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Diffstat (limited to 'utils/raspberrypi/ctt/ctt.py')
| -rwxr-xr-x | utils/raspberrypi/ctt/ctt.py | 837 |
1 files changed, 0 insertions, 837 deletions
diff --git a/utils/raspberrypi/ctt/ctt.py b/utils/raspberrypi/ctt/ctt.py deleted file mode 100755 index bbe960b0..00000000 --- a/utils/raspberrypi/ctt/ctt.py +++ /dev/null @@ -1,837 +0,0 @@ -#!/usr/bin/env python3 -# -# SPDX-License-Identifier: BSD-2-Clause -# -# Copyright (C) 2019, Raspberry Pi Ltd -# -# camera tuning tool - -import os -import sys -from ctt_image_load import * -from ctt_ccm import * -from ctt_awb import * -from ctt_alsc import * -from ctt_lux import * -from ctt_noise import * -from ctt_geq import * -from ctt_pretty_print_json import pretty_print -import random -import json -import re - -""" -This file houses the camera object, which is used to perform the calibrations. -The camera object houses all the calibration images as attributes in two lists: - - imgs (macbeth charts) - - imgs_alsc (alsc correction images) -Various calibrations are methods of the camera object, and the output is stored -in a dictionary called self.json. -Once all the caibration has been completed, the Camera.json is written into a -json file. -The camera object initialises its json dictionary by reading from a pre-written -blank json file. This has been done to avoid reproducing the entire json file -in the code here, thereby avoiding unecessary clutter. -""" - - -""" -Get the colour and lux values from the strings of each inidvidual image -""" -def get_col_lux(string): - """ - Extract colour and lux values from filename - """ - col = re.search(r'([0-9]+)[kK](\.(jpg|jpeg|brcm|dng)|_.*\.(jpg|jpeg|brcm|dng))$', string) - lux = re.search(r'([0-9]+)[lL](\.(jpg|jpeg|brcm|dng)|_.*\.(jpg|jpeg|brcm|dng))$', string) - try: - col = col.group(1) - except AttributeError: - """ - Catch error if images labelled incorrectly and pass reasonable defaults - """ - return None, None - try: - lux = lux.group(1) - except AttributeError: - """ - Catch error if images labelled incorrectly and pass reasonable defaults - Still returns colour if that has been found. - """ - return col, None - return int(col), int(lux) - - -""" -Camera object that is the backbone of the tuning tool. -Input is the desired path of the output json. -""" -class Camera: - def __init__(self, jfile): - self.path = os.path.dirname(os.path.expanduser(__file__)) + '/' - if self.path == '/': - self.path = '' - self.imgs = [] - self.imgs_alsc = [] - self.log = 'Log created : ' + time.asctime(time.localtime(time.time())) - self.log_separator = '\n'+'-'*70+'\n' - self.jf = jfile - """ - initial json dict populated by uncalibrated values - """ - self.json = { - "rpi.black_level": { - "black_level": 4096 - }, - "rpi.dpc": { - }, - "rpi.lux": { - "reference_shutter_speed": 10000, - "reference_gain": 1, - "reference_aperture": 1.0 - }, - "rpi.noise": { - }, - "rpi.geq": { - }, - "rpi.sdn": { - }, - "rpi.awb": { - "priors": [ - {"lux": 0, "prior": [2000, 1.0, 3000, 0.0, 13000, 0.0]}, - {"lux": 800, "prior": [2000, 0.0, 6000, 2.0, 13000, 2.0]}, - {"lux": 1500, "prior": [2000, 0.0, 4000, 1.0, 6000, 6.0, 6500, 7.0, 7000, 1.0, 13000, 1.0]} - ], - "modes": { - "auto": {"lo": 2500, "hi": 8000}, - "incandescent": {"lo": 2500, "hi": 3000}, - "tungsten": {"lo": 3000, "hi": 3500}, - "fluorescent": {"lo": 4000, "hi": 4700}, - "indoor": {"lo": 3000, "hi": 5000}, - "daylight": {"lo": 5500, "hi": 6500}, - "cloudy": {"lo": 7000, "hi": 8600} - }, - "bayes": 1 - }, - "rpi.agc": { - "metering_modes": { - "centre-weighted": { - "weights": [3, 3, 3, 2, 2, 2, 2, 1, 1, 1, 1, 0, 0, 0, 0] - }, - "spot": { - "weights": [2, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] - }, - "matrix": { - "weights": [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] - } - }, - "exposure_modes": { - "normal": { - "shutter": [100, 10000, 30000, 60000, 120000], - "gain": [1.0, 2.0, 4.0, 6.0, 6.0] - }, - "short": { - "shutter": [100, 5000, 10000, 20000, 120000], - "gain": [1.0, 2.0, 4.0, 6.0, 6.0] - } - }, - "constraint_modes": { - "normal": [ - {"bound": "LOWER", "q_lo": 0.98, "q_hi": 1.0, "y_target": [0, 0.5, 1000, 0.5]} - ], - "highlight": [ - {"bound": "LOWER", "q_lo": 0.98, "q_hi": 1.0, "y_target": [0, 0.5, 1000, 0.5]}, - {"bound": "UPPER", "q_lo": 0.98, "q_hi": 1.0, "y_target": [0, 0.8, 1000, 0.8]} - ] - }, - "y_target": [0, 0.16, 1000, 0.165, 10000, 0.17] - }, - "rpi.alsc": { - 'omega': 1.3, - 'n_iter': 100, - 'luminance_strength': 0.7, - }, - "rpi.contrast": { - "ce_enable": 1, - "gamma_curve": [ - 0, 0, - 1024, 5040, - 2048, 9338, - 3072, 12356, - 4096, 15312, - 5120, 18051, - 6144, 20790, - 7168, 23193, - 8192, 25744, - 9216, 27942, - 10240, 30035, - 11264, 32005, - 12288, 33975, - 13312, 35815, - 14336, 37600, - 15360, 39168, - 16384, 40642, - 18432, 43379, - 20480, 45749, - 22528, 47753, - 24576, 49621, - 26624, 51253, - 28672, 52698, - 30720, 53796, - 32768, 54876, - 36864, 57012, - 40960, 58656, - 45056, 59954, - 49152, 61183, - 53248, 62355, - 57344, 63419, - 61440, 64476, - 65535, 65535 - ] - }, - "rpi.ccm": { - }, - "rpi.sharpen": { - } - } - - """ - Perform colour correction calibrations by comparing macbeth patch colours - to standard macbeth chart colours. - """ - def ccm_cal(self, do_alsc_colour): - if 'rpi.ccm' in self.disable: - return 1 - print('\nStarting CCM calibration') - self.log_new_sec('CCM') - """ - if image is greyscale then CCm makes no sense - """ - if self.grey: - print('\nERROR: Can\'t do CCM on greyscale image!') - self.log += '\nERROR: Cannot perform CCM calibration ' - self.log += 'on greyscale image!\nCCM aborted!' - del self.json['rpi.ccm'] - return 0 - a = time.time() - """ - Check if alsc tables have been generated, if not then do ccm without - alsc - """ - if ("rpi.alsc" not in self.disable) and do_alsc_colour: - """ - case where ALSC colour has been done, so no errors should be - expected... - """ - try: - cal_cr_list = self.json['rpi.alsc']['calibrations_Cr'] - cal_cb_list = self.json['rpi.alsc']['calibrations_Cb'] - self.log += '\nALSC tables found successfully' - except KeyError: - cal_cr_list, cal_cb_list = None, None - print('WARNING! No ALSC tables found for CCM!') - print('Performing CCM calibrations without ALSC correction...') - self.log += '\nWARNING: No ALSC tables found.\nCCM calibration ' - self.log += 'performed without ALSC correction...' - else: - """ - case where config options result in CCM done without ALSC colour tables - """ - cal_cr_list, cal_cb_list = None, None - self.log += '\nWARNING: No ALSC tables found.\nCCM calibration ' - self.log += 'performed without ALSC correction...' - - """ - Do CCM calibration - """ - try: - ccms = ccm(self, cal_cr_list, cal_cb_list) - except ArithmeticError: - print('ERROR: Matrix is singular!\nTake new pictures and try again...') - self.log += '\nERROR: Singular matrix encountered during fit!' - self.log += '\nCCM aborted!' - return 1 - """ - Write output to json - """ - self.json['rpi.ccm']['ccms'] = ccms - self.log += '\nCCM calibration written to json file' - print('Finished CCM calibration') - - """ - Auto white balance calibration produces a colour curve for - various colour temperatures, as well as providing a maximum 'wiggle room' - distance from this curve (transverse_neg/pos). - """ - def awb_cal(self, greyworld, do_alsc_colour): - if 'rpi.awb' in self.disable: - return 1 - print('\nStarting AWB calibration') - self.log_new_sec('AWB') - """ - if image is greyscale then AWB makes no sense - """ - if self.grey: - print('\nERROR: Can\'t do AWB on greyscale image!') - self.log += '\nERROR: Cannot perform AWB calibration ' - self.log += 'on greyscale image!\nAWB aborted!' - del self.json['rpi.awb'] - return 0 - """ - optional set greyworld (e.g. for noir cameras) - """ - if greyworld: - self.json['rpi.awb']['bayes'] = 0 - self.log += '\nGreyworld set' - """ - Check if alsc tables have been generated, if not then do awb without - alsc correction - """ - if ("rpi.alsc" not in self.disable) and do_alsc_colour: - try: - cal_cr_list = self.json['rpi.alsc']['calibrations_Cr'] - cal_cb_list = self.json['rpi.alsc']['calibrations_Cb'] - self.log += '\nALSC tables found successfully' - except KeyError: - cal_cr_list, cal_cb_list = None, None - print('ERROR, no ALSC calibrations found for AWB') - print('Performing AWB without ALSC tables') - self.log += '\nWARNING: No ALSC tables found.\nAWB calibration ' - self.log += 'performed without ALSC correction...' - else: - cal_cr_list, cal_cb_list = None, None - self.log += '\nWARNING: No ALSC tables found.\nAWB calibration ' - self.log += 'performed without ALSC correction...' - """ - call calibration function - """ - plot = "rpi.awb" in self.plot - awb_out = awb(self, cal_cr_list, cal_cb_list, plot) - ct_curve, transverse_neg, transverse_pos = awb_out - """ - write output to json - """ - self.json['rpi.awb']['ct_curve'] = ct_curve - self.json['rpi.awb']['sensitivity_r'] = 1.0 - self.json['rpi.awb']['sensitivity_b'] = 1.0 - self.json['rpi.awb']['transverse_pos'] = transverse_pos - self.json['rpi.awb']['transverse_neg'] = transverse_neg - self.log += '\nAWB calibration written to json file' - print('Finished AWB calibration') - - """ - Auto lens shading correction completely mitigates the effects of lens shading for ech - colour channel seperately, and then partially corrects for vignetting. - The extent of the correction depends on the 'luminance_strength' parameter. - """ - def alsc_cal(self, luminance_strength, do_alsc_colour): - if 'rpi.alsc' in self.disable: - return 1 - print('\nStarting ALSC calibration') - self.log_new_sec('ALSC') - """ - check if alsc images have been taken - """ - if len(self.imgs_alsc) == 0: - print('\nError:\nNo alsc calibration images found') - self.log += '\nERROR: No ALSC calibration images found!' - self.log += '\nALSC calibration aborted!' - return 1 - self.json['rpi.alsc']['luminance_strength'] = luminance_strength - if self.grey and do_alsc_colour: - print('Greyscale camera so only luminance_lut calculated') - do_alsc_colour = False - self.log += '\nWARNING: ALSC colour correction cannot be done on ' - self.log += 'greyscale image!\nALSC colour corrections forced off!' - """ - call calibration function - """ - plot = "rpi.alsc" in self.plot - alsc_out = alsc_all(self, do_alsc_colour, plot) - cal_cr_list, cal_cb_list, luminance_lut, av_corn = alsc_out - """ - write output to json and finish if not do_alsc_colour - """ - if not do_alsc_colour: - self.json['rpi.alsc']['luminance_lut'] = luminance_lut - self.json['rpi.alsc']['n_iter'] = 0 - self.log += '\nALSC calibrations written to json file' - self.log += '\nNo colour calibrations performed' - print('Finished ALSC calibrations') - return 1 - - self.json['rpi.alsc']['calibrations_Cr'] = cal_cr_list - self.json['rpi.alsc']['calibrations_Cb'] = cal_cb_list - self.json['rpi.alsc']['luminance_lut'] = luminance_lut - self.log += '\nALSC colour and luminance tables written to json file' - - """ - The sigmas determine the strength of the adaptive algorithm, that - cleans up any lens shading that has slipped through the alsc. These are - determined by measuring a 'worst-case' difference between two alsc tables - that are adjacent in colour space. If, however, only one colour - temperature has been provided, then this difference can not be computed - as only one table is available. - To determine the sigmas you would have to estimate the error of an alsc - table with only the image it was taken on as a check. To avoid circularity, - dfault exaggerated sigmas are used, which can result in too much alsc and - is therefore not advised. - In general, just take another alsc picture at another colour temperature! - """ - - if len(self.imgs_alsc) == 1: - self.json['rpi.alsc']['sigma'] = 0.005 - self.json['rpi.alsc']['sigma_Cb'] = 0.005 - print('\nWarning:\nOnly one alsc calibration found' - '\nStandard sigmas used for adaptive algorithm.') - print('Finished ALSC calibrations') - self.log += '\nWARNING: Only one colour temperature found in ' - self.log += 'calibration images.\nStandard sigmas used for adaptive ' - self.log += 'algorithm!' - return 1 - - """ - obtain worst-case scenario residual sigmas - """ - sigma_r, sigma_b = get_sigma(self, cal_cr_list, cal_cb_list) - """ - write output to json - """ - self.json['rpi.alsc']['sigma'] = np.round(sigma_r, 5) - self.json['rpi.alsc']['sigma_Cb'] = np.round(sigma_b, 5) - self.log += '\nCalibrated sigmas written to json file' - print('Finished ALSC calibrations') - - """ - Green equalisation fixes problems caused by discrepancies in green - channels. This is done by measuring the effect on macbeth chart patches, - which ideally would have the same green values throughout. - An upper bound linear model is fit, fixing a threshold for the green - differences that are corrected. - """ - def geq_cal(self): - if 'rpi.geq' in self.disable: - return 1 - print('\nStarting GEQ calibrations') - self.log_new_sec('GEQ') - """ - perform calibration - """ - plot = 'rpi.geq' in self.plot - slope, offset = geq_fit(self, plot) - """ - write output to json - """ - self.json['rpi.geq']['offset'] = offset - self.json['rpi.geq']['slope'] = slope - self.log += '\nGEQ calibrations written to json file' - print('Finished GEQ calibrations') - - """ - Lux calibrations allow the lux level of a scene to be estimated by a ratio - calculation. Lux values are used in the pipeline for algorithms such as AGC - and AWB - """ - def lux_cal(self): - if 'rpi.lux' in self.disable: - return 1 - print('\nStarting LUX calibrations') - self.log_new_sec('LUX') - """ - The lux calibration is done on a single image. For best effects, the - image with lux level closest to 1000 is chosen. - """ - luxes = [Img.lux for Img in self.imgs] - argmax = luxes.index(min(luxes, key=lambda l: abs(1000-l))) - Img = self.imgs[argmax] - self.log += '\nLux found closest to 1000: {} lx'.format(Img.lux) - self.log += '\nImage used: ' + Img.name - if Img.lux < 50: - self.log += '\nWARNING: Low lux could cause inaccurate calibrations!' - """ - do calibration - """ - lux_out, shutter_speed, gain = lux(self, Img) - """ - write output to json - """ - self.json['rpi.lux']['reference_shutter_speed'] = shutter_speed - self.json['rpi.lux']['reference_gain'] = gain - self.json['rpi.lux']['reference_lux'] = Img.lux - self.json['rpi.lux']['reference_Y'] = lux_out - self.log += '\nLUX calibrations written to json file' - print('Finished LUX calibrations') - - """ - Noise alibration attempts to describe the noise profile of the sensor. The - calibration is run on macbeth images and the final output is taken as the average - """ - def noise_cal(self): - if 'rpi.noise' in self.disable: - return 1 - print('\nStarting NOISE calibrations') - self.log_new_sec('NOISE') - """ - run calibration on all images and sort by slope. - """ - plot = "rpi.noise" in self.plot - noise_out = sorted([noise(self, Img, plot) for Img in self.imgs], key=lambda x: x[0]) - self.log += '\nFinished processing images' - """ - take the average of the interquartile - """ - length = len(noise_out) - noise_out = np.mean(noise_out[length//4:1+3*length//4], axis=0) - self.log += '\nAverage noise profile: constant = {} '.format(int(noise_out[1])) - self.log += 'slope = {:.3f}'.format(noise_out[0]) - """ - write to json - """ - self.json['rpi.noise']['reference_constant'] = int(noise_out[1]) - self.json['rpi.noise']['reference_slope'] = round(noise_out[0], 3) - self.log += '\nNOISE calibrations written to json' - print('Finished NOISE calibrations') - - """ - Removes json entries that are turned off - """ - def json_remove(self, disable): - self.log_new_sec('Disabling Options', cal=False) - if len(self.disable) == 0: - self.log += '\nNothing disabled!' - return 1 - for key in disable: - try: - del self.json[key] - self.log += '\nDisabled: ' + key - except KeyError: - self.log += '\nERROR: ' + key + ' not found!' - """ - writes the json dictionary to the raw json file then make pretty - """ - def write_json(self): - """ - Write json dictionary to file using our version 2 format - """ - - out_json = { - "version": 2.0, - 'target': 'bcm2835', - "algorithms": [{name: data} for name, data in self.json.items()], - } - - with open(self.jf, 'w') as f: - f.write(pretty_print(out_json)) - - """ - add a new section to the log file - """ - def log_new_sec(self, section, cal=True): - self.log += '\n'+self.log_separator - self.log += section - if cal: - self.log += ' Calibration' - self.log += self.log_separator - - """ - write script arguments to log file - """ - def log_user_input(self, json_output, directory, config, log_output): - self.log_new_sec('User Arguments', cal=False) - self.log += '\nJson file output: ' + json_output - self.log += '\nCalibration images directory: ' + directory - if config is None: - self.log += '\nNo configuration file input... using default options' - elif config is False: - self.log += '\nWARNING: Invalid configuration file path...' - self.log += ' using default options' - elif config is True: - self.log += '\nWARNING: Invalid syntax in configuration file...' - self.log += ' using default options' - else: - self.log += '\nConfiguration file: ' + config - if log_output is None: - self.log += '\nNo log file path input... using default: ctt_log.txt' - else: - self.log += '\nLog file output: ' + log_output - - # if log_output - - """ - write log file - """ - def write_log(self, filename): - if filename is None: - filename = 'ctt_log.txt' - self.log += '\n' + self.log_separator - with open(filename, 'w') as logfile: - logfile.write(self.log) - - """ - Add all images from directory, pass into relevant list of images and - extrace lux and temperature values. - """ - def add_imgs(self, directory, mac_config, blacklevel=-1): - self.log_new_sec('Image Loading', cal=False) - img_suc_msg = 'Image loaded successfully!' - print('\n\nLoading images from '+directory) - self.log += '\nDirectory: ' + directory - """ - get list of files - """ - filename_list = get_photos(directory) - print("Files found: {}".format(len(filename_list))) - self.log += '\nFiles found: {}'.format(len(filename_list)) - """ - iterate over files - """ - filename_list.sort() - for filename in filename_list: - address = directory + filename - print('\nLoading image: '+filename) - self.log += '\n\nImage: ' + filename - """ - obtain colour and lux value - """ - col, lux = get_col_lux(filename) - """ - Check if image is an alsc calibration image - """ - if 'alsc' in filename: - Img = load_image(self, address, mac=False) - self.log += '\nIdentified as an ALSC image' - """ - check if imagae data has been successfully unpacked - """ - if Img == 0: - print('\nDISCARDED') - self.log += '\nImage discarded!' - continue - """ - check that image colour temperature has been successfuly obtained - """ - elif col is not None: - """ - if successful, append to list and continue to next image - """ - Img.col = col - Img.name = filename - self.log += '\nColour temperature: {} K'.format(col) - self.imgs_alsc.append(Img) - if blacklevel != -1: - Img.blacklevel_16 = blacklevel - print(img_suc_msg) - continue - else: - print('Error! No colour temperature found!') - self.log += '\nWARNING: Error reading colour temperature' - self.log += '\nImage discarded!' - print('DISCARDED') - else: - self.log += '\nIdentified as macbeth chart image' - """ - if image isn't an alsc correction then it must have a lux and a - colour temperature value to be useful - """ - if lux is None: - print('DISCARDED') - self.log += '\nWARNING: Error reading lux value' - self.log += '\nImage discarded!' - continue - Img = load_image(self, address, mac_config) - """ - check that image data has been successfuly unpacked - """ - if Img == 0: - print('DISCARDED') - self.log += '\nImage discarded!' - continue - else: - """ - if successful, append to list and continue to next image - """ - Img.col, Img.lux = col, lux - Img.name = filename - self.log += '\nColour temperature: {} K'.format(col) - self.log += '\nLux value: {} lx'.format(lux) - if blacklevel != -1: - Img.blacklevel_16 = blacklevel - print(img_suc_msg) - self.imgs.append(Img) - - print('\nFinished loading images') - - """ - Check that usable images have been found - Possible errors include: - - no macbeth chart - - incorrect filename/extension - - images from different cameras - """ - def check_imgs(self, macbeth=True): - self.log += '\n\nImages found:' - self.log += '\nMacbeth : {}'.format(len(self.imgs)) - self.log += '\nALSC : {} '.format(len(self.imgs_alsc)) - self.log += '\n\nCamera metadata' - """ - check usable images found - """ - if len(self.imgs) == 0 and macbeth: - print('\nERROR: No usable macbeth chart images found') - self.log += '\nERROR: No usable macbeth chart images found' - return 0 - elif len(self.imgs) == 0 and len(self.imgs_alsc) == 0: - print('\nERROR: No usable images found') - self.log += '\nERROR: No usable images found' - return 0 - """ - Double check that every image has come from the same camera... - """ - all_imgs = self.imgs + self.imgs_alsc - camNames = list(set([Img.camName for Img in all_imgs])) - patterns = list(set([Img.pattern for Img in all_imgs])) - sigbitss = list(set([Img.sigbits for Img in all_imgs])) - blacklevels = list(set([Img.blacklevel_16 for Img in all_imgs])) - sizes = list(set([(Img.w, Img.h) for Img in all_imgs])) - - if len(camNames) == 1 and len(patterns) == 1 and len(sigbitss) == 1 and \ - len(blacklevels) == 1 and len(sizes) == 1: - self.grey = (patterns[0] == 128) - self.blacklevel_16 = blacklevels[0] - self.log += '\nName: {}'.format(camNames[0]) - self.log += '\nBayer pattern case: {}'.format(patterns[0]) - if self.grey: - self.log += '\nGreyscale camera identified' - self.log += '\nSignificant bits: {}'.format(sigbitss[0]) - self.log += '\nBlacklevel: {}'.format(blacklevels[0]) - self.log += '\nImage size: w = {} h = {}'.format(sizes[0][0], sizes[0][1]) - return 1 - else: - print('\nERROR: Images from different cameras') - self.log += '\nERROR: Images are from different cameras' - return 0 - - -def run_ctt(json_output, directory, config, log_output, alsc_only=False): - """ - check input files are jsons - """ - if json_output[-5:] != '.json': - raise ArgError('\n\nError: Output must be a json file!') - if config is not None: - """ - check if config file is actually a json - """ - if config[-5:] != '.json': - raise ArgError('\n\nError: Config file must be a json file!') - """ - read configurations - """ - try: - with open(config, 'r') as config_json: - configs = json.load(config_json) - except FileNotFoundError: - configs = {} - config = False - except json.decoder.JSONDecodeError: - configs = {} - config = True - - else: - configs = {} - """ - load configurations from config file, if not given then set default - """ - disable = get_config(configs, "disable", [], 'list') - plot = get_config(configs, "plot", [], 'list') - awb_d = get_config(configs, "awb", {}, 'dict') - greyworld = get_config(awb_d, "greyworld", 0, 'bool') - alsc_d = get_config(configs, "alsc", {}, 'dict') - do_alsc_colour = get_config(alsc_d, "do_alsc_colour", 1, 'bool') - luminance_strength = get_config(alsc_d, "luminance_strength", 0.5, 'num') - blacklevel = get_config(configs, "blacklevel", -1, 'num') - macbeth_d = get_config(configs, "macbeth", {}, 'dict') - mac_small = get_config(macbeth_d, "small", 0, 'bool') - mac_show = get_config(macbeth_d, "show", 0, 'bool') - mac_config = (mac_small, mac_show) - - if blacklevel < -1 or blacklevel >= 2**16: - print('\nInvalid blacklevel, defaulted to 64') - blacklevel = -1 - - if luminance_strength < 0 or luminance_strength > 1: - print('\nInvalid luminance_strength strength, defaulted to 0.5') - luminance_strength = 0.5 - - """ - sanitise directory path - """ - if directory[-1] != '/': - directory += '/' - """ - initialise tuning tool and load images - """ - try: - Cam = Camera(json_output) - Cam.log_user_input(json_output, directory, config, log_output) - if alsc_only: - disable = set(Cam.json.keys()).symmetric_difference({"rpi.alsc"}) - Cam.disable = disable - Cam.plot = plot - Cam.add_imgs(directory, mac_config, blacklevel) - except FileNotFoundError: - raise ArgError('\n\nError: Input image directory not found!') - - """ - preform calibrations as long as check_imgs returns True - If alsc is activated then it must be done before awb and ccm since the alsc - tables are used in awb and ccm calibrations - ccm also technically does an awb but it measures this from the macbeth - chart in the image rather than using calibration data - """ - if Cam.check_imgs(macbeth=not alsc_only): - if not alsc_only: - Cam.json['rpi.black_level']['black_level'] = Cam.blacklevel_16 - Cam.json_remove(disable) - print('\nSTARTING CALIBRATIONS') - Cam.alsc_cal(luminance_strength, do_alsc_colour) - Cam.geq_cal() - Cam.lux_cal() - Cam.noise_cal() - Cam.awb_cal(greyworld, do_alsc_colour) - Cam.ccm_cal(do_alsc_colour) - print('\nFINISHED CALIBRATIONS') - Cam.write_json() - Cam.write_log(log_output) - print('\nCalibrations written to: '+json_output) - if log_output is None: - log_output = 'ctt_log.txt' - print('Log file written to: '+log_output) - pass - else: - Cam.write_log(log_output) - - -if __name__ == '__main__': - """ - initialise calibration - """ - if len(sys.argv) == 1: - print(""" - Pisp Camera Tuning Tool version 1.0 - - Required Arguments: - '-i' : Calibration image directory. - '-o' : Name of output json file. - - Optional Arguments: - '-c' : Config file for the CTT. If not passed, default parameters used. - '-l' : Name of output log file. If not passed, 'ctt_log.txt' used. - """) - quit(0) - else: - """ - parse input arguments - """ - json_output, directory, config, log_output = parse_input() - run_ctt(json_output, directory, config, log_output) |