diff options
-rw-r--r-- | utils/tuning/libtuning/utils.py | 43 |
1 files changed, 43 insertions, 0 deletions
diff --git a/utils/tuning/libtuning/utils.py b/utils/tuning/libtuning/utils.py index 1e8128ea..f099c0ed 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') + |