neural network using intel integrated graphics

My computer has a Intel Xeon E3-1200 v2/3rd Gen Core processor Graphics Controller. I want to train a neural network using the integrated graphics. There is no need for speed-up. What should I do?
Since Keras use Tensorflow under the hood Tensorflow's GPU support needs Nvidia Cuda and CuDNN packages installed. For GPU accelerated training you will need a dedicated GPU. Intel onboard graphics can't be used for that purpose.
You can check the support https://www.tensorflow.org/install/gpu

Is it possible to run ARCore on Raspberry pi 3?

Is it possible to run ARCore on Raspberry pi 3? It seems it possible to run Android on Raspberry but it's not clear am I able to run ARCore here.
No, Rasberry pi has no camera and no IMU and even if you would add them yourself, it is highly unlikely that Google would provide a calibration for it.
This calibration is needed to understand how to interprete IMU measurements and camera features and translate them into translation and rotation

delay/slow lve streaming video in Simulink using Raspberry Pi camera

I have a Pi camera module which is attached to pi B board. I am streaming the Live video from Pi camera into Pc Simulink via Edimax Wifi Adaptor Using Router.
By using 10fps and res 320*240, I am facing delay into my Simulink video viewer. Why this delay happens either the speed or range of wifi adaptor or my Laptop processor (i have intel i3 with 4gb RAM 2.4GHZ)
Is there is the way to the reduce the delay?
Since you are using low image resolution and frame-rate, the only reason you are experiencing such delay can be the limited bandwidth of the WiFi.
If you can, try to wire the Raspberry Pi with an Ethernet connection, you will considerably increase the bandwidth and reduce potential delays of the video transmission.