| Message ID | 20240703141726.252368-5-stefan.klug@ideasonboard.com |
|---|---|
| State | Superseded |
| Headers | show |
| Series |
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| Related | show |
On Wed, Jul 03, 2024 at 04:16:53PM +0200, Stefan Klug wrote: > Copy visualize_macbeth_chart from raspberry pi. It is copied verbatim > and does not work in this state. > > Signed-off-by: Stefan Klug <stefan.klug@ideasonboard.com> > Reviewed-by: Laurent Pinchart <laurent.pinchart@ideasonboard.com> Acked-by: Paul Elder <paul.elder@ideasonboard.com> > --- > utils/tuning/libtuning/utils.py | 43 +++++++++++++++++++++++++++++++++ > 1 file changed, 43 insertions(+) > > diff --git a/utils/tuning/libtuning/utils.py b/utils/tuning/libtuning/utils.py > index 1e8128ea0571..f099c0ed685c 100644 > --- a/utils/tuning/libtuning/utils.py > +++ b/utils/tuning/libtuning/utils.py > @@ -123,3 +123,46 @@ def load_images(input_dir: str, config: dict, load_nonlsc: bool, load_lsc: bool) > return None > > return images > + > + > + > +""" > +Some code that will save virtual macbeth charts that show the difference between optimised matrices and non optimised matrices > + > +The function creates an image that is 1550 by 1050 pixels wide, and fills it with patches which are 200x200 pixels in size > +Each patch contains the ideal color, the color from the original matrix, and the color from the final matrix > +_________________ > +| | > +| Ideal Color | > +|_______________| > +| Old | new | > +| Color | Color | > +|_______|_______| > + > +Nice way of showing how the optimisation helps change the colors and the color matricies > +""" > +def visualise_macbeth_chart(macbeth_rgb, original_rgb, new_rgb, output_filename): > + image = np.zeros((1050, 1550, 3), dtype=np.uint8) > + colorindex = -1 > + for y in range(6): > + for x in range(4): # Creates 6 x 4 grid of macbeth chart > + colorindex += 1 > + xlocation = 50 + 250 * x # Means there is 50px of black gap between each square, more like the real macbeth chart. > + ylocation = 50 + 250 * y > + for g in range(200): > + for i in range(100): > + image[xlocation + i, ylocation + g] = macbeth_rgb[colorindex] > + xlocation = 150 + 250 * x > + ylocation = 50 + 250 * y > + for i in range(100): > + for g in range(100): > + image[xlocation + i, ylocation + g] = original_rgb[colorindex] # Smaller squares below to compare the old colors with the new ones > + xlocation = 150 + 250 * x > + ylocation = 150 + 250 * y > + for i in range(100): > + for g in range(100): > + image[xlocation + i, ylocation + g] = new_rgb[colorindex] > + > + img = Image.fromarray(image, 'RGB') > + img.save(str(output_filename) + 'Generated Macbeth Chart.png') > + > -- > 2.43.0 >
diff --git a/utils/tuning/libtuning/utils.py b/utils/tuning/libtuning/utils.py index 1e8128ea0571..f099c0ed685c 100644 --- a/utils/tuning/libtuning/utils.py +++ b/utils/tuning/libtuning/utils.py @@ -123,3 +123,46 @@ def load_images(input_dir: str, config: dict, load_nonlsc: bool, load_lsc: bool) return None return images + + + +""" +Some code that will save virtual macbeth charts that show the difference between optimised matrices and non optimised matrices + +The function creates an image that is 1550 by 1050 pixels wide, and fills it with patches which are 200x200 pixels in size +Each patch contains the ideal color, the color from the original matrix, and the color from the final matrix +_________________ +| | +| Ideal Color | +|_______________| +| Old | new | +| Color | Color | +|_______|_______| + +Nice way of showing how the optimisation helps change the colors and the color matricies +""" +def visualise_macbeth_chart(macbeth_rgb, original_rgb, new_rgb, output_filename): + image = np.zeros((1050, 1550, 3), dtype=np.uint8) + colorindex = -1 + for y in range(6): + for x in range(4): # Creates 6 x 4 grid of macbeth chart + colorindex += 1 + xlocation = 50 + 250 * x # Means there is 50px of black gap between each square, more like the real macbeth chart. + ylocation = 50 + 250 * y + for g in range(200): + for i in range(100): + image[xlocation + i, ylocation + g] = macbeth_rgb[colorindex] + xlocation = 150 + 250 * x + ylocation = 50 + 250 * y + for i in range(100): + for g in range(100): + image[xlocation + i, ylocation + g] = original_rgb[colorindex] # Smaller squares below to compare the old colors with the new ones + xlocation = 150 + 250 * x + ylocation = 150 + 250 * y + for i in range(100): + for g in range(100): + image[xlocation + i, ylocation + g] = new_rgb[colorindex] + + img = Image.fromarray(image, 'RGB') + img.save(str(output_filename) + 'Generated Macbeth Chart.png') +