gemenerik / gap8-obstacle-avoidance Goto Github PK

Hello @gemenerik,

I want people to be able to recreate your project more easily.

Therefore I want to write a clear and concise easy-to-follow guide on how to get the obstacle avoidance running. This includes the implementation on the crazyfly itself.

Judging by the date of the blog post one year has passed from your original implementation? I am aware that you might have forgotten some stuff. Nonetheless I would like to schedule a short (teams, discord, zoom) call with you (the shorter the better...1 hour maximum) for the beginning of the next week (Monday, Tuesday or Wednesday) so we can make an outline of the instructions. You don't have to, but the people reading the instructions and I would very much appreciate it :)

I will have access to the crazyflies only until the end of next week. I really want this to work.

It would be said to see your project not being implemented by more people. I genuinely think this is amazing.

Best regards

Hello @gemenerik,

I watched the ai deck workshop 1 giving some insight into flashing onto the ai deck.

I moved nanoflownet_unquantized.json into the BUILD_MODEL directory as needed to overcome this error:
FileNotFoundError: [Errno 2] No such file or directory: 'BUILD_MODEL/nanoflownet_unquantized.json'

Running make all in the gap8-obstacle-avoidance directory I got this error:
ModuleNotFoundError: No module named 'stats'

This was fixed by adding the path of the nntools to the pythonpath, making the nntool stats python package available:
export PYTHONPATH=$PYTHONPATH:~/repo/gap_sdk/tools/nntool/nntool

Now I run into this error when I make all:
nntool.quantization.range_provider.RangesMissingError: no ranges found for DEPTHWISE_CONV_2D_0_128

Hello,

I want to get the NanoFlowNet running on the AI deck for obstacle avoidance. The following shows an older version of nntool_script.

What were the pictures displaying (e.g. samples/img_OUT_7_a.ppm)? What are the images supposed to display?
Since these are used for quantization, they should represent typical inputs for the neural network?

I have collected images from the crazyflie's wifi video stream.
Following which rule would you group the images into pairs?

Which file format is needed?
Does it have to be .ppm file format?
I have looked at the nntools data_importer.py. Seems like most are accepted.

I am learning. Questions might seem dumb.

Thank you!