pimoroni-pico
edgetpu
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pimoroni-pico | edgetpu | |
---|---|---|
25 | 34 | |
1,202 | 397 | |
3.7% | 3.8% | |
8.9 | 2.7 | |
5 days ago | over 2 years ago | |
C | C++ | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pimoroni-pico
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Family Photos vs 256 Kb RAM
It takes some time to decode, but I can grab- for example- this 259k JPEG: http://placekitten.com/3840/2160
And display it from the microSD card with this code: https://gist.github.com/Gadgetoid/0b8e352e377135d743338c9483...
As more or less demonstrated by this example: https://github.com/pimoroni/pimoroni-pico/blob/main/micropyt...
Decoding is done via Larry Bank's JPEGDEC: https://github.com/bitbank2/JPEGDEC
It uses roughly 20k RAM to provide the necessary buffers both for decoding JPEGs into blocks which are passed to a drawing routine that handles copying the data into the display RAM buffer (on our larger Inky display this is backed by PSRAM). I don't believe there's a hard limit to the size of the JPEGs you can display. The main bottlenecks are decoding time and the relatively limited scaling options: FULL, HALF, QUARTER, EIGHTH.
This aside, the authors solution is actually quite elegant. As long as you have control over the image pipeline there's no real reason to encumber the device with handling large (both in bytes and pixel dimensions) files. You'll also get much better dithering results writing your own routine to convert files from JPG to the raw 4-bits per pixel format for the display. Our built-in dithering is just a plain ordered dither matrix and, while quaint and retro, it leaves much to be desired visually.
If you're trying to use a public API you can also make GitHub actions automate the whole image conversion process and publish the results to GitHub pages. This works great for, for example, the daily XKCD, serving both to reformat the strip for the display, credit the author, extract the "alt" text and avoid excess requests to the origin. Eg: https://pimoroni.github.io/feed2image/xkcd-800x480-daily.jpg. Though the astute will notice I still opted for jpeg in this case.
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Ask HN: Getting started with DIY programming of electronics
I've done a lot of programmable LED projects (keyword Neopixel or WS2812) and by far my favorite hardware has been this little raspberry pi pico board that takes care of the power requirements for you, a USB-C cable can supply 3 amps, powering one or two hundred LEDs with ease. There's lot of Arduino boards that let you program a few neopixels, but supplying power for lots of them is usually the annoying part.
https://shop.pimoroni.com/en-us/products/plasma-2040
https://github.com/pimoroni/pimoroni-pico/tree/main/micropyt...
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Sony backs Raspberry Pi with fresh funding, access to A.I. chips
https://shop.pimoroni.com/collections/pico is the pi version of that.
I'm still not sure why the BBC went down the route of making its own platform when adapting the arduino world would have been simpler and more effective. Still its good to see that the BBC is doing computing again.
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Pico I2C problem with SCD41 sensor
I have a problem with an I2C connection to a SCD41 sensor (Pimoroni Breakout). The strange thing is: The example provided by Pimoroni works perfectly fine.
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Pico KuCoin Trader gadget - I spent too long on the UI and forgot I need memory for the API and important code. Not sure how to rescue the project, or I'm just asking too much from the Pico?
But I'm using the https://github.com/pimoroni/pimoroni-pico firmware with the PicoGraphics module. There doesn't seem to much documentation about compiling their version (except the c version?)
- Static Image on a 0.96inch display
- Not much Pi, but it has a RP2040 on board - Waveshare Round LCD
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Pico W and RGB matrix 64x64 project help
I used the Pimoroni Micropython and the clock.py here.
- Can you use a real computer to replace a Raspberry Pi?
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Remember to say no to walled garden/non-modular stuff
However you'll find that the file you have linked includes breakout_sgp30.hpp which in turn includes drivers/sgp30/sgp30.hpp which you can find here: https://github.com/pimoroni/pimoroni-pico/tree/main/drivers/sgp30
edgetpu
- The Pixel 8 Pro's Tensor G3 off-loads all generative AI tasks to the cloud
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Chromebook Plus: more performance and AI capabilities
I know the tensor power pixelbook was shutdown and I never heard the actual reason just a bunch of speculation about costs/profitability which is probably true.
It's a shame that there isn't more competition and development in the neural asic world to harness the power of llms/generative AI on a low power, cheap hardware platform like the pixelbook line. For someone that invented the TPU they have done a not so great job of ensuring it's commercialization and support. Both on the hardware and software side.
The coral edge tpu seemed to be the right high level idea but without proper execution.
https://github.com/google-coral/edgetpu/issues/668
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Show HN: RISC-V core written in 600 lines of C89
> even in the 80s I wanted an FPGA accelerators in every machine
Mostly unrelated, but I recently discovered that you can buy TPUs, right now, as a consumer product, from https://coral.ai.
The stock firmware already allows you to run these things so hard they overheat, which is amazing.
But yes, I also want FPGA accelerators.
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Another PCIe A+E card in place of wifi in M900 tiny
I'm looking at the coral.ai cards and they have a M.2 A+E card, same form factor as the wifi slot in the m900 tiny. Has anyone tried another card in that slot other than wifi?
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Sony backs Raspberry Pi with fresh funding, access to A.I. chips
Chips optimized to perform the type of calculations used for NN inference at high parallelism. A good example would be the google spinoff https://coral.ai/ (though their usecase is highly limited by sub-par software constraints)
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Any ML accelarator chips?
By no means an expert, but I have seen prototypes using a raspberry pi and a dongle from Coral Ai. They have PCIE and USB based modules.
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Is Google coral getting abandoned
Last news on https://coral.ai/ was on May 5 2022
Activity on the github project seems to have stopped. https://github.com/google-coral
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Ask HN: Worth it to buy 4x Nvidia Tesla K40 for AI?
https://coral.ai/
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How do you effectively test accuracy of your software product?
Your problem statement still needs more clarification. If the above applies, the best way is to evaluate your ML-based pattern matcher on high-level scenarios. One approach to speed up the evaluation is to lift and shift the execution of scenarios into cloud. Another approach is to use an AI accelerator, such as http://coral.ai or other.
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Cluster AIs - low cost (lower performance) super/minicomputing
You probably could but not with raspis. Maybe the TPUs they sell. https://coral.ai/
What are some alternatives?
yocto-8 - A (WIP) PICO-8 cartridge runner for the Raspberry Pi Pico
yolov7 - Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
badger2040 - Sample code I used to design my badge for events to share information with attendees
scrypted - Scrypted is a high performance home video integration and automation platform
microphone-library-for-pico - Capture audio from a microphone on your Raspberry Pi Pico or any RP2040 based board. 🎤
frigate - NVR with realtime local object detection for IP cameras
BME280_SensorAPI - Bosch Sensortec BME280 sensor driver. To report issues, go to https://community.bosch-sensortec.com/t5/Bosch-Sensortec-Community/ct-p/bst_community
PINTO_model_zoo - A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
wizio-pico - Raspberry Pi Pico development platform for PlatformIO
yolov7_d2 - 🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
pico-composite8 - Raspberry Pi Pico NTSC 8-bit Composite Video output using Resistor R2R DAC, interlaced at 640x480, with slideshow on second core.
Dual-Edge-TPU-Adapter - Dual Edge TPU Adapter to use it on a system with single PCIe port on m.2 A/B/E/M slot