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-#!/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)