Error on Raspberry PI 4 while opening TensorFlow.

[arunksoman]

@sreu13 What is the version of tensorflow you are using? Did you read the tensorflow docs? You can't do simply
pip install tensorflow
for Python 3.7 version.

[sreu13]

@arunksoman i installed tensorflow from the below given link

and i installed it without entering into virtual environment

but this 10% memory issue is a serious pain

[sreu13]

@arunksoman tensorflow 2.0.0 version had been installed

[arunksoman]

@sreu13
Ensure that you are installed tensorflow 1.x since screenshot of your code shows something like
from keras.layers.convolution import covolution2D
It is not correct in case for tensorflow 2.0 since keras api is part of tensorflow itself.

Another thing is try to expand your file system. It should be do with your own risk.

1. sudo raspi-config
2. Navigate to Advanced options
3. Select advanced options and hit enter(I believes tab key is useful here)
4. Choose Expand File System and hit enter finish.
5. Then your pi may prompt to reboot. If it didn't run. Execute
   sudo reboot
6. Then execute following commands one by one:

$ sudo apt-get purge wolfram-engine
$ sudo apt-get purge libreoffice*
$ sudo apt-get clean
$ sudo apt-get autoremove

7. Then increase swap memory by editing following file swapfile:
   $ sudo nano /etc/dphys-swapfile
8. It will open nano editor. Navigate to variable

CONF_SWAPSIZE=100

It indicates your current swap is only 100mb.
So you just have to increase by commenting down this line and increase to appropriate value something like shown below for 2GB swap:

#CONF_SWAPSIZE=100
CONF_SWAPSIZE=2048

9. Save the file and exit nano editor.
10. sudo reboot

I believes if it did not helped you, you have to think about MOVIDIUS or NVIDIA Jetson nano etc.

[sreu13]

@arunksoman i'll try this method, but while executing swap command, will the rasbian os and the files it contains be effected??

[arunksoman]

@sreu13 I edited comment please read that again. Most probably it will not effect your file system. In some scenarios it can create worse effect.

[sreu13]

@arunksoman hi,..
actually at this point of time, I'm not willing to risk RPI4,....i thought of connecting the rpi4 to google cloud (already have an account with $300 credit) and proceeding with the code.
but i do not know if the below process can be executed

1. sending image from rpi4 to cloud
2. using this cloud for running prediction
3. the above two processes should be automated and image should be sent to cloud when pi boots up(VM engine can be activated whenever nessesary)

is this possible?

[arunksoman]

@sreu13 It is possible and a far far better method.

[sreu13]

@arunksoman thankyou so much...your reply really busted the stress out of me...can you help with any documentations which i could possibly go through

[salmanfaris]

@sreu13 is the problem solved?