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In a project some data should be stored for later use.
My decision is to use an SD Card, to be open for a lot of data.
Problem is E.connectSDCard, I get an error message.
Somewhere in my mind is a feedback like "you have to build your own binary"
After some jumping through sources, I could see FLASHFS and FILESYSTEM.
This is where some confusions starts with different boardfiles for ESP32
First is ESP32.py having both set
Next is ESP32_IDF4.py where both are commented
And for different boards
ESP32C3_IDF4.py, both are commented
ESP32S3_IDF4.py, only FLASHFS is commentedWhat is the reason for different handling.
What should I do to build a version which supports SD Cards and runs on a standard ESP32 ?
I could use ESP32 WROVER oder WROOM and would prefer the WROVER with additional memory -
@Ganblejs
AFAIK, data is loaded to memory which takes away a lot of vars. Correct me, if I'm wrong.
And I would like to have some more complex gestures.
For example lift the arm and draw a right circle, something like lifting umbrella by tourist guides.
My expectation for complex gestures is much larger file compared to the simple UpDown, LeftRight in my example.
Last not least, if I compare size of EdgeImpuls with nodeconfeu, size of nodeconfeu file is about 30%. Even compared with an JS building, which has 14kb for Keras Model, its a lot. -
played around looks like I had to
- select device to Nordic NRF 52840 DK in the beginning
- ignore that NN stuff
- train without changes
Now I've got a file
TensorFlow Lite (int8 quantized) 22 KB
22KB is a big file for a clock
Anyway, copied this to .tfmodel and created .tfnames
reset bangle2 and checked.
I've 2 gestures (leftright and updown) leftright is recognized perfect
Updown of the clock gives leftright very often.At the end, I got something running, but I'm not really satisfied, because
- steps for EdgeImpuls are complicated, there is no way to automate this
- resulting file is very large, at least in my eyes
- gives wrong results very often
- select device to Nordic NRF 52840 DK in the beginning
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Checked the edge solution and failed.
Could this be a new version ?
Wording and buttons don't match perfect.
Made it up to generated features.
Next step should be train the neural network, but there is no NN Classifier
Should I select another target (tried all nordics, no success) -
Looks to me like Tensorflow itself changed.
And there is a new tflite version, and in sources I found SPACE_TO_BATCH and BATCH_TO_SPACE
I will give EdgeImpuls a try, but this will take some time. -
I tried to create my own gestures. Somehow I got this in github
https://github.com/nearform/nodeconfeu-gesture-models
There is a file create_gesture_model.ipynb which I got running on COLAB
First problem was circular loading around AccelerationReader
Got rid of that by changing directory to nodeconfeu-gesture-models before importing reader and go back
Next problem was in converting to tflite, functions SPACE_TO_BATCH_ND and BATCH_TO_SPACE_ND have been unknown.
Added these commands to builtin_operator_version_support in export_tflite.py
At least I got it working this way. Training etc ran fine.
Next created .tfnames and .tflite and added a handle for aiGesture
Now I get an error Didn't find op for builtin opcode 'SPACE_TO_BATCH_ND'
Is there any idea, what to do or how to do it better ?
Flashfs needs to be disabled to have E.connectSDCard running (see jswrap_file.c)
Comparing the comfort of having a file system for flash memory (storage), and not having the chance to use an SD Card, my winner is SD Card.
Last not least looks to me Flashfs being a special function for ESP32 only.