This way we'll be able to have colors on SetupWizard when added a
secondary user.
Test: manual
Test: atest ThemeOverlayControllerTest
Fixes: 189168701
Change-Id: I8c7e5cc3a4804c34ad4ace0ba473a373b939cb83
- Make the new task immediately visible, and reset the crop on the
original task transferred from the leash
Fixes: 190550846
Test: Open ApiDemos, autoenter from a task with multiple activities
Change-Id: I2527cee68448dc8f1be7634051547c29c596c63a
If setup wizard is not complete, run the theme application directly
instead of posting it to a Handler.
Test: atest ThemeOverlayControllerTest
Fixes: 190580756
Change-Id: Ibe59526fe569766bdcb243652dc21ad35f83320c
* changes:
Quantize image to 128 colors instead of 5
Quantizer improvements
Sort colors from high count => low count
Don't interpolate image input to quantizer
Cache set wallpaper as PNG instead of JPEG
Only rescale wallpaper if its > display height
- NotificationWakeUpCoordinator should prioritize screen off doze override.
- We should tell the stack scroll layout to switch to KEYGUARD so that it doesn't show notifs even if bypass is enabled.
Fixes: 190227875
Test: with/without face unlock and bypass
Change-Id: I902692fa6ae417c051a77b248fd3863f51e0bc36
- Technically the IME window is above the Bubble window, but when
traversing the windows top-down for calculating the final exclusion
region for SysUI, the IME is placed just above its target (the
embedded task), and the Bubble's full touchable region effectively
overrides the IME's requested exclusion region
Fixes: 190338512
Test: Expand a bubble, swipe from IME edge
Change-Id: Idd71eabfaba1be4bc6fc90d09db28d3f9e9106c5
Quantizing an image to five colors results in an extreme amount of
averaging of colors, leading to low chroma colors and erasing colors
from the image that the eye gravitates towards.
Coupled with a change to ensure there's still a broadly accurate signal
of a given cluster's population of the image, via summing the population
of all the clusters close to the hue of the cluster, and with proof that
having this many data points doesn't lead to instability in results,
we gain access to a much larger variety of colors. This gives room to
add heuristics to avoid 'bad' colors, as well as increase the
number of colorful colors we offer.
Bug: 189931209
Test: Test tons and tons of wallpapers over a couple days.
Change-Id: Ifc2d9393039194c151920536b9217ae9636ff0d6
The original versions of these quantizers landed a couple months back,
and they were fine. Since then, we've had several opportunities to
iterate on them. This change lands improvements from those iterations.
TL;DR: 18% faster, big bug fix to WSMeans, code is cleaner (hopefully)
- QuantizerMap indexes an image's pixels, 'unique-ing' them by reducing
the pixel array to a map with keys of colors, and values of population.
This allows other quantizers to operate much more quickly: instead of
working on each pixel individually, they're able to operate in bulk.
- QuantizerWu uses flat arrays instead of 3D arrays and is more
understandable IMHO.
- QuantizerWsmeans has speed improvements, most importantly, it has a
big bug fix. When a Kmeans-based quantizer algo starts, it must first
assign the pixels to any one of the starting clusters. The original
implementation decided what cluster to assign a pixel to by finding the
cluster closest to the pixel. However, the algo terminates if no pixels
moved after one iteration of the algorithm, and since the pixels were
already in the cluster closest to them, the algo would immediately
terminate before it actually figured out where the cluster moved to
after pixels were assigned to it, and had a chance to move pixels around
based on that.
- Funnily enough, even though this _should_ mean Wsmeans got a lot
slower since it has to do more iterations, it is actually 16% faster
Additionally, during review of this CL:
An accidental dependency on iteration order of a Set was introduced,
causing inconsistent initialization of the mPoints array, creating
inconsistent results from the quantizer.
Removing the dependency on hashes of float[], and avoiding Maps
altogether, removes a dependency on hash codes of pointers that existed
during review, making it easier to have verifiable consistency across
iterations. This also improves speed slightly, from 55 ms to 39 ms
(tested on sunfish, first 9 wallpapers in Landscapes, City Scapes, and
Art categories, and averaged)
Bug: 189931209
Test: ran performance tests with VariationalKMeansQuantizer,
the previous Celebi = Wu + Wsmeans quantizer, and the new Celebi =
new Wu + new Wsmeans quantizers, over 100 iterations. Wu speed is
roughly the same, Wsmeans is 18%. Verified quantizer output is stable
for the same input pixels, run 100,000 times for each of two wallpapers.
Change-Id: I3324d29860c098ea1fd602b8d4197837e732f4f1
