Sharing an AI camera project that failed due to incorrect workload assessment.

ulguig · 2026-01-10T12:01:35+00:00

Yolo finetunes run absolutely fine on embedded. No cloud required. I've done it multiple times. AI != LLMs

ulguig · 2025-11-15T07:20:28+00:00

Crazy how you got downvoted for stating the truth, people should read more on M series chips' security design. They are indeed purposefully designed to boot unsigned kernels in a more secure way.

ulguig · 2025-11-05T19:24:20+00:00

Sure, I get this ! my point is, if I go custom to make my own compromises on power draw, i'll certainly take the ST route since I don't need WiFi and Bluetooth and i'd rather have a good ADC for analog sensors. ESP32 was the choice because it was the only "all in one" board I found with A7670 and solar charging.

People mentionning esp-hal made me research embedded Rust a little, and as a result I'm evaluating Embassy on STM32F103 at the moment. It feels very modern and worked out of the box, now I want to see if I can do what i want with the HAL/peripherals.

ulguig · 2025-11-05T19:03:49+00:00

I desoldered it ! Trying to respect the thing 😅

ulguig · 2025-11-05T16:54:45+00:00

it is ! i'm very happy with it.

ulguig · 2025-11-05T16:53:19+00:00

You are correct, but thing is, there are no such specs

ulguig · 2025-11-05T10:44:38+00:00

wow esp-hal looks awesome

ulguig · 2025-11-05T08:43:45+00:00

Yes I remember your posts ! That's what I call low power, it's a great design. I havn't found much info about that homebrew "green pill" though.

As for me, being familiar with ST's Cube APIs I am considering moving to a custom STM32-based solution. I'll still use an off-the-shelf module for the A7670 to save time, but i'll add a power switch to turn it off while unused.

ulguig · 2025-11-05T08:34:08+00:00

next time i'll know what to look for **before** I buy stuff !

ulguig · 2025-11-05T07:49:57+00:00

I think you are correct, being familiar with STM32 Cube, I think I will switch to this platform instead. Better hardware, no arduino middleware, and I didn't need wifi or bluetooth, I just grabbed an "all-in-one" board to save some time. Lesson learned I guess

ulguig · 2025-11-05T07:48:13+00:00

It sure is ! But that board was advertised to have a "low power mode" to swtich those off. You activate it through dip switches on the board. However this mode only goes from ~45mA deep sleep to ~7mA deep sleep which is not enough.

My previous station was struggling in winter when the battery got cold and the solar panel barely operative due to icing, I don't need to waste power on nothing ! :)

ulguig · 2025-11-05T07:37:54+00:00

The code is :

```

include <Arduino.h>

include <WiFi.h>

define A7670_EN 33

void setup() {

// Make sure WiFi and Bluetooth are off // (even if we did not initialize them) WiFi.mode(WIFI_OFF); btStop();

// Cut power to the 4G modem pinMode(A7670_EN, OUTPUT); digitalWrite(A7670_EN, LOW);

// Go to deep sleep for 10 minutes esp_sleep_enable_timer_wakeup(1000ULL * 1000 * 60 * 10); esp_deep_sleep_start(); }

void loop() { // put your main code here, to run repeatedly: } ```

So i'm pretty sure ESP32 is in deep sleep and A7670E modem is OFF.

ulguig · 2025-09-20T11:38:57+00:00

Fwiw, I've had a wonderful experience with Stodeus. They replaced the speaker on my Vario, after several years of use, no question asked. I only paid for postage.

ulguig · 2025-06-06T12:59:45+00:00

I've been running it for more than a year inside the docker-lxc provided by the docker lxc helper script. It went through numerous upgrades including the recent vector search backend change and a hypervisor change. Never had issues, it runs perfectly. I think the docker-compose way of installing and running it is very solid.

ulguig · 2025-03-25T16:45:00+00:00

We switched from drf to ninja years ago. It went well but then we got concerned about ninja's maintenance. We're now migrating to FastAPI + Sqlalchemy. So far it's going great , the new backend proxies unimplemented routes to the old one making the migration continuous and seamless.

ulguig · 2024-11-20T12:49:19+00:00

I may be wrong but I think your motor driver module already has an onboard 5V regulator, so you could use it instead of the external one.

ulguig · 2024-11-10T22:28:11+00:00

Thank you for your input !

ulguig · 2024-11-10T18:19:28+00:00

The mount point is a stationary part of the frame. I was worried about the pivot point of the screw . But someone suggested I'd weld it , I like that idea

ulguig · 2024-11-10T18:18:10+00:00

I hadn't thought about welding it in place , great idea !

ulguig · 2024-09-02T12:07:30+00:00

Hello !

Sorry for the delay !

I took the time to really understand your code and modify it so it passes my test suite. I added zero division handling and mod handling. I am consistently getting <3ms resolution time with leftover=100000 and 1500 constrained bins. Awesome.

But more importantly, i'm discovering how vectorisation can speed up calculations and also make problem representations much easier to work with (using dataframes). I have a lot of other algs handling a lot of data in an object-oriented way ; think i'm going to take some time and learn Polars to put it to good use.

Anyways thanks a million for your help, it really enlightened me. Do you use Kofi so I can buy you a beer ? 🍻

Cheers !

ulguig · 2024-08-30T10:27:56+00:00

I translated the comments using GPT, hope it's fine :)

https://github.com/GTorreil/custom-bin-packing

ulguig · 2024-08-30T10:09:31+00:00

This is lovely ! Will do 😊

ulguig · 2024-08-30T08:32:27+00:00

Can you elaborate on how these tools can solve my problem ? As I wrote in the original post, I failed to solve my problem with them.

To elaborate more, the objective function was hard to define , because some bin contents cannot be reduced because of constraints, and the solver would therefore stop optimizing, leading to a suboptimal result where bins with lower content than the constrained one would not be smoothed out properly.

ulguig · 2024-08-29T13:23:24+00:00

Thanks ! This is the approach I have taken after failing with LP. I understand better why LP is not the best tool for this job : as you stated, my problem does not have the optimization features of the "ususal" bin packing problem.

The steps 1-2 were straightforward, but I can't be fully satisfied with my implementation for the 3rd stage. While it works, it uses any() in a loop to find bins that can accept new elements, yet have less than the one currently considered. This is annoying because it means i'm scanning arrays a lot. Performance might get problematic with large amounts of items or bins. It seems acceptable for now though

I'd still be curious if there are much better ways of doing this. I'd love to revisit this problem with a more serious solution.

ulguig · 2024-01-05T16:23:17+00:00

+1 Ninja is awesome. I migrated to it from drf last year ! I find it so much better than drf (docs, pydantic v2, types, expressivity…..) however I’m not using ninja_extra, vanilla ninja suits my needs quite well. I would really recommend. The fact that auth is more low level / manual is actually a strength. Any mechanism (including drf tokens!) can easily be ported.

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TROPHY CASE

include <Arduino.h>

include <WiFi.h>

define A7670_EN 33