Calling remove_shadows() on an image without a background source of
truth image now works. However, that said, the shadow remover isn't
suitable for anything other than removing shadow on an image of concrete
flow or somthing of the like. In general, it can only remove shadows
from a scene that has nothing else in it except for a hard edge shadow.
Improving this to work for anything is about a month of work. I've
researched enough about shadow removal to now know the optimal way to do
it. However, it requires many steps and a large amount of RAM. On the H7
I may revist this as being possible.
...
In order to get the shadow remover working well I had to add a few
features to the image library and fix some of the convolution code.
These fixes will likely be more useful than the shadow removal code.
Note the addition of the new get_threshold() method. This computes
otsu's threshold on a histogram allowing you to pick the optimal color
bounds.
OpenMV IDE includes an ini file generator which will let you set board
settings easily from the IDE. Currently, the IDE has support for setting
the WiFi shield up along with adding a REPL Uart.
Anyway, this commit adds support for the OpenMV Cam to parse an ini file
on startup to configure things before starting main.py. WiFi support is
not yet implmented. However, we now have the ability to turn the UART
and put the REPL terminal on it on startup given a setting in the ini
file.
(Why not use boot.py like normal MP? While that is more flxible it's
much harder for the IDE to easily write out settings for you which is
what most users will want to do versus coding this up).
...
The movitation for adding REPL UART support in particular is so that the
OpenMV Cam can be used as a slave processor to IoT type processors like
the ESP32/ESP8266/ParticlePhoton/ElectricImp. In particular, a processor
like the ParticlePhoton can control the OpenMV Cam's reset wire. Wake
the camera up by releasing reset, then send a script to it after it
powers on over the UART. The camera will then run the script, do
computer vision, and report results back over the UART to the
ParticlePhoton. Users can then push new scripts to the OpenMV Cam from
the cloud allowing for semi-flexible firmware fixes for the OpenMV Cam
over low data rate networks.
By setting this feature up the need for OpenMV to offer a WiFi IoT
system is reduced as we can now just be the best camera for everything.
...
Due to... I don't know... ctrl-c doesn't work on the duplicated UART.
https://github.com/micropython/micropython/issues/1568
Not sure how to handle this. I don't want to fix it since it needs to be
fixed by MP upstream. Right now the work around is for the mastering MCU
to just reset the OpenMV Cam when it's done with the system.
That said, this does mean that once you start a script using the Open
Terminal command line system you won't be able to stop the script.
Add in support for shadow removal from the current image using a shadow
free background image. Test results show the algorithm works similar to
max() while still keeping dark objects around. The preformance impact of
the algorithm is not too high. An in memory example can achieve 30 FPS.
Redid the phase correlation code again so it's one method call now. This
method call can either do logpolar phase correlation to get rotation/
scale or translation(x/y). Additionally, it will be able to also do both
at once. However, I don't have that quite working yet.
I've updated the example scripts to reflect the new code too.
Finally, I had to fix a bug in the rotation correction code.
...
Once I've got the full pipeline working I will post scripts for that. I
have all the code in there and it's been somewhat debugged... However, I
can't get a useful phase correlation lock out of the log polar fft mag.
I plan to look into noise filtering and spectral whitening solutions for
this.
This commit updates the shadow free invariant image to 2 colors from
just grayscale.
If we need to save ROM room in the future we'll just disable the LUT and
have the algorithm run with the regular C code. Right now this is not an
issue.
Someone asked me about doing a field of receptors before. These scripts
show how to do that. Also, added example scripts for calling the linear
polar and log polar methods added previously which power
find_rotscale().
Just doing one big commit/PR here since I noticed that breaking it up
causes issues.
Anyway, these fixes give us GOOD/WORKING/FAST optical flow now on the
OpenMV Cam M7. A number of changes were made to the optical flow
scripts. You have have absolute and differential estimation example
scripts. Additionally, you also have the ability to measure rotation and
scale changes too. Linear/Log Polar conversion was added for this. Users
may use the new code for generic image manipulation too. Finally, I
updated the power of 2 resolutions since you actually HAVE to use them
with optical flow for the phasecorrelation code to work correctly.
I have some more advanced scripts coming after this. But, This commit is
already getting kinda large so I'm stopping it here.