def __init__(self):
self.already_marked_dir = 'Datasets/legacy_jsons/agro'
self.already_marked_list = os.listdir(self.already_marked_dir)
super(WindowClassificationPicture, self).__init__()
self.setWindowTitle("Plant Disease Recognizer")
# TODO some dev stuff
# with open(self.choose_json(content_title='config data')) as config_fp:
with open('config_create_json.json') as config_fp:
config_dict = json.load(config_fp)
# self.img_path = self.choose_picture()
# self.img_name = os.path.splitext(self.img_path)[0]
self.window_shape = config_dict['window_shape']
self.classes = config_dict['classes']
self.default_label_size = config_dict['qt_label_size']
self.img_thumb = config_dict['img_thumb']
self._init_hbox_control()
self._init_main_menu()
self.main_layout = MyGridWidget(hbox_control=self.hbox_control)
self.setCentralWidget(self.main_layout)
self.showFullScreen()
self.choose_and_render_image()
# for offset calculation
self.last_x = 0
self.last_y = 0
def __init__(self):
super(WindowPredictOnImage, self).__init__()
with open(os.path.abspath('config_full_system.json')) as config_fp:
self.config_dict = json.load(config_fp)
# load layers
self.clusterer = get_clusterer_by_name(
self.config_dict['clusterer']['name'],
self.config_dict['clusterer']['args'])
if self.config_dict['preprocessor']['use']:
self.segmentator = get_preprocessor_by_name(
self.config_dict['preprocessor']['name'],
self.config_dict['preprocessor']['args'])
self.classifier = get_classifier_by_name(
self.config_dict['classifier']['name'],
self.config_dict['classifier']['args'])
self.bad_key = self.config_dict['classifier']['bad_key']
self._define_max_key_len()
self._parse_image()
self.main_layout = MyGridWidget(hbox_control=self.hbox_control)
self.pbar = QProgressBar(self)
self.main_layout.layout.addWidget(self.pbar)
self.right_text_labels = []
self.setCentralWidget(self.main_layout)
self.showFullScreen()
self.update_main_layout()
def __init__(self, x_data, y_data, y_predicted):
super(WindowShowUnetFitting, self).__init__()
with open('config_full_system.json') as config_fp:
self.label_size = json.load(config_fp)['gui']['qt_label_size']
self.main_layout = MyGridWidget(hbox_control=self.hbox_control)
self.setCentralWidget(self.main_layout)
self.showFullScreen()
self.update_main_layout(x_data, y_data, y_predicted)
def __init__(self, x_data, y_data, y_predicted, classes):
super(WindowShowPredictions, self).__init__()
config_dict = self.load_dict_from_json_with_keys(
key_list=['qt_label_size'])
self.label_size = config_dict['qt_label_size']
self.x_data = x_data
self.y_data = y_data
self.y_predicted = y_predicted
self.classes = classes
self._define_max_key_len()
self.main_layout = MyGridWidget(hbox_control=self.hbox_control)
self.setCentralWidget(self.main_layout)
self.showFullScreen()
self.update_main_layout()
def __init__(self, json_list):
super(WindowMultipleExamples, self).__init__()
self.postfix = 'joined'
self.label_size = (224, 224)
# TODO maybe will be restored someday
# with open(self.choose_json(content_title='config augmentation data')) as aug_config_fp:
with open('config_data_augmentation.json') as aug_config_fp:
aug_config_dict = json.load(aug_config_fp)
alghs_dict = aug_config_dict['algorithms']
self.max_aug_part = aug_config_dict['aug_part']
self.augment_all = aug_config_dict['augment_all']
self.output_json = aug_config_dict['output_json']
self.save_data_binary = aug_config_dict['save_data_to_binary']
self.save_data_dir = aug_config_dict['save_data_to_dir']
for key, value in alghs_dict.items():
if value['use'] and len(
value['val_list']) != self.max_aug_part:
raise Exception('bad val_list size for %s' % key)
self.arg_dict = {
'use_noise': alghs_dict['noise']['use'],
'intensity_noise_list': alghs_dict['noise']['val_list'],
'use_deform': alghs_dict['deform']['use'],
'k_deform_list': alghs_dict['deform']['val_list'],
'use_blur': alghs_dict['blur']['use'],
'rad_list': alghs_dict['blur']['val_list'],
'use_affine': alghs_dict['affine']['use'],
'affine_list': alghs_dict['affine']['val_list'],
'use_contrast': alghs_dict['contrast']['use'],
'contrast_list': alghs_dict['contrast']['val_list']
}
if json_list == None:
raise Exception('No passed json')
self.json_name = os.path.splitext(json_list[0])[0]
if len(json_list) == 1:
print('Parsing preprocessed json')
self.classes, img_shape, self.x_data, self.y_data = \
dmk.json_big_load(json_list[0])
self.x_data = np.array(self.x_data, dtype='uint8')
self.y_data = np.array(self.y_data, dtype='uint8')
else:
print('Parsing json list')
self.classes, self.x_data, self.y_data = dmk.get_data_from_json_list(
json_list=json_list,
# remove_classes=None,
# TODO some dev stuff
remove_classes=[
'альтернариоз', 'прочие инфекции', 'морщинистая мозаика',
'полосатая мозаика'
])
self.init_size = len(self.x_data)
self.img_shape = self.x_data.shape[1:]
# TODO some dev stuff
# self.classes['здоровый куст'] = self.classes['марь белая']
# del self.classes['марь белая']
# self.classes['мозаика'] = self.classes['прочие мозаики']
# del self.classes['прочие мозаики']
# self.classes['сорняк'] = self.classes['прочие сорняки']
# del self.classes['прочие сорняки']
self._define_max_class()
self.main_layout = MyGridWidget(hbox_control=self.hbox_control)
self.setCentralWidget(self.main_layout)
self.showFullScreen()
self.show_full()
print("---------------------------------")
print('classes = %s' % str(self.classes))
print('max_classes = %s' % str(self.max_aug_for_classes))
print('ex_num = %d' %
sum(map(lambda x: x['num'], self.classes.values())))
print("---------------------------------")
self.show_histogram(labels=list(self.classes.keys()),
values=list(
map(lambda val: val['num'],
self.classes.values())))