# coding: utf-8
# docs
from typing import Dict
from supervisely._utils import batched
from supervisely.api.module_api import ApiField
from supervisely.api.pointcloud.pointcloud_api import PointcloudApi
from supervisely.api.pointcloud.pointcloud_episode_annotation_api import (
PointcloudEpisodeAnnotationAPI,
)
from supervisely.api.pointcloud.pointcloud_episode_object_api import (
PointcloudEpisodeObjectApi,
)
[docs]class PointcloudEpisodeApi(PointcloudApi):
"""
API for working with :class:`PointcloudEpisodes<supervisely.pointcloud_episodes.pointcloud_episodes>`.
:class:`PointcloudEpisodeApi<PointcloudEpisodeApi>` object is immutable.
Inherits from :class:`PointcloudApi<supervisely.api.pointcloud.PointcloudApi>`.
:param api: API connection to the server.
:type api: Api
:Usage example:
.. code-block:: python
import os
from dotenv import load_dotenv
import supervisely as sly
# Load secrets and create API object from .env file (recommended)
# Learn more here: https://developer.supervisely.com/getting-started/basics-of-authentication
if sly.is_development():
load_dotenv(os.path.expanduser("~/supervisely.env"))
api = sly.Api.from_env()
# Pass values into the API constructor (optional, not recommended)
# api = sly.Api(server_address="https://app.supervise.ly", token="4r47N...xaTatb")
pcd_epsodes_id = 19373295
pcd_epsodes_info = api.pointcloud_episode.get_info_by_id(pcd_epsodes_id) # api usage example
"""
def __init__(self, api):
super().__init__(api)
self.annotation = PointcloudEpisodeAnnotationAPI(api)
self.object = PointcloudEpisodeObjectApi(api)
self.tag = None
def _convert_json_info(self, info: dict, skip_missing=True):
res = super()._convert_json_info(info, skip_missing=skip_missing)
if res.meta is not None:
return res._replace(frame=res.meta[ApiField.FRAME])
else:
raise RuntimeError(
"Error with point cloud meta or API version. Please, contact support"
)
[docs] def get_frame_name_map(self, dataset_id: int) -> Dict:
"""
Get a dictionary with frame_id and name of pointcloud by dataset id.
:param dataset_id: :class:`Dataset<supervisely.project.project.Dataset>` ID in Supervisely.
:type dataset_id: int
:return: Dict with frame_id and name of pointcloud.
:rtype: Dict
:Usage example:
.. code-block:: python
import supervisely as sly
os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()
dataset_id = 62664
frame_to_name_map = api.pointcloud_episode.get_frame_name_map(dataset_id)
print(frame_to_name_map)
# Output:
# {0: '001', 1: '002'}
"""
pointclouds = self.get_list(dataset_id)
frame_index_to_pcl_name = {}
if len(pointclouds) > 0 and pointclouds[0].frame is None:
pointclouds_names = sorted([x.name for x in pointclouds])
for frame_index, pcl_name in enumerate(pointclouds_names):
frame_index_to_pcl_name[frame_index] = pcl_name
else:
frame_index_to_pcl_name = {x.frame: x.name for x in pointclouds}
return frame_index_to_pcl_name
[docs] def notify_progress(
self,
track_id: int,
dataset_id: int,
pcd_ids: list,
current: int,
total: int,
):
"""
Send message to the Annotation Tool and return info if tracking was stopped
:param track_id: int
:param dataset_id: int
:param pcd_ids: list
:param current: int
:param total: int
:return: str
"""
response = self._api.post(
"point-clouds.episodes.notify-annotation-tool",
{
"type": "point-cloud-episodes:fetch-figures-in-range",
"data": {
ApiField.TRACK_ID: track_id,
ApiField.DATASET_ID: dataset_id,
ApiField.POINTCLOUD_IDS: pcd_ids,
ApiField.PROGRESS: {ApiField.CURRENT: current, ApiField.TOTAL: total},
},
},
)
return response.json()[ApiField.STOPPED]
[docs] def get_max_frame_idx(self, dataset_id: int) -> int:
"""
Get max frame index for episode by dataset id.
This method is useful for uploading pointclouds to the episode in parts.
:param dataset_id: :class:`Dataset<supervisely.project.project.Dataset>` ID in Supervisely.
:type dataset_id: int
:return: Max frame index.
:rtype: int
:Usage example:
.. code-block:: python
import supervisely as sly
os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()
dataset_id = 62664
max_frame = api.pointcloud_episode.get_max_frame(dataset_id)
print(max_frame)
# Output:
# 1
"""
pointclouds = self.get_list(dataset_id)
frames = [x.frame for x in pointclouds]
if len(frames) == 0:
return None
max_frame = max(frames)
return max_frame
def _upload_bulk_add(
self,
func_item_to_kv,
dataset_id,
names,
items,
metas=None,
progress_cb=None,
):
if metas is None:
max_frame = self.get_max_frame_idx(dataset_id)
if max_frame is None:
max_frame = range(len(items))
else:
max_frame = range(max_frame + 1, max_frame + 1 + len(items))
metas = [{ApiField.FRAME: i} for i in max_frame]
else:
if len(metas) != len(items):
raise RuntimeError(
'Can not match "metas" and "items" lists, len(metas) != len(items)'
)
missing_frame_indices = [
idx for idx, meta in enumerate(metas) if ApiField.FRAME not in meta
]
if len(missing_frame_indices) == len(metas):
raise RuntimeError("No 'frame' key found in all 'metas'.")
elif len(missing_frame_indices) > 0:
missing_frame_names = [names[idx] for idx in missing_frame_indices]
raise RuntimeError(
f"No 'frame' key found in 'metas' for names {missing_frame_names}."
)
results = []
if len(names) == 0:
return results
if len(names) != len(items):
raise RuntimeError('Can not match "names" and "items" lists, len(names) != len(items)')
for batch in batched(list(zip(names, items, metas))):
images = []
for name, item, meta in batch:
item_tuple = func_item_to_kv(item)
images.append(
{
ApiField.NAME: name,
item_tuple[0]: item_tuple[1],
ApiField.META: meta,
}
)
response = self._api.post(
"point-clouds.bulk.add",
{ApiField.DATASET_ID: dataset_id, ApiField.POINTCLOUDS: images},
)
if progress_cb is not None:
progress_cb(len(images))
results.extend([self._convert_json_info(item) for item in response.json()])
name_to_res = {img_info.name: img_info for img_info in results}
ordered_results = [name_to_res[name] for name in names]
return ordered_results