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Merge branch 'changes-into-saturation-fix' into verify-focus

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Joe Knapper 2024-02-20 14:17:25 +00:00
commit 6031280a19
1 changed files with 14 additions and 3 deletions
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src/openflexure_microscope_server/things/smart_scan.py
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@ -12,6 +12,7 @@ from PIL import Image
from pydantic import BaseModel from pydantic import BaseModel
from scipy.stats import norm from scipy.stats import norm
from scipy.ndimage import zoom from scipy.ndimage import zoom
from scipy.interpolate import interp1d
from copy import deepcopy from copy import deepcopy
from datetime import datetime from datetime import datetime
from subprocess import CompletedProcess, Popen, PIPE, SubprocessError, run, STDOUT from subprocess import CompletedProcess, Popen, PIPE, SubprocessError, run, STDOUT
@ -549,11 +550,21 @@ class SmartScanThing(Thing):
Cb = np.array(lst["Cb"]) Cb = np.array(lst["Cb"])
gr, gb = cam.colour_gains gr, gb = cam.colour_gains
G = 1/lum G = 1/lum
R = 1/lum/Cr/gr R = G/Cr/gr*np.min(Cr) # The extra /np.max(Cr) emulates the quirky handling of Cr in
B = 1/lum/Cb/gb B = G/Cb/gb*np.min(Cb) # the picamera2 pipeline
white_norm_lores = np.stack([R, G, B], axis=2) white_norm_lores = np.stack([R, G, B], axis=2)
zoom_factors = [i/n for i, n in zip(rgb[...,:3].shape, white_norm_lores.shape)] zoom_factors = [i/n for i, n in zip(rgb[...,:3].shape, white_norm_lores.shape)]
white_norm = zoom(white_norm_lores, zoom_factors, order=1)[:rgb.shape[0], :rgb.shape[1], :] # Could use some work white_norm = zoom(white_norm_lores, zoom_factors, order=1)[:rgb.shape[0], :rgb.shape[1], :] # Could use some work
colour_correction_matrix = np.array(cam.colour_correction_matrix).reshape((3,3))
contrast_algorithm = cam.tuning["algorithms"][9]["rpi.contrast"]
gamma = np.array(contrast_algorithm["gamma_curve"]).reshape((-1,2))
gamma_8bit = interp1d(gamma[:, 0]/255, gamma[:, 1]/255)
def process_raw_image(img):
normed = img/white_norm
corrected = np.dot(colour_correction_matrix, normed.reshape((-1, 3)).T).T.reshape(normed.shape)
corrected[corrected < 0] = 0
corrected[corrected > 255] = 255
return gamma_8bit(corrected)
logger.info( logger.info(
f"Generated normalisation image with shape {white_norm.shape}, " f"Generated normalisation image with shape {white_norm.shape}, "
f"max {white_norm.max(axis=(0,1))}, min {white_norm.min(axis=(0,1))}" f"max {white_norm.max(axis=(0,1))}, min {white_norm.min(axis=(0,1))}"
@ -580,7 +591,7 @@ class SmartScanThing(Thing):
# Save the raw image # Save the raw image
np.savez(os.path.join(raw_images_folder, name + ".npz"), raw_image=raw_image, **norm_inputs) np.savez(os.path.join(raw_images_folder, name + ".npz"), raw_image=raw_image, **norm_inputs)
# Process it into 8 bit RGB # Process it into 8 bit RGB
processed = rggb2rgb(raw2rggb(raw_image)) / white_norm processed = process_raw_image(rggb2rgb(raw2rggb(raw_image)))
processed[processed > 255] = 255 processed[processed > 255] = 255
processed[processed < 0] = 0 processed[processed < 0] = 0
img = Image.fromarray(processed.astype(np.uint8), mode="RGB") img = Image.fromarray(processed.astype(np.uint8), mode="RGB")