summaryrefslogtreecommitdiff
path: root/src/qcam/assets/feathericons/voicemail.svg
AgeCommit message (Expand)Author
2020-02-14qcam: assets: Provide initial icon setKieran Bingham
' href='#n98'>98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149
# SPDX-License-Identifier: BSD-2-Clause
#
# Copyright (C) 2019, Raspberry Pi (Trading) Limited
#
# ctt_tools.py - camera tuning tool miscellaneous

import time
import re
import binascii
import os
import cv2
import numpy as np
import imutils
import sys
import matplotlib.pyplot as plt
from sklearn import cluster as cluster
from sklearn.neighbors.nearest_centroid import NearestCentroid as get_centroids

"""
This file contains some useful tools, the details of which aren't important to
understanding of the code. They ar collated here to attempt to improve code
readability in the main files.
"""


"""
obtain config values, unless it doesnt exist, in which case pick default
Furthermore, it can check if the input is the correct type
"""
def get_config(dictt, key, default, ttype):
    try:
        val = dictt[key]
        if ttype == 'string':
            val = str(val)
        elif ttype == 'num':
            if 'int' not in str(type(val)):
                if 'float' not in str(type(val)):
                    raise ValueError
        elif ttype == 'dict':
            if not isinstance(val, dict):
                raise ValueError
        elif ttype == 'list':
            if not isinstance(val, list):
                raise ValueError
        elif ttype == 'bool':
            ttype = int(bool(ttype))
        else:
            val = dictt[key]
    except (KeyError, ValueError):
        val = default
    return val


"""
argument parser
"""
def parse_input():
    arguments = sys.argv[1:]
    if len(arguments) % 2 != 0:
        raise ArgError('\n\nERROR! Enter value for each arguent passed.')
    params = arguments[0::2]
    vals = arguments[1::2]
    args_dict = dict(zip(params, vals))
    json_output = get_config(args_dict, '-o', None, 'string')
    directory = get_config(args_dict, '-i', None, 'string')
    config = get_config(args_dict, '-c', None, 'string')
    log_path = get_config(args_dict, '-l', None, 'string')
    if directory is None:
        raise ArgError('\n\nERROR! No input directory given.')
    if json_output is None:
        raise ArgError('\n\nERROR! No output json given.')
    return json_output, directory, config, log_path


"""
custom arg and macbeth error class
"""
class ArgError(Exception):
    pass
class MacbethError(Exception):
    pass


"""
correlation function to quantify match
"""
def correlate(im1, im2):
    f1 = im1.flatten()
    f2 = im2.flatten()
    cor = np.corrcoef(f1, f2)
    return cor[0][1]


"""
get list of files from directory
"""
def get_photos(directory='photos'):
    filename_list = []
    for filename in os.listdir(directory):
        if 'jp' in filename or '.dng' in filename:
            filename_list.append(filename)
    return filename_list


"""
display image for debugging... read at your own risk...
"""
def represent(img, name='image'):
    # if type(img) == tuple or type(img) == list:
    #     for i in range(len(img)):
    #         name = 'image {}'.format(i)
    #         cv2.imshow(name, img[i])
    # else:
    #     cv2.imshow(name, img)
    # cv2.waitKey(0)
    # cv2.destroyAllWindows()
    # return 0
    """
    code above displays using opencv, but this doesn't catch users pressing 'x'
    with their mouse to close the window....  therefore matplotlib is used....
    (thanks a lot opencv)
    """
    grid = plt.GridSpec(22, 1)
    plt.subplot(grid[:19, 0])
    plt.imshow(img, cmap='gray')
    plt.axis('off')
    plt.subplot(grid[21, 0])
    plt.title('press \'q\' to continue')
    plt.axis('off')
    plt.show()

    # f = plt.figure()
    # ax = f.add_subplot(211)
    # ax2 = f.add_subplot(122)
    # ax.imshow(img, cmap='gray')
    # ax.axis('off')
    # ax2.set_figheight(2)
    # ax2.title('press \'q\' to continue')
    # ax2.axis('off')
    # plt.show()


"""
reshape image to fixed width without distorting
returns image and scale factor
"""
def reshape(img, width):
    factor = width/img.shape[0]
    return cv2.resize(img, None, fx=factor, fy=factor), factor