| Message ID | 20240703141726.252368-23-stefan.klug@ideasonboard.com |
|---|---|
| State | Superseded |
| Headers | show |
| Series |
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| Related | show |
On Wed, Jul 03, 2024 at 04:17:11PM +0200, Stefan Klug wrote: > In cases where the calibration image contains super dark areas, or when > an invalid blacklevel was supplied, the grid might get close to zero or > negative. This would have bad effects on the 1/grid later. So clamp the > values to a small positive number. > > Signed-off-by: Stefan Klug <stefan.klug@ideasonboard.com> > Reviewed-by: Laurent Pinchart <laurent.pinchart@ideasonboard.com> Reviewed-by: Paul Elder <paul.elder@ideasonboard.com> > --- > utils/tuning/libtuning/modules/lsc/lsc.py | 5 ++++- > 1 file changed, 4 insertions(+), 1 deletion(-) > > diff --git a/utils/tuning/libtuning/modules/lsc/lsc.py b/utils/tuning/libtuning/modules/lsc/lsc.py > index 344a07a3d443..e0ca22ebe9bd 100644 > --- a/utils/tuning/libtuning/modules/lsc/lsc.py > +++ b/utils/tuning/libtuning/modules/lsc/lsc.py > @@ -59,7 +59,10 @@ class LSC(Module): > def _lsc_single_channel(self, channel: np.array, > image: lt.Image, green_grid: np.array = None): > grid = self._get_grid(channel, image.w, image.h) > - grid -= image.blacklevel_16 > + # Clamp the values to a small positive, so that the following 1/grid > + # doesn't produce negative results. > + grid = np.maximum(grid - image.blacklevel_16, 0.1) > + > if green_grid is None: > table = np.reshape(1 / grid, self.sector_shape[::-1]) > else: > -- > 2.43.0 >
diff --git a/utils/tuning/libtuning/modules/lsc/lsc.py b/utils/tuning/libtuning/modules/lsc/lsc.py index 344a07a3d443..e0ca22ebe9bd 100644 --- a/utils/tuning/libtuning/modules/lsc/lsc.py +++ b/utils/tuning/libtuning/modules/lsc/lsc.py @@ -59,7 +59,10 @@ class LSC(Module): def _lsc_single_channel(self, channel: np.array, image: lt.Image, green_grid: np.array = None): grid = self._get_grid(channel, image.w, image.h) - grid -= image.blacklevel_16 + # Clamp the values to a small positive, so that the following 1/grid + # doesn't produce negative results. + grid = np.maximum(grid - image.blacklevel_16, 0.1) + if green_grid is None: table = np.reshape(1 / grid, self.sector_shape[::-1]) else: