code stringlengths 3 6.57k |
|---|
params(self) |
copy.deepcopy(self.__actual_params__) |
tag(cls) |
description(cls) |
key(cls) |
no_field(self) |
len(self.__params__) |
CombineDBs(data.Dataset) |
__init__(self, dataloaders, excluded=None) |
self.im_ids.append(elem) |
self.im_ids.remove(elem) |
enumerate(dataloaders) |
enumerate(dl.im_ids) |
if (curr_im_id in self.im_ids) |
and (curr_im_id not in new_im_ids) |
new_im_ids.append(curr_im_id) |
range(len(dl.obj_dict[curr_im_id]) |
self.obj_list.append({'db_ii': ii, 'obj_ii': dl.obj_list.index([jj, kk]) |
self.im_list.append({'db_ii': ii, 'im_ii': jj}) |
print('Combined number of images: {:d}\nCombined number of objects: {:d}'.format(num_images, len(self.obj_list) |
__getitem__(self, index) |
__getitem__(_obj_ii) |
sample.keys() |
str(self.dataloaders[_db_ii]) |
__len__(self) |
len(self.obj_list) |
__str__(self) |
str(db) |
str(db) |
str(include_db) |
str(exclude_db) |
tr.RandomHorizontalFlip() |
tr.ScaleNRotate(rots=(-15, 15) |
tr.FixedResize(resolutions={'image': (450, 450) |
tr.DistanceMap(v=0.15, elem='gt') |
tr.ConcatInputs(elems=('image', 'distance_map') |
tr.ToTensor() |
tr.FixedResize(resolutions={'image': (450, 450) |
tr.DistanceMap(v=0.15, elem='gt') |
tr.ConcatInputs(elems=('image', 'distance_map') |
tr.ToTensor() |
pascal.VOCSegmentation(split='val', transform=composed_transforms_ts, retname=True) |
sbd.SBDSegmentation(split=['train', 'val'], transform=composed_transforms_tr, retname=True) |
pascal.VOCSegmentation(split='train', transform=composed_transforms_tr, retname=True) |
CombineDBs([pascal_voc_train, sbd], excluded=[pascal_voc_val]) |
torch.utils.data.DataLoader(dataset, batch_size=2, shuffle=True, num_workers=0) |
enumerate(dataloader) |
range(sample["image"].size() |
numpy() |
numpy() |
np.array(gt[0]) |
astype(np.uint8) |
np.array(dismap[0]) |
astype(np.uint8) |
display.astype(np.uint8) |
plt.figure() |
plt.title('display') |
plt.imshow(display, cmap='gray') |
plt.show(block=True) |
SlackClient('<YOUR_SLACK_API_TOKEN>') |
handle_command(command, channel) |
command.startswith(MAKE_TEA_COMMAND) |
requests.post('https://api.relayr.io/devices/<KETTLE_DEVICE_ID>/data', data=json.dumps(data) |
command.startswith(STOP_BOILING_COMMAND) |
requests.post('https://api.relayr.io/devices/<KETTLE_DEVICE_ID>/data', data=json.dumps(data) |
command.startswith("is the kettle boiling?") |
requests.get('https://api.relayr.io/devices/<KETTLE_DEVICE_ID>/readings', headers=headers) |
json.loads(r.text) |
command.startswith("is the water hot?") |
requests.get('https://api.relayr.io/devices/<KETTLE_TEMPERATURE_DEVICE_ID>/readings', headers=headers) |
json.loads(r.text) |
float(resp['readings'][0]['value']) |
float(resp['readings'][0]['value']) |
float(resp['readings'][0]['value']) |
parse_slack_output(slack_rtm_output) |
len(output_list) |
split(AT_BOT) |
strip() |
lower() |
slack_client.rtm_connect() |
print("StarterBot connected and running!") |
parse_slack_output(slack_client.rtm_read() |
handle_command(command, channel) |
time.sleep(READ_WEBSOCKET_DELAY) |
print("Connection failed. Invalid Slack token or bot ID?") |
_vim_vital_web_api_github_main() |
import (urlparse, parse_qs, urlencode, urlunparse) |
import (urlparse, parse_qs, urlunparse) |
format_exception() |
sys.exc_info() |
to_vim(obj) |
isinstance(obj, bool) |
int(obj) |
isinstance(obj, dict) |
dict([to_vim(k) |
to_vim(v) |
obj.items() |
isinstance(obj, (list, tuple) |
list(to_vim(v) |
build_headers(token) |
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