AI punk tribute MNIST: only Python and development boards, never re-sample clock production

We used to see the ancient times, clocked by tube composed. In the AI ​​era, there is no more time to display trendy way? Yes, the data set can also be made of the clock every morning, let MNIST handwritten digital awaken memories of your day.

MNIST computer vision is not old classic, when the first generation of convolution neural network bursting out with dazzling light on this handwritten digital data set, it is destined to load "go down in history."

Although computer vision has long been out of the era MNIST data sets, and even more than ten million ImageNet image is no longer a very large image datasets. However, MNIST still can not be ignored, entry-depth study of the first data set, the first experimental verification algorithms is it. Even Hinton verify it Capsule idea datasets are used.

If you want to pay tribute to such a data set "pioneer", in what ways would you adopt? In GitHub, the Almost Human found an interesting little project, the author Dheera Venkatraman made a side bell, which the figures are from MNIST data set sampling.

Project address: https: //github.com/dheera/mnist-clock

In other words, 24-hour random draw ten thousand different handwritten numbers, not with the kind of weight a day. Made out of effect is this:

Such electronic clock requires only a simple circuit board plus the four e-ink screen on the line, look behind it is this:

hardware

Project uses TinyPICO development board; compact ESP32 board and a large number of GPIO pins, 4MB flash memory, Wi-Fi, as well as many other features. TinyPICO can be said that the world based ESP32-PICO-D4 smallest development board, 240 MHz 32-bit dual-core processor enough for us to complete the calculation.

4 e-link digital display, e-link was chosen, because it is consistent with the concept of handwritten digits, will operate properly under all lighting conditions, but that does not bother anyone. The e-link display Waveshare most SPI, although some additional pins. Most people will want one that contains only one CS and SPI pins, but some more links are necessary. The following is a connection diagram ESP32, according to this roll up the wire.

OF TinyPICO is used on two 10- pin JST-EH connector, JST-EH configuration using a lower than JST-XH, more suitable insert, shorter and safer than the standard pins.

JST-EH connector connected TinyPICO

Next, the hardware bye secured to the housing 3D printing, it is done:

If readers are not familiar with the hardware, it would not worry, as long as we give the hardware according to the project authors, and assemble trying to be difficult. We will look at all the "equipment" of the price and the author provides design.

software

Project author Dheera Venkatraman said he often write C ++ or C, but he was very interested in MicroPython, so using in this project is that it.

Items using the gradation depth of 2 bits per pixel to represent the handwritten numbers MNIST. In such an image bit-depth of 28 * 28 pixels it requires only 196 bytes, and therefore able to meet a 4MB flash MNIST whole validation set. If you want the entire data set are loaded into, then only want to change the Flash also more microcontrollers, or the use of a bit-depth image using a compression method or the like.

All files in / code TinyPICO root directory, the file is probably correct as shown.

In addition, we also need to create a file named .wifi for Wi-Fi, middle write yourssid and yourpassword, specific WIFI read the code shown on the following settings.

Project author Dheera Venkatraman provides all the code files on GitHub, the print watch digital code is also very easy to read. More friendly, the authors of the code provides a very comprehensive notes, important basic statements are interpreted.

Realistically, how much money do one?

If from the hardware point of view, it seems that the main cost is the TinyPICO development boards and four e-ink screen. First TinyPICO can buy in Taobao or foreign Web sites, foreign selling for $ 20, while the price of 235 yuan on Taobao, plus shipping actually about the same. In addition, readers can also choose specific components mall, its prices are around 200.

Secondly, an e-ink screen about $ 24, although Taobao can not find, but the domestic components mall is much cheaper, one only need about 92 yuan, raspberry party may demand its relatively large bar.

Other cost relatively less, the wire connector installed clock packaging are relatively easy to obtain, store in the country may be disposable components available. If readers would like 3D printing packaging, the authors also provide specific printing parameters. So, in general, the production costs should be less than 650 dollars, and electronic display boards which can be reused in other projects.

Maybe we can improve the realization of the project, the digital clock on a large screen ink, direct use of the more commonly used as a Raspberry Pi board (power consumption is much higher than TinyPICO), and achieve more capabilities such as real-time sampling a CIFAR-10 as a background. In short, MNIST digital clock, there are many places to play.

Finally, detailed information on all hardware and software can access to the original project. In addition, it is worth mentioning that, Dheera Venkatraman is a very interesting little brother, his longest from Hangzhou to Beijing along the history of mankind artificial river by bicycle to ride 1,600 kilometers.

Last But Not Least

MNIST really stood center stage is gone, but its role is still not be ignored, there are still many researchers working to improve and fix it, make a unique contribution.

2017, German fashion Technologies Zalando offers Fashion MNIST data set, its size, and format of the training set / test set is fully consistent with the original MNIST divide, migrate from MNIST to it, we do not need to modify any code.

In June last year, NYU researcher and Facebook rebuilt and expanded MNIST data set in the test set adds 50,000 samples, the test set will increase to 60,000 samples. Yann LeCun MNIST one of the authors said, "If you repeatedly use MNIST original test set, your model may have been fitted on the test set, it's time to try on a new sample."

Whether the MNIST make daily life nice and fun project, or to enhance the capacity of the data set itself, MNIST will always be living history -

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Origin www.cnblogs.com/7758520lzy/p/12458454.html