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OpenMV固件源码
Mean filter -> Fast and easy to use. This will likely be the only filter that gets alot of action on the M4. Median filter -> Works really well, but, slow. On grayscale at 160x120 you can get also 10 FPS with it for a 3x3 kernel. That said, it's still slow. Also, the code only works for 3x3 and 5x5 kernels. About the previous histogram filter... technically, that filter should be better. However, it suffers from a startup cost. The operation of finding the median point in the histogram costs too much to compute. This is what causes it to be slow. On very large kernels it will be faster than the sorting median alrogithm I put up... but, large kernels will be too slow for anyone to use anyway. The paper Ibrahim linked to about it showed it being used for like 7x7 kernels and up... so, I think the researcher who thought of the idea was really thinking about the algorithm for large kernels. Mode filter -> Works great on grayscale. Not so much on color. I think it needs to be run on the LAB color space instead of the RGB color space. I say this because it causes pretty strong artifacts around edges. When we get more flash we'll be able to have a reverse lookup table for LAB to make the mode filter better. Until then... |
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| CHANGELOG.md | ||
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| README.md | ||
###OpenMV (Open Machine Vision Module)
OpenMV is an open-source tiny machine vision module based on the STM32F4xx ARM Cortex-M4 MCU and the OV2640 JPEG sensor.
OpenMV is programmable in Python3 (MicroPython) and capable of doing face detection and tracking, keypoint extraction, color tracking and more..The board has USB, a uSD connector and an expansion header (USART/SPI/I2C).
A Python IDE with syntax highlighting is available for the camera, it can run/upload scripts to the camera, view the framebuffer and update the firmware.