From 60d60c13672b81f2a57894467a569c6ba98ae895 Mon Sep 17 00:00:00 2001 From: Stefan Klug Date: Thu, 23 Jan 2025 12:40:58 +0100 Subject: libtuning: module: awb: Add bayes AWB support To support the bayesian AWB algorithm in libtuning, the necessary data needs to be collected and written to the tuning file. Extend libtuning to calculate and output that additional data. Prior probabilities and AwbModes are manually specified and not calculated in the tuning process. Add sample values from the RaspberryPi tuning files to the example config file. Signed-off-by: Stefan Klug Reviewed-by: Paul Elder Reviewed-by: Kieran Bingham --- utils/tuning/libtuning/modules/awb/awb.py | 16 ++++++++++------ utils/tuning/libtuning/modules/awb/rkisp1.py | 21 +++++++++++++++------ 2 files changed, 25 insertions(+), 12 deletions(-) (limited to 'utils/tuning/libtuning/modules') diff --git a/utils/tuning/libtuning/modules/awb/awb.py b/utils/tuning/libtuning/modules/awb/awb.py index c154cf3b..0dc4f59d 100644 --- a/utils/tuning/libtuning/modules/awb/awb.py +++ b/utils/tuning/libtuning/modules/awb/awb.py @@ -27,10 +27,14 @@ class AWB(Module): imgs = [img for img in images if img.macbeth is not None] - gains, _, _ = awb(imgs, None, None, False) - gains = np.reshape(gains, (-1, 3)) + ct_curve, transverse_pos, transverse_neg = awb(imgs, None, None, False) + ct_curve = np.reshape(ct_curve, (-1, 3)) + gains = [{ + 'ct': int(v[0]), + 'gains': [float(1.0 / v[1]), float(1.0 / v[2])] + } for v in ct_curve] + + return {'colourGains': gains, + 'transversePos': transverse_pos, + 'transverseNeg': transverse_neg} - return [{ - 'ct': int(v[0]), - 'gains': [float(1.0 / v[1]), float(1.0 / v[2])] - } for v in gains] diff --git a/utils/tuning/libtuning/modules/awb/rkisp1.py b/utils/tuning/libtuning/modules/awb/rkisp1.py index 0c95843b..d562d26e 100644 --- a/utils/tuning/libtuning/modules/awb/rkisp1.py +++ b/utils/tuning/libtuning/modules/awb/rkisp1.py @@ -6,9 +6,6 @@ from .awb import AWB -import libtuning as lt - - class AWBRkISP1(AWB): hr_name = 'AWB (RkISP1)' out_name = 'Awb' @@ -20,8 +17,20 @@ class AWBRkISP1(AWB): return True def process(self, config: dict, images: list, outputs: dict) -> dict: - output = {} - - output['colourGains'] = self.do_calculation(images) + if not 'awb' in config['general']: + raise ValueError('AWB configuration missing') + awb_config = config['general']['awb'] + algorithm = awb_config['algorithm'] + + output = {'algorithm': algorithm} + data = self.do_calculation(images) + if algorithm == 'grey': + output['colourGains'] = data['colourGains'] + elif algorithm == 'bayes': + output['AwbMode'] = awb_config['AwbMode'] + output['priors'] = awb_config['priors'] + output.update(data) + else: + raise ValueError(f"Unknown AWB algorithm {output['algorithm']}") return output -- cgit v1.2.1