code stringlengths 3 6.57k |
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ICalendarParser.get_instance(device_data[CONF_PARSER]) |
HTTPPasswordMgrWithDefaultRealm() |
HTTPBasicAuthHandler(passman) |
HTTPDigestAuthHandler(passman) |
build_opener(digest_auth_handler, basic_auth_handler) |
install_opener(opener) |
_download_calendar(self) |
or (datetime.now() |
datetime.now() |
urlopen(self.url) |
conn.read() |
decode() |
replace("\0", "") |
_LOGGER.error(f"{self.name}: Failed to open url: {http_error.reason}") |
_LOGGER.error(f"{self.name}: Failed to open url: {url_error.reason}") |
_LOGGER.error(f"{self.name}: Failed to open url!") |
async_get_events(self, hass, start_date, end_date) |
hass.async_add_job(self._download_calendar) |
list(map(self.format_dates, events) |
_LOGGER.error(f"{self.name}: Failed to parse ICS!") |
Throttle(MIN_TIME_BETWEEN_UPDATES) |
update(self) |
self._download_calendar() |
_LOGGER.error(f"{self.name}: Failed to parse ICS!") |
format_dates(self, event) |
self.get_date_formatted(event["start"], event["all_day"]) |
self.get_date_formatted(event["end"], event["all_day"]) |
get_date_formatted(self, dt, is_all_day) |
dt.strftime("%Y-%m-%d") |
dt.strftime("%Y-%m-%dT%H:%M:%S.%f%z") |
get_hass_date(self, dt, is_all_day) |
self.parser.get_date_formatted(dt, is_all_day) |
self.parser.get_date_formatted(dt, is_all_day) |
_rand(a=0., b=1.) |
np.random.rand() |
get_imageId_from_fileName(filename, id_iter) |
os.path.splitext(filename) |
filename.isdigit() |
int(filename) |
random_sample_crop(image, boxes) |
np.random.choice([None, 0.1, 0.3, 0.5, 0.7, 0.9]) |
trails (50) |
range(50) |
_rand(0.3, 1.0) |
_rand(0.3, 1.0) |
_rand() |
_rand() |
np.array([int(top) |
int(left) |
int(top + h) |
int(left + w) |
jaccard_numpy(boxes, rect) |
drop_mask.any() |
min() |
max() |
mask.any() |
copy() |
np.maximum(boxes_t[:, :2], rect[:2]) |
np.minimum(boxes_t[:, 2:4], rect[2:4]) |
preprocess_fn(img_id, image, box, is_training) |
cv2.setNumThreads(2) |
_infer_data(image, input_shape) |
cv2.resize(image, (input_w, input_h) |
len(image.shape) |
np.expand_dims(image, axis=-1) |
np.concatenate([image, image, image], axis=-1) |
np.array((img_h, img_w) |
_data_aug(image, box, is_training, image_size=(300, 300) |
_infer_data(image, image_size) |
box.astype(np.float32) |
random_sample_crop(image, box) |
cv2.resize(image, (w, h) |
_rand() |
cv2.flip(image, 1, dst=None) |
len(image.shape) |
np.expand_dims(image, axis=-1) |
np.concatenate([image, image, image], axis=-1) |
ssd_bboxes_encode(box) |
_data_aug(image, box, is_training, image_size=config.img_shape) |
create_voc_label(is_training) |
enumerate(config.classes) |
os.path.join(voc_root, sub_dir) |
os.path.isdir(voc_dir) |
ValueError(f'Cannot find {sub_dir} dataset path.') |
os.path.isdir(os.path.join(voc_dir, 'Images') |
os.path.join(voc_dir, 'Images') |
os.path.isdir(os.path.join(voc_dir, 'Annotations') |
os.path.join(voc_dir, 'Annotations') |
os.path.join(config.voc_root, config.voc_json) |
os.path.split(json_file) |
os.path.isdir(file_dir) |
os.makedirs(file_dir) |
os.listdir(anno_dir) |
print(anno_file) |
anno_file.endswith('xml') |
et.parse(os.path.join(anno_dir, anno_file) |
tree.getroot() |
root_node.find('filename') |
get_imageId_from_fileName(file_name, id_iter) |
os.path.join(image_dir, file_name) |
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