code stringlengths 114 1.05M | path stringlengths 3 312 | quality_prob float64 0.5 0.99 | learning_prob float64 0.2 1 | filename stringlengths 3 168 | kind stringclasses 1
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import numpy as np
from typing import List
from detectron2.config import CfgNode as CfgNode_
from detectron2.config import configurable
from .base_tracker import TRACKER_HEADS_REGISTRY
from .vanilla_hungarian_bbox_iou_tracker import VanillaHungarianBBoxIOUTracker
@TRACKER_HEADS_REGISTRY.register()
class IOUWeighte... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/tracking/iou_weighted_hungarian_bbox_iou_tracker.py | 0.926429 | 0.403097 | iou_weighted_hungarian_bbox_iou_tracker.py | pypi |
import copy
import itertools
import logging
import numpy as np
import pickle
import random
import torch.utils.data as data
from torch.utils.data.sampler import Sampler
from detectron2.utils.serialize import PicklableWrapper
__all__ = ["MapDataset", "DatasetFromList", "AspectRatioGroupedDataset", "ToIterableDataset"]
... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/data/common.py | 0.80651 | 0.358971 | common.py | pypi |
import logging
import numpy as np
from typing import List, Union
import pycocotools.mask as mask_util
import torch
from PIL import Image
from detectron2.structures import (
BitMasks,
Boxes,
BoxMode,
Instances,
Keypoints,
PolygonMasks,
RotatedBoxes,
polygons_to_bitmask,
)
from detectron2... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/data/detection_utils.py | 0.908035 | 0.437403 | detection_utils.py | pypi |
import copy
import logging
import types
from collections import UserDict
from typing import List
from detectron2.utils.logger import log_first_n
__all__ = ["DatasetCatalog", "MetadataCatalog", "Metadata"]
class _DatasetCatalog(UserDict):
"""
A global dictionary that stores information about the datasets and... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/data/catalog.py | 0.83193 | 0.460592 | catalog.py | pypi |
import logging
import numpy as np
from itertools import count
from typing import List, Tuple
import torch
import tqdm
from fvcore.common.timer import Timer
from detectron2.utils import comm
from .build import build_batch_data_loader
from .common import DatasetFromList, MapDataset
from .samplers import TrainingSampler... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/data/benchmark.py | 0.911876 | 0.340759 | benchmark.py | pypi |
import copy
import logging
import numpy as np
from typing import List, Optional, Union
import torch
from detectron2.config import configurable
from . import detection_utils as utils
from . import transforms as T
"""
This file contains the default mapping that's applied to "dataset dicts".
"""
__all__ = ["DatasetMap... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/data/dataset_mapper.py | 0.94488 | 0.49884 | dataset_mapper.py | pypi |
import itertools
import logging
import math
from collections import defaultdict
from typing import Optional
import torch
from torch.utils.data.sampler import Sampler
from detectron2.utils import comm
logger = logging.getLogger(__name__)
class TrainingSampler(Sampler):
"""
In training, we only care about the... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/data/samplers/distributed_sampler.py | 0.918745 | 0.574484 | distributed_sampler.py | pypi |
import numpy as np
import sys
from typing import Tuple
import torch
from fvcore.transforms.transform import (
BlendTransform,
CropTransform,
HFlipTransform,
NoOpTransform,
PadTransform,
Transform,
TransformList,
VFlipTransform,
)
from PIL import Image
from .augmentation import Augmentat... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/data/transforms/augmentation_impl.py | 0.818156 | 0.634883 | augmentation_impl.py | pypi |
# All coco categories, together with their nice-looking visualization colors
# It's from https://github.com/cocodataset/panopticapi/blob/master/panoptic_coco_categories.json
COCO_CATEGORIES = [
{"color": [220, 20, 60], "isthing": 1, "id": 1, "name": "person"},
{"color": [119, 11, 32], "isthing": 1, "id": 2, "na... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/data/datasets/builtin_meta.py | 0.772831 | 0.690647 | builtin_meta.py | pypi |
# fmt: off
LVIS_CATEGORIES = [{'frequency': 'c', 'synset': 'aerosol.n.02', 'synonyms': ['aerosol_can', 'spray_can'], 'id': 1, 'def': 'a dispenser that holds a substance under pressure', 'name': 'aerosol_can'}, {'frequency': 'f', 'synset': 'air_conditioner.n.01', 'synonyms': ['air_conditioner'], 'id': 2, 'def': 'a mach... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/data/datasets/lvis_v1_categories.py | 0.483892 | 0.390883 | lvis_v1_categories.py | pypi |
import copy
import json
import os
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.utils.file_io import PathManager
from .coco import load_coco_json, load_sem_seg
__all__ = ["register_coco_panoptic", "register_coco_panoptic_separated"]
def load_coco_panoptic_json(json_file, image_dir, gt... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/data/datasets/coco_panoptic.py | 0.631935 | 0.385086 | coco_panoptic.py | pypi |
import logging
import os
from fvcore.common.timer import Timer
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.structures import BoxMode
from detectron2.utils.file_io import PathManager
from .builtin_meta import _get_coco_instances_meta
from .lvis_v0_5_categories import LVIS_CATEGORIES as ... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/data/datasets/lvis.py | 0.675015 | 0.259732 | lvis.py | pypi |
import json
import logging
import os
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.data.datasets.builtin_meta import CITYSCAPES_CATEGORIES
from detectron2.utils.file_io import PathManager
"""
This file contains functions to register the Cityscapes panoptic dataset to the DatasetCatalog.
... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/data/datasets/cityscapes_panoptic.py | 0.61682 | 0.386474 | cityscapes_panoptic.py | pypi |
import functools
import json
import logging
import multiprocessing as mp
import numpy as np
import os
from itertools import chain
import pycocotools.mask as mask_util
from PIL import Image
from detectron2.structures import BoxMode
from detectron2.utils.comm import get_world_size
from detectron2.utils.file_io import Pa... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/data/datasets/cityscapes.py | 0.674372 | 0.305607 | cityscapes.py | pypi |
# fmt: off
LVIS_CATEGORIES = [{'frequency': 'r', 'id': 1, 'synset': 'acorn.n.01', 'synonyms': ['acorn'], 'def': 'nut from an oak tree', 'name': 'acorn'}, {'frequency': 'c', 'id': 2, 'synset': 'aerosol.n.02', 'synonyms': ['aerosol_can', 'spray_can'], 'def': 'a dispenser that holds a substance under pressure', 'name': '... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/data/datasets/lvis_v0_5_categories.py | 0.500244 | 0.339034 | lvis_v0_5_categories.py | pypi |
import logging
from contextlib import contextmanager
from functools import wraps
import torch
__all__ = ["retry_if_cuda_oom"]
@contextmanager
def _ignore_torch_cuda_oom():
"""
A context which ignores CUDA OOM exception from pytorch.
"""
try:
yield
except RuntimeError as e:
# NOTE... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/utils/memory.py | 0.870432 | 0.369656 | memory.py | pypi |
import numpy as np
import random
__all__ = ["colormap", "random_color", "random_colors"]
# fmt: off
# RGB:
_COLORS = np.array(
[
0.000, 0.447, 0.741,
0.850, 0.325, 0.098,
0.929, 0.694, 0.125,
0.494, 0.184, 0.556,
0.466, 0.674, 0.188,
0.301, 0.745, 0.933,
0.6... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/utils/colormap.py | 0.710729 | 0.355663 | colormap.py | pypi |
import functools
import numpy as np
import torch
import torch.distributed as dist
_LOCAL_PROCESS_GROUP = None
"""
A torch process group which only includes processes that on the same machine as the current process.
This variable is set when processes are spawned by `launch()` in "engine/launch.py".
"""
def get_world... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/utils/comm.py | 0.902876 | 0.495606 | comm.py | pypi |
import typing
from typing import Any, List
import fvcore
from fvcore.nn import activation_count, flop_count, parameter_count, parameter_count_table
from torch import nn
from detectron2.export import TracingAdapter
__all__ = [
"activation_count_operators",
"flop_count_operators",
"parameter_count_table",
... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/detectron2/utils/analysis.py | 0.840521 | 0.545104 | analysis.py | pypi |
import platform
from pathlib import Path
import cv2
from ultralytics.nn.autobackend import AutoBackend
from ultralytics.yolo.cfg import get_cfg
from ultralytics.yolo.data import load_inference_source
from ultralytics.yolo.data.augment import classify_transforms
from ultralytics.yolo.utils import DEFAULT_CFG, LOGGER, ... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/ultralytics/yolo/engine/predictor.py | 0.711932 | 0.158826 | predictor.py | pypi |
from copy import deepcopy
from functools import lru_cache
from pathlib import Path
import numpy as np
import torch
from ultralytics.yolo.data.augment import LetterBox
from ultralytics.yolo.utils import LOGGER, SimpleClass, deprecation_warn, ops
from ultralytics.yolo.utils.plotting import Annotator, colors, save_one_b... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/ultralytics/yolo/engine/results.py | 0.799912 | 0.459743 | results.py | pypi |
import contextlib
import re
import shutil
import sys
from difflib import get_close_matches
from pathlib import Path
from types import SimpleNamespace
from typing import Dict, List, Union
from ultralytics.yolo.utils import (DEFAULT_CFG, DEFAULT_CFG_DICT, DEFAULT_CFG_PATH, LOGGER, ROOT, USER_CONFIG_DIR,
... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/ultralytics/yolo/cfg/__init__.py | 0.654453 | 0.23995 | __init__.py | pypi |
from copy import copy
import torch
import torch.nn as nn
from ultralytics.nn.tasks import PoseModel
from ultralytics.yolo import v8
from ultralytics.yolo.utils import DEFAULT_CFG
from ultralytics.yolo.utils.loss import KeypointLoss
from ultralytics.yolo.utils.metrics import OKS_SIGMA
from ultralytics.yolo.utils.ops ... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/ultralytics/yolo/v8/pose/train.py | 0.824533 | 0.199698 | train.py | pypi |
from itertools import repeat
from multiprocessing.pool import ThreadPool
from pathlib import Path
import cv2
import numpy as np
import torch
import torchvision
from tqdm import tqdm
from ..utils import LOCAL_RANK, NUM_THREADS, TQDM_BAR_FORMAT, is_dir_writeable
from .augment import Compose, Format, Instances, LetterB... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/ultralytics/yolo/data/dataset.py | 0.735262 | 0.385143 | dataset.py | pypi |
from ultralytics.yolo.utils import LOGGER
try:
from ray import tune
from ray.air import RunConfig, session # noqa
from ray.air.integrations.wandb import WandbLoggerCallback # noqa
from ray.tune.schedulers import ASHAScheduler # noqa
from ray.tune.schedulers import AsyncHyperBandScheduler as AHB ... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/ultralytics/yolo/utils/tuner.py | 0.677474 | 0.317466 | tuner.py | pypi |
import platform
import time
from pathlib import Path
from ultralytics import YOLO
from ultralytics.yolo.engine.exporter import export_formats
from ultralytics.yolo.utils import LINUX, LOGGER, MACOS, ROOT, SETTINGS
from ultralytics.yolo.utils.checks import check_yolo
from ultralytics.yolo.utils.downloads import downloa... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/ultralytics/yolo/utils/benchmarks.py | 0.446977 | 0.246669 | benchmarks.py | pypi |
from copy import deepcopy
import numpy as np
import torch
from ultralytics.yolo.utils import LOGGER, colorstr
from ultralytics.yolo.utils.torch_utils import profile
def check_train_batch_size(model, imgsz=640, amp=True):
"""
Check YOLO training batch size using the autobatch() function.
Args:
m... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/ultralytics/yolo/utils/autobatch.py | 0.926844 | 0.544559 | autobatch.py | pypi |
from collections import defaultdict
from copy import deepcopy
# Trainer callbacks ----------------------------------------------------------------------------------------------------
def on_pretrain_routine_start(trainer):
pass
def on_pretrain_routine_end(trainer):
pass
def on_train_start(trainer):
pa... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/ultralytics/yolo/utils/callbacks/base.py | 0.655667 | 0.267943 | base.py | pypi |
import os
from pathlib import Path
from ultralytics.yolo.utils import LOGGER, RANK, TESTS_RUNNING, ops
from ultralytics.yolo.utils.torch_utils import get_flops, get_num_params
try:
import comet_ml
assert not TESTS_RUNNING # do not log pytest
assert hasattr(comet_ml, '__version__') # verify package is n... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/ultralytics/yolo/utils/callbacks/comet.py | 0.527803 | 0.22378 | comet.py | pypi |
import os
import platform
import shutil
import sys
import threading
import time
from pathlib import Path
from random import random
import requests
from tqdm import tqdm
from ultralytics.yolo.utils import (ENVIRONMENT, LOGGER, ONLINE, RANK, SETTINGS, TESTS_RUNNING, TQDM_BAR_FORMAT,
... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/ultralytics/hub/utils.py | 0.604516 | 0.170232 | utils.py | pypi |
import requests
from ultralytics.hub.auth import Auth
from ultralytics.hub.utils import PREFIX
from ultralytics.yolo.utils import LOGGER, SETTINGS, USER_CONFIG_DIR, yaml_save
def login(api_key=''):
"""
Log in to the Ultralytics HUB API using the provided API key.
Args:
api_key (str, optional): ... | /roof_mask_Yv8-0.5.9-py3-none-any.whl/ultralytics/hub/__init__.py | 0.811041 | 0.289962 | __init__.py | pypi |
import logging
from typing import List, Optional, Tuple
from .config import CfgNode as CN
from .defaults import _C
__all__ = ["upgrade_config", "downgrade_config"]
def upgrade_config(cfg: CN, to_version: Optional[int] = None) -> CN:
"""
Upgrade a config from its current version to a newer version.
Args... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/config/compat.py | 0.846895 | 0.197367 | compat.py | pypi |
import functools
import inspect
import logging
from fvcore.common.config import CfgNode as _CfgNode
from detectron2.utils.file_io import PathManager
class CfgNode(_CfgNode):
"""
The same as `fvcore.common.config.CfgNode`, but different in:
1. Use unsafe yaml loading by default.
Note that this ma... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/config/config.py | 0.777131 | 0.214825 | config.py | pypi |
import copy
import io
import logging
import numpy as np
from typing import List
import onnx
import torch
from caffe2.proto import caffe2_pb2
from caffe2.python import core
from caffe2.python.onnx.backend import Caffe2Backend
from tabulate import tabulate
from termcolor import colored
from torch.onnx import OperatorExp... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/export/caffe2_export.py | 0.894703 | 0.335174 | caffe2_export.py | pypi |
import os
import torch
from detectron2.utils.file_io import PathManager
from .torchscript_patch import freeze_training_mode, patch_instances
__all__ = ["scripting_with_instances", "dump_torchscript_IR"]
def scripting_with_instances(model, fields):
"""
Run :func:`torch.jit.script` on a model that uses the ... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/export/torchscript.py | 0.824285 | 0.529446 | torchscript.py | pypi |
import copy
import logging
import os
import torch
from caffe2.proto import caffe2_pb2
from torch import nn
from detectron2.config import CfgNode
from detectron2.utils.file_io import PathManager
from .caffe2_inference import ProtobufDetectionModel
from .caffe2_modeling import META_ARCH_CAFFE2_EXPORT_TYPE_MAP, convert_... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/export/api.py | 0.855127 | 0.417925 | api.py | pypi |
import contextlib
from unittest import mock
import torch
from detectron2.modeling import poolers
from detectron2.modeling.proposal_generator import rpn
from detectron2.modeling.roi_heads import keypoint_head, mask_head
from detectron2.modeling.roi_heads.fast_rcnn import FastRCNNOutputLayers
from .c10 import (
Ca... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/export/caffe2_patch.py | 0.849691 | 0.251625 | caffe2_patch.py | pypi |
import copy
import itertools
import numpy as np
from typing import Any, Iterator, List, Union
import pycocotools.mask as mask_util
import torch
from torch import device
from detectron2.layers.roi_align import ROIAlign
from detectron2.utils.memory import retry_if_cuda_oom
from .boxes import Boxes
def polygon_area(x,... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/structures/masks.py | 0.941439 | 0.650503 | masks.py | pypi |
import itertools
from typing import Any, Dict, List, Tuple, Union
import torch
class Instances:
"""
This class represents a list of instances in an image.
It stores the attributes of instances (e.g., boxes, masks, labels, scores) as "fields".
All fields must have the same ``__len__`` which is the numb... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/structures/instances.py | 0.902262 | 0.67662 | instances.py | pypi |
from __future__ import division
from typing import Any, List, Tuple
import torch
from torch import device
from torch.nn import functional as F
from detectron2.layers.wrappers import move_device_like, shapes_to_tensor
class ImageList(object):
"""
Structure that holds a list of images (of possibly
varying ... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/structures/image_list.py | 0.924432 | 0.686091 | image_list.py | pypi |
import numpy as np
from typing import Any, List, Tuple, Union
import torch
from torch.nn import functional as F
class Keypoints:
"""
Stores keypoint **annotation** data. GT Instances have a `gt_keypoints` property
containing the x,y location and visibility flag of each keypoint. This tensor has shape
... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/structures/keypoints.py | 0.938674 | 0.802942 | keypoints.py | pypi |
import logging
from detectron2.utils.file_io import PathHandler, PathManager
class ModelCatalog(object):
"""
Store mappings from names to third-party models.
"""
S3_C2_DETECTRON_PREFIX = "https://dl.fbaipublicfiles.com/detectron"
# MSRA models have STRIDE_IN_1X1=True. False otherwise.
# NOT... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/checkpoint/catalog.py | 0.600071 | 0.286731 | catalog.py | pypi |
import argparse
import logging
import os
import sys
import weakref
from collections import OrderedDict
from typing import Optional
import torch
from fvcore.nn.precise_bn import get_bn_modules
from omegaconf import OmegaConf
from torch.nn.parallel import DistributedDataParallel
import detectron2.data.transforms as T
fr... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/engine/defaults.py | 0.778439 | 0.187021 | defaults.py | pypi |
import datetime
import itertools
import logging
import math
import operator
import os
import tempfile
import time
import warnings
from collections import Counter
import torch
from fvcore.common.checkpoint import Checkpointer
from fvcore.common.checkpoint import PeriodicCheckpointer as _PeriodicCheckpointer
from fvcore... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/engine/hooks.py | 0.757705 | 0.225843 | hooks.py | pypi |
import logging
import math
from bisect import bisect_right
from typing import List
import torch
from fvcore.common.param_scheduler import (
CompositeParamScheduler,
ConstantParamScheduler,
LinearParamScheduler,
ParamScheduler,
)
logger = logging.getLogger(__name__)
class WarmupParamScheduler(Composit... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/solver/lr_scheduler.py | 0.924611 | 0.550064 | lr_scheduler.py | pypi |
import torch
from detectron2.layers import nonzero_tuple
__all__ = ["subsample_labels"]
def subsample_labels(
labels: torch.Tensor, num_samples: int, positive_fraction: float, bg_label: int
):
"""
Return `num_samples` (or fewer, if not enough found)
random samples from `labels` which is a mixture of... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/sampling.py | 0.935744 | 0.770551 | sampling.py | pypi |
import itertools
import logging
import numpy as np
from collections import OrderedDict
from collections.abc import Mapping
from typing import Dict, List, Optional, Tuple, Union
import torch
from omegaconf import DictConfig, OmegaConf
from torch import Tensor, nn
from detectron2.layers import ShapeSpec
from detectron2.... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/mmdet_wrapper.py | 0.928149 | 0.40539 | mmdet_wrapper.py | pypi |
import torch
from torch.nn import functional as F
from detectron2.structures import Instances, ROIMasks
# perhaps should rename to "resize_instance"
def detector_postprocess(
results: Instances, output_height: int, output_width: int, mask_threshold: float = 0.5
):
"""
Resize the output instances.
The... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/postprocessing.py | 0.859266 | 0.747363 | postprocessing.py | pypi |
import collections
import math
from typing import List
import torch
from torch import nn
from detectron2.config import configurable
from detectron2.layers import ShapeSpec, move_device_like
from detectron2.structures import Boxes, RotatedBoxes
from detectron2.utils.registry import Registry
ANCHOR_GENERATOR_REGISTRY =... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/anchor_generator.py | 0.943971 | 0.433981 | anchor_generator.py | pypi |
import math
from typing import List, Tuple, Union
import torch
from fvcore.nn import giou_loss, smooth_l1_loss
from torch.nn import functional as F
from detectron2.layers import cat, ciou_loss, diou_loss
from detectron2.structures import Boxes
# Value for clamping large dw and dh predictions. The heuristic is that we... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/box_regression.py | 0.9605 | 0.644281 | box_regression.py | pypi |
import math
import fvcore.nn.weight_init as weight_init
import torch
import torch.nn.functional as F
from torch import nn
from detectron2.layers import Conv2d, ShapeSpec, get_norm
from .backbone import Backbone
from .build import BACKBONE_REGISTRY
from .resnet import build_resnet_backbone
__all__ = ["build_resnet_fp... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/backbone/fpn.py | 0.931009 | 0.435902 | fpn.py | pypi |
import numpy as np
from torch import nn
from detectron2.layers import CNNBlockBase, ShapeSpec, get_norm
from .backbone import Backbone
__all__ = [
"AnyNet",
"RegNet",
"ResStem",
"SimpleStem",
"VanillaBlock",
"ResBasicBlock",
"ResBottleneckBlock",
]
def conv2d(w_in, w_out, k, *, stride=1... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/backbone/regnet.py | 0.983447 | 0.608478 | regnet.py | pypi |
import numpy as np
import fvcore.nn.weight_init as weight_init
import torch
import torch.nn.functional as F
from torch import nn
from detectron2.layers import (
CNNBlockBase,
Conv2d,
DeformConv,
ModulatedDeformConv,
ShapeSpec,
get_norm,
)
from .backbone import Backbone
from .build import BACKB... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/backbone/resnet.py | 0.877405 | 0.386619 | resnet.py | pypi |
import logging
import numpy as np
from typing import Dict, List, Optional, Tuple
import torch
from torch import nn
from detectron2.config import configurable
from detectron2.data.detection_utils import convert_image_to_rgb
from detectron2.layers import move_device_like
from detectron2.structures import ImageList, Inst... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/meta_arch/rcnn.py | 0.947974 | 0.418816 | rcnn.py | pypi |
import numpy as np
from typing import Dict, List, Optional, Tuple
import torch
from torch import Tensor, nn
from detectron2.data.detection_utils import convert_image_to_rgb
from detectron2.layers import move_device_like
from detectron2.modeling import Backbone
from detectron2.structures import Boxes, ImageList, Instan... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/meta_arch/dense_detector.py | 0.956856 | 0.630813 | dense_detector.py | pypi |
import numpy as np
from typing import Callable, Dict, Optional, Tuple, Union
import fvcore.nn.weight_init as weight_init
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import configurable
from detectron2.layers import Conv2d, ShapeSpec, get_norm
from detectron2.structures... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/meta_arch/semantic_seg.py | 0.94474 | 0.461017 | semantic_seg.py | pypi |
import logging
import math
from typing import List, Tuple
import torch
from fvcore.nn import sigmoid_focal_loss_jit
from torch import Tensor, nn
from torch.nn import functional as F
from detectron2.config import configurable
from detectron2.layers import CycleBatchNormList, ShapeSpec, batched_nms, cat, get_norm
from d... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/meta_arch/retinanet.py | 0.930387 | 0.324704 | retinanet.py | pypi |
import logging
from typing import Dict, List
import torch
from torch import nn
from detectron2.config import configurable
from detectron2.structures import ImageList
from ..postprocessing import detector_postprocess, sem_seg_postprocess
from .build import META_ARCH_REGISTRY
from .rcnn import GeneralizedRCNN
from .se... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/meta_arch/panoptic_fpn.py | 0.946163 | 0.257975 | panoptic_fpn.py | pypi |
import logging
import math
from typing import List, Tuple, Union
import torch
from detectron2.layers import batched_nms, cat, move_device_like
from detectron2.structures import Boxes, Instances
logger = logging.getLogger(__name__)
def _is_tracing():
# (fixed in TORCH_VERSION >= 1.9)
if torch.jit.is_scriptin... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/proposal_generator/proposal_utils.py | 0.902076 | 0.469155 | proposal_utils.py | pypi |
import itertools
import logging
from typing import Dict, List
import torch
from detectron2.config import configurable
from detectron2.layers import ShapeSpec, batched_nms_rotated, cat
from detectron2.structures import Instances, RotatedBoxes, pairwise_iou_rotated
from detectron2.utils.memory import retry_if_cuda_oom
... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/proposal_generator/rrpn.py | 0.89204 | 0.351826 | rrpn.py | pypi |
import inspect
import logging
import numpy as np
from typing import Dict, List, Optional, Tuple
import torch
from torch import nn
from detectron2.config import configurable
from detectron2.layers import ShapeSpec, nonzero_tuple
from detectron2.structures import Boxes, ImageList, Instances, pairwise_iou
from detectron2... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/roi_heads/roi_heads.py | 0.907487 | 0.541954 | roi_heads.py | pypi |
from typing import List
import fvcore.nn.weight_init as weight_init
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import configurable
from detectron2.layers import Conv2d, ConvTranspose2d, ShapeSpec, cat, get_norm
from detectron2.layers.wrappers import move_device_like
f... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/roi_heads/mask_head.py | 0.959345 | 0.578329 | mask_head.py | pypi |
from typing import List
import torch
from torch import nn
from torch.autograd.function import Function
from detectron2.config import configurable
from detectron2.layers import ShapeSpec
from detectron2.structures import Boxes, Instances, pairwise_iou
from detectron2.utils.events import get_event_storage
from ..box_re... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/roi_heads/cascade_rcnn.py | 0.947986 | 0.480235 | cascade_rcnn.py | pypi |
import logging
import numpy as np
import torch
from detectron2.config import configurable
from detectron2.layers import ShapeSpec, batched_nms_rotated
from detectron2.structures import Instances, RotatedBoxes, pairwise_iou_rotated
from detectron2.utils.events import get_event_storage
from ..box_regression import Box2... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/roi_heads/rotated_fast_rcnn.py | 0.926012 | 0.584212 | rotated_fast_rcnn.py | pypi |
import numpy as np
from typing import List
import fvcore.nn.weight_init as weight_init
import torch
from torch import nn
from detectron2.config import configurable
from detectron2.layers import Conv2d, ShapeSpec, get_norm
from detectron2.utils.registry import Registry
__all__ = ["FastRCNNConvFCHead", "build_box_head"... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/roi_heads/box_head.py | 0.934671 | 0.421016 | box_head.py | pypi |
from typing import List
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import configurable
from detectron2.layers import Conv2d, ConvTranspose2d, cat, interpolate
from detectron2.structures import Instances, heatmaps_to_keypoints
from detectron2.utils.events import get_ev... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/modeling/roi_heads/keypoint_head.py | 0.965892 | 0.535706 | keypoint_head.py | pypi |
import copy
import logging
import numpy as np
import time
from pycocotools.cocoeval import COCOeval
from detectron2 import _C
logger = logging.getLogger(__name__)
class COCOeval_opt(COCOeval):
"""
This is a slightly modified version of the original COCO API, where the functions evaluateImg()
and accumul... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/evaluation/fast_eval_api.py | 0.661158 | 0.413181 | fast_eval_api.py | pypi |
import datetime
import logging
import time
from collections import OrderedDict, abc
from contextlib import ExitStack, contextmanager
from typing import List, Union
import torch
from torch import nn
from detectron2.utils.comm import get_world_size, is_main_process
from detectron2.utils.logger import log_every_n_seconds... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/evaluation/evaluator.py | 0.931851 | 0.600569 | evaluator.py | pypi |
import glob
import logging
import numpy as np
import os
import tempfile
from collections import OrderedDict
import torch
from PIL import Image
from detectron2.data import MetadataCatalog
from detectron2.utils import comm
from detectron2.utils.file_io import PathManager
from .evaluator import DatasetEvaluator
class ... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/evaluation/cityscapes_evaluation.py | 0.530236 | 0.248409 | cityscapes_evaluation.py | pypi |
import itertools
import json
import numpy as np
import os
import torch
from pycocotools.cocoeval import COCOeval, maskUtils
from detectron2.structures import BoxMode, RotatedBoxes, pairwise_iou_rotated
from detectron2.utils.file_io import PathManager
from .coco_evaluation import COCOEvaluator
class RotatedCOCOeval(... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/evaluation/rotated_coco_evaluation.py | 0.565539 | 0.441974 | rotated_coco_evaluation.py | pypi |
import copy
import itertools
import json
import logging
import os
import pickle
from collections import OrderedDict
import torch
import detectron2.utils.comm as comm
from detectron2.config import CfgNode
from detectron2.data import MetadataCatalog
from detectron2.structures import Boxes, BoxMode, pairwise_iou
from det... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/evaluation/lvis_evaluation.py | 0.746509 | 0.296349 | lvis_evaluation.py | pypi |
import itertools
import json
import logging
import numpy as np
import os
from collections import OrderedDict
from typing import Optional, Union
import pycocotools.mask as mask_util
import torch
from PIL import Image
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.utils.comm import all_gathe... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/evaluation/sem_seg_evaluation.py | 0.811863 | 0.333286 | sem_seg_evaluation.py | pypi |
import contextlib
import io
import itertools
import json
import logging
import numpy as np
import os
import tempfile
from collections import OrderedDict
from typing import Optional
from PIL import Image
from tabulate import tabulate
from detectron2.data import MetadataCatalog
from detectron2.utils import comm
from det... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/evaluation/panoptic_evaluation.py | 0.726426 | 0.206634 | panoptic_evaluation.py | pypi |
import torch
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
class _ROIAlignRotated(Function):
@staticmethod
def forward(ctx, input, roi, output_size, spatial_scale, sampling_ratio):
ctx.save_for_... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/layers/roi_align_rotated.py | 0.940463 | 0.514156 | roi_align_rotated.py | pypi |
import math
import torch
def diou_loss(
boxes1: torch.Tensor,
boxes2: torch.Tensor,
reduction: str = "none",
eps: float = 1e-7,
) -> torch.Tensor:
"""
Distance Intersection over Union Loss (Zhaohui Zheng et. al)
https://arxiv.org/abs/1911.08287
Args:
boxes1, boxes2 (Tensor): bo... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/layers/losses.py | 0.721253 | 0.849535 | losses.py | pypi |
from torch import nn
from torchvision.ops import roi_align
# NOTE: torchvision's RoIAlign has a different default aligned=False
class ROIAlign(nn.Module):
def __init__(self, output_size, spatial_scale, sampling_ratio, aligned=True):
"""
Args:
output_size (tuple): h, w
spati... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/layers/roi_align.py | 0.956937 | 0.746093 | roi_align.py | pypi |
from copy import deepcopy
import fvcore.nn.weight_init as weight_init
import torch
from torch import nn
from torch.nn import functional as F
from .batch_norm import get_norm
from .blocks import DepthwiseSeparableConv2d
from .wrappers import Conv2d
class ASPP(nn.Module):
"""
Atrous Spatial Pyramid Pooling (A... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/layers/aspp.py | 0.949599 | 0.566498 | aspp.py | pypi |
from typing import List, Optional
import torch
from torch.nn import functional as F
def shapes_to_tensor(x: List[int], device: Optional[torch.device] = None) -> torch.Tensor:
"""
Turn a list of integer scalars or integer Tensor scalars into a vector,
in a way that's both traceable and scriptable.
In ... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/layers/wrappers.py | 0.96796 | 0.776496 | wrappers.py | pypi |
import fvcore.nn.weight_init as weight_init
from torch import nn
from .batch_norm import FrozenBatchNorm2d, get_norm
from .wrappers import Conv2d
"""
CNN building blocks.
"""
class CNNBlockBase(nn.Module):
"""
A CNN block is assumed to have input channels, output channels and a stride.
The input and o... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/layers/blocks.py | 0.962276 | 0.501648 | blocks.py | pypi |
import copy
import numpy as np
from typing import Dict
import torch
from scipy.optimize import linear_sum_assignment
from detectron2.config import configurable
from detectron2.structures import Boxes, Instances
from ..config.config import CfgNode as CfgNode_
from .base_tracker import BaseTracker
class BaseHungarian... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/tracking/hungarian_tracker.py | 0.842021 | 0.367242 | hungarian_tracker.py | pypi |
from detectron2.config import configurable
from detectron2.utils.registry import Registry
from ..config.config import CfgNode as CfgNode_
from ..structures import Instances
TRACKER_HEADS_REGISTRY = Registry("TRACKER_HEADS")
TRACKER_HEADS_REGISTRY.__doc__ = """
Registry for tracking classes.
"""
class BaseTracker(ob... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/tracking/base_tracker.py | 0.72086 | 0.23118 | base_tracker.py | pypi |
import copy
import numpy as np
from typing import List
import torch
from detectron2.config import configurable
from detectron2.structures import Boxes, Instances
from detectron2.structures.boxes import pairwise_iou
from ..config.config import CfgNode as CfgNode_
from .base_tracker import TRACKER_HEADS_REGISTRY, BaseT... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/tracking/bbox_iou_tracker.py | 0.843911 | 0.318141 | bbox_iou_tracker.py | pypi |
import numpy as np
from typing import List
from detectron2.config import CfgNode as CfgNode_
from detectron2.config import configurable
from detectron2.structures import Instances
from detectron2.structures.boxes import pairwise_iou
from detectron2.tracking.utils import LARGE_COST_VALUE, create_prediction_pairs
from... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/tracking/vanilla_hungarian_bbox_iou_tracker.py | 0.926408 | 0.440409 | vanilla_hungarian_bbox_iou_tracker.py | pypi |
import numpy as np
from typing import List
from detectron2.config import CfgNode as CfgNode_
from detectron2.config import configurable
from .base_tracker import TRACKER_HEADS_REGISTRY
from .vanilla_hungarian_bbox_iou_tracker import VanillaHungarianBBoxIOUTracker
@TRACKER_HEADS_REGISTRY.register()
class IOUWeighte... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/tracking/iou_weighted_hungarian_bbox_iou_tracker.py | 0.926429 | 0.403097 | iou_weighted_hungarian_bbox_iou_tracker.py | pypi |
import copy
import itertools
import logging
import numpy as np
import pickle
import random
import torch.utils.data as data
from torch.utils.data.sampler import Sampler
from detectron2.utils.serialize import PicklableWrapper
__all__ = ["MapDataset", "DatasetFromList", "AspectRatioGroupedDataset", "ToIterableDataset"]
... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/data/common.py | 0.80651 | 0.358971 | common.py | pypi |
import logging
import numpy as np
from typing import List, Union
import pycocotools.mask as mask_util
import torch
from PIL import Image
from detectron2.structures import (
BitMasks,
Boxes,
BoxMode,
Instances,
Keypoints,
PolygonMasks,
RotatedBoxes,
polygons_to_bitmask,
)
from detectron2... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/data/detection_utils.py | 0.908035 | 0.437403 | detection_utils.py | pypi |
import copy
import logging
import types
from collections import UserDict
from typing import List
from detectron2.utils.logger import log_first_n
__all__ = ["DatasetCatalog", "MetadataCatalog", "Metadata"]
class _DatasetCatalog(UserDict):
"""
A global dictionary that stores information about the datasets and... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/data/catalog.py | 0.83193 | 0.460592 | catalog.py | pypi |
import logging
import numpy as np
from itertools import count
from typing import List, Tuple
import torch
import tqdm
from fvcore.common.timer import Timer
from detectron2.utils import comm
from .build import build_batch_data_loader
from .common import DatasetFromList, MapDataset
from .samplers import TrainingSampler... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/data/benchmark.py | 0.911876 | 0.340759 | benchmark.py | pypi |
import copy
import logging
import numpy as np
from typing import List, Optional, Union
import torch
from detectron2.config import configurable
from . import detection_utils as utils
from . import transforms as T
"""
This file contains the default mapping that's applied to "dataset dicts".
"""
__all__ = ["DatasetMap... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/data/dataset_mapper.py | 0.94488 | 0.49884 | dataset_mapper.py | pypi |
import itertools
import logging
import math
from collections import defaultdict
from typing import Optional
import torch
from torch.utils.data.sampler import Sampler
from detectron2.utils import comm
logger = logging.getLogger(__name__)
class TrainingSampler(Sampler):
"""
In training, we only care about the... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/data/samplers/distributed_sampler.py | 0.918745 | 0.574484 | distributed_sampler.py | pypi |
import numpy as np
import sys
from typing import Tuple
import torch
from fvcore.transforms.transform import (
BlendTransform,
CropTransform,
HFlipTransform,
NoOpTransform,
PadTransform,
Transform,
TransformList,
VFlipTransform,
)
from PIL import Image
from .augmentation import Augmentat... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/data/transforms/augmentation_impl.py | 0.818156 | 0.634883 | augmentation_impl.py | pypi |
# All coco categories, together with their nice-looking visualization colors
# It's from https://github.com/cocodataset/panopticapi/blob/master/panoptic_coco_categories.json
COCO_CATEGORIES = [
{"color": [220, 20, 60], "isthing": 1, "id": 1, "name": "person"},
{"color": [119, 11, 32], "isthing": 1, "id": 2, "na... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/data/datasets/builtin_meta.py | 0.772831 | 0.690647 | builtin_meta.py | pypi |
# fmt: off
LVIS_CATEGORIES = [{'frequency': 'c', 'synset': 'aerosol.n.02', 'synonyms': ['aerosol_can', 'spray_can'], 'id': 1, 'def': 'a dispenser that holds a substance under pressure', 'name': 'aerosol_can'}, {'frequency': 'f', 'synset': 'air_conditioner.n.01', 'synonyms': ['air_conditioner'], 'id': 2, 'def': 'a mach... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/data/datasets/lvis_v1_categories.py | 0.483892 | 0.390883 | lvis_v1_categories.py | pypi |
import copy
import json
import os
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.utils.file_io import PathManager
from .coco import load_coco_json, load_sem_seg
__all__ = ["register_coco_panoptic", "register_coco_panoptic_separated"]
def load_coco_panoptic_json(json_file, image_dir, gt... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/data/datasets/coco_panoptic.py | 0.631935 | 0.385086 | coco_panoptic.py | pypi |
import logging
import os
from fvcore.common.timer import Timer
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.structures import BoxMode
from detectron2.utils.file_io import PathManager
from .builtin_meta import _get_coco_instances_meta
from .lvis_v0_5_categories import LVIS_CATEGORIES as ... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/data/datasets/lvis.py | 0.675015 | 0.259732 | lvis.py | pypi |
import json
import logging
import os
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.data.datasets.builtin_meta import CITYSCAPES_CATEGORIES
from detectron2.utils.file_io import PathManager
"""
This file contains functions to register the Cityscapes panoptic dataset to the DatasetCatalog.
... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/data/datasets/cityscapes_panoptic.py | 0.61682 | 0.386474 | cityscapes_panoptic.py | pypi |
import functools
import json
import logging
import multiprocessing as mp
import numpy as np
import os
from itertools import chain
import pycocotools.mask as mask_util
from PIL import Image
from detectron2.structures import BoxMode
from detectron2.utils.comm import get_world_size
from detectron2.utils.file_io import Pa... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/data/datasets/cityscapes.py | 0.674372 | 0.305607 | cityscapes.py | pypi |
# fmt: off
LVIS_CATEGORIES = [{'frequency': 'r', 'id': 1, 'synset': 'acorn.n.01', 'synonyms': ['acorn'], 'def': 'nut from an oak tree', 'name': 'acorn'}, {'frequency': 'c', 'id': 2, 'synset': 'aerosol.n.02', 'synonyms': ['aerosol_can', 'spray_can'], 'def': 'a dispenser that holds a substance under pressure', 'name': '... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/data/datasets/lvis_v0_5_categories.py | 0.500244 | 0.339034 | lvis_v0_5_categories.py | pypi |
import logging
from contextlib import contextmanager
from functools import wraps
import torch
__all__ = ["retry_if_cuda_oom"]
@contextmanager
def _ignore_torch_cuda_oom():
"""
A context which ignores CUDA OOM exception from pytorch.
"""
try:
yield
except RuntimeError as e:
# NOTE... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/utils/memory.py | 0.870432 | 0.369656 | memory.py | pypi |
import numpy as np
import random
__all__ = ["colormap", "random_color", "random_colors"]
# fmt: off
# RGB:
_COLORS = np.array(
[
0.000, 0.447, 0.741,
0.850, 0.325, 0.098,
0.929, 0.694, 0.125,
0.494, 0.184, 0.556,
0.466, 0.674, 0.188,
0.301, 0.745, 0.933,
0.6... | /roof-mask-0.5.4.tar.gz/roof-mask-0.5.4/detectron2/utils/colormap.py | 0.710729 | 0.355663 | colormap.py | pypi |
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