python_code stringlengths 0 4.04M | repo_name stringlengths 8 58 | file_path stringlengths 5 147 |
|---|---|---|
# Copyright (c) Facebook, Inc. and its affiliates.
import io
import numpy as np
import os
from dataclasses import dataclass
from functools import reduce
from operator import mul
from typing import BinaryIO, Dict, Optional, Tuple
import torch
from detectron2.utils.comm import gather, get_rank
from detectron2.utils.fil... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/evaluation/tensor_storage.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .evaluator import DensePoseCOCOEvaluator
| banmo-main | third_party/detectron2_old/projects/DensePose/densepose/evaluation/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.data.catalog import Metadata
from detectron2.evaluation import COCOEvaluator
from densepose.data.datasets.coco import (
get_contiguous_id_to_category_id_map,
maybe_filter_categories_cocoapi,
)
def _maybe_add_iscrowd_annotations(cocoapi):
... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/evaluation/d2_evaluator_adapter.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
# This is a modified version of cocoeval.py where we also have the densepose evaluation.
__author__ = "tsungyi"
import cop... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/evaluation/densepose_coco_evaluation.py |
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
import copy
import io
import itertools
import logging
import numpy as np
import os
from collections import OrderedDict
from typing import Dict, Iterable, List, Optional
import pycocotools.mask as mask_utils
import torch
from p... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/evaluation/evaluator.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import itertools
import logging
import numpy as np
from collections import UserDict, defaultdict
from dataclasses import dataclass
from typing import Any, Callable, Collection, Dict, Iterable, List, Optional, Sequence, Tuple
import torch
from torch.utils.data.dataset ... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/build.py |
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
import numpy as np
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from torch.utils.data.dataset import Dataset
from detectron2.data.detection_utils import read_image
ImageTransform = Callable[[torch.... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/image_list_dataset.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import random
from typing import Any, Callable, Dict, Iterable, Iterator, List, Optional, Tuple
import torch
from torch import nn
SampledData = Any
ModelOutput = Any
def _grouper(iterable: Iterable[Any], n: int, fillvalue=None) -> Iterator[Tuple[Any]]:
"""
... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/inference_based_loader.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .meshes import builtin
from .build import (
build_detection_test_loader,
build_detection_train_loader,
build_combined_loader,
build_frame_selector,
build_inference_based_loaders,
has_inference_based_loaders,
BootstrapDatasetFactoryCata... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/__init__.py |
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import copy
import logging
from typing import Any, Dict, List, Tuple
import torch
from detectron2.data import MetadataCatalog
from detectron2.data import detection_utils as utils
from detectron2.data import transforms as T
from detectron2.laye... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/dataset_mapper.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import os
from typing import Dict, Optional
from detectron2.config import CfgNode
def is_relative_local_path(path: str):
path_str = os.fsdecode(path)
return ("://" not in path_str) and not os.path.isabs(path)
def maybe_prepend_base_path(base_path: Optiona... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import random
from collections import deque
from typing import Any, Collection, Deque, Iterable, Iterator, List, Sequence
Loader = Iterable[Any]
def _pooled_next(iterator: Iterator[Any], pool: Deque[Any]):
if not pool:
pool.extend(next(iterator))
re... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/combined_loader.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .frame_selector import (
FrameSelectionStrategy,
RandomKFramesSelector,
FirstKFramesSelector,
LastKFramesSelector,
FrameTsList,
FrameSelector,
)
from .video_keyframe_dataset import (
VideoKeyframeDataset,
video_list_from_file,
... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/video/__init__.py |
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import csv
import logging
import numpy as np
from typing import Any, Callable, Dict, List, Optional, Union
import av
import torch
from torch.utils.data.dataset import Dataset
from detectron2.utils.file_io import PathManager
from ..utils impor... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/video/video_keyframe_dataset.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import random
from collections.abc import Callable
from enum import Enum
from typing import Callable as TCallable
from typing import List
FrameTsList = List[int]
FrameSelector = TCallable[[FrameTsList], FrameTsList]
class FrameSelectionStrategy(Enum):
"""
F... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/video/frame_selector.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from typing import Optional
from detectron2.data import DatasetCatalog, MetadataCatalog
from ..utils import maybe_prepend_base_path
from .dataset_type import DatasetType
CHIMPNSEE_DATASET_NAME = "chimpnsee"
def register_dataset(datasets_root: Optional[str] = None... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/datasets/chimpnsee.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
import io
import logging
import os
from collections import defaultdict
from dataclasses import dataclass
from typing import Any, Dict, Iterable, List, Optional
from fvcore.common.timer import Timer
from detectron2.data import DatasetCatalog, Metadata... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/datasets/coco.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from . import builtin # ensure the builtin datasets are registered
__all__ = [k for k in globals().keys() if "builtin" not in k and not k.startswith("_")]
| banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/datasets/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
import os
from typing import Any, Dict, Iterable, List, Optional
from fvcore.common.timer import Timer
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.data.datasets.lvis import get_lvis_instances_meta
from detectron2.structur... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/datasets/lvis.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from enum import Enum
class DatasetType(Enum):
"""
Dataset type, mostly used for datasets that contain data to bootstrap models on
"""
VIDEO_LIST = "video_list"
| banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/datasets/dataset_type.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .chimpnsee import register_dataset as register_chimpnsee_dataset
from .coco import BASE_DATASETS as BASE_COCO_DATASETS
from .coco import DATASETS as COCO_DATASETS
from .coco import register_datasets as register_coco_datasets
from .lvis import DATASETS as LVIS_DATA... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/datasets/builtin.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
from collections import UserDict
from dataclasses import dataclass
from typing import Iterable, Optional
from ..utils import maybe_prepend_base_path
@dataclass
class MeshInfo:
name: str
data: str
geodists: Optional[str... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/meshes/catalog.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from . import builtin
__all__ = [k for k in globals().keys() if "builtin" not in k and not k.startswith("_")]
| banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/meshes/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from .catalog import MeshInfo, register_meshes
DENSEPOSE_MESHES_DIR = "https://dl.fbaipublicfiles.com/densepose/meshes/"
MESHES = [
MeshInfo(
name="smpl_27554",
data="smpl_27554.pkl",
geodists="geodists/geodists_smpl_2... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/meshes/builtin.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.structures import BitMasks, Instances
from densepose.converters import ToMaskConverter
class MaskFromDensePoseSampler:
"""
Produce mask GT from DensePose predictions
This sampler simply converts DensePose predictions to BitMasks
that... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/samplers/mask_from_densepose.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional
from detectron2.structures import Instances
ModelOutput = Dict[str, Any]
SampledData = Dict[str, Any]
@dataclass
class _Sampler:
"""
Sampler registry entry that contai... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/samplers/prediction_to_gt.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .densepose_uniform import DensePoseUniformSampler
from .densepose_confidence_based import DensePoseConfidenceBasedSampler
from .densepose_cse_uniform import DensePoseCSEUniformSampler
from .densepose_cse_confidence_based import DensePoseCSEConfidenceBasedSampler
... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/samplers/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .densepose_cse_base import DensePoseCSEBaseSampler
from .densepose_uniform import DensePoseUniformSampler
class DensePoseCSEUniformSampler(DensePoseCSEBaseSampler, DensePoseUniformSampler):
"""
Uniform Sampler for CSE
"""
pass
| banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/samplers/densepose_cse_uniform.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from typing import Any, Dict, List, Tuple
import torch
from torch.nn import functional as F
from detectron2.structures import BoxMode, Instances
from densepose.converters import ToChartResultConverter
from densepose.converters.base import IntTupleBox, make_int_box
f... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/samplers/densepose_base.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import random
import torch
from .densepose_base import DensePoseBaseSampler
class DensePoseUniformSampler(DensePoseBaseSampler):
"""
Samples DensePose data from DensePose predictions.
Samples for each class are drawn uniformly over all pixels estimated
... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/samplers/densepose_uniform.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import random
from typing import Optional, Tuple
import torch
from torch.nn import functional as F
from detectron2.config import CfgNode
from detectron2.structures import Instances
from densepose.converters.base import IntTupleBox
from .densepose_cse_base import De... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/samplers/densepose_cse_confidence_based.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import random
from typing import Optional, Tuple
import torch
from densepose.converters import ToChartResultConverterWithConfidences
from .densepose_base import DensePoseBaseSampler
class DensePoseConfidenceBasedSampler(DensePoseBaseSampler):
"""
Samples D... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/samplers/densepose_confidence_based.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from typing import Any, Dict, List, Tuple
import torch
from torch.nn import functional as F
from detectron2.config import CfgNode
from detectron2.structures import Instances
from densepose.converters.base import IntTupleBox
from densepose.data.utils import get_class... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/samplers/densepose_cse_base.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .image import ImageResizeTransform
| banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/transform/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
class ImageResizeTransform:
"""
Transform that resizes images loaded from a dataset
(BGR data in NCHW channel order, typically uint8) to a format ready to be
consumed by DensePose training (BGR float32 data in NCHW channel order)
"""... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/data/transform/image.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .trainer import Trainer
| banmo-main | third_party/detectron2_old/projects/DensePose/densepose/engine/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import os
from collections import OrderedDict
from typing import List, Optional, Union
import torch
from torch import nn
from detectron2.checkpoint import DetectionCheckpointer
from detectron2.config import CfgNode
from detectron2.e... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/engine/trainer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import random
import unittest
from densepose.data.video import FirstKFramesSelector, LastKFramesSelector, RandomKFramesSelector
class TestFrameSelector(unittest.TestCase):
def test_frame_selector_random_k_1(self):
_SEED = 43
_K = 4
rando... | banmo-main | third_party/detectron2_old/projects/DensePose/tests/test_frame_selector.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import unittest
from .common import (
get_config_files,
get_evolution_config_files,
get_hrnet_config_files,
get_quick_schedules_config_files,
setup,
)
class TestSetup(unittest.TestCase):
def _test_setup(self, config_file):
setup(conf... | banmo-main | third_party/detectron2_old/projects/DensePose/tests/test_setup.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import unittest
from densepose.structures import normalized_coords_transform
class TestStructures(unittest.TestCase):
def test_normalized_coords_transform(self):
bbox = (32, 24, 288, 216)
x0, y0, w, h = bbox
xmin, ymin, xmax, ymax = x0, ... | banmo-main | third_party/detectron2_old/projects/DensePose/tests/test_structures.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import unittest
import torch
from detectron2.structures import BitMasks, Boxes, Instances
from .common import get_model
# TODO(plabatut): Modularize detectron2 tests and re-use
def make_model_inputs(image, instances=None):
if instances is None:
return ... | banmo-main | third_party/detectron2_old/projects/DensePose/tests/test_model_e2e.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
import os
import random
import tempfile
import unittest
import torch
import torchvision.io as io
from densepose.data.transform import ImageResizeTransform
from densepose.data.video import RandomKFramesSelector, VideoKeyframeDataset
try:
import ... | banmo-main | third_party/detectron2_old/projects/DensePose/tests/test_video_keyframe_dataset.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import random
import unittest
from typing import Any, Iterable, Iterator, Tuple
from densepose.data import CombinedDataLoader
def _grouper(iterable: Iterable[Any], n: int, fillvalue=None) -> Iterator[Tuple[Any]]:
"""
Group elements of an iterable by chunks ... | banmo-main | third_party/detectron2_old/projects/DensePose/tests/test_combine_data_loader.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import unittest
import torch
from detectron2.structures import Boxes, BoxMode, Instances
from densepose.modeling.losses.utils import ChartBasedAnnotationsAccumulator
from densepose.structures import DensePoseDataRelative, DensePoseList
image_shape = (100, 100)
inst... | banmo-main | third_party/detectron2_old/projects/DensePose/tests/test_chart_based_annotations_accumulator.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import unittest
import torch
from detectron2.structures import Boxes, BoxMode, Instances
from densepose.modeling.losses.embed_utils import CseAnnotationsAccumulator
from densepose.structures import DensePoseDataRelative, DensePoseList
class Tes... | banmo-main | third_party/detectron2_old/projects/DensePose/tests/test_cse_annotations_accumulator.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import contextlib
import os
import tempfile
import unittest
import torch
from torchvision.utils import save_image
from densepose.data.image_list_dataset import ImageListDataset
from densepose.data.transform import ImageResizeTransform
@contextlib.contextmanager
def... | banmo-main | third_party/detectron2_old/projects/DensePose/tests/test_image_list_dataset.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import os
import torch
from detectron2.config import get_cfg
from detectron2.engine import default_setup
from detectron2.modeling import build_model
from densepose import add_densepose_config
_BASE_CONFIG_DIR = "configs"
_EVOLUTION_CONFIG_SUB_DIR = "evolution"
_HRN... | banmo-main | third_party/detectron2_old/projects/DensePose/tests/common.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import unittest
import torch
from densepose.data.transform import ImageResizeTransform
class TestImageResizeTransform(unittest.TestCase):
def test_image_resize_1(self):
images_batch = torch.ones((3, 3, 100, 100), dtype=torch.uint8) * 100
transfo... | banmo-main | third_party/detectron2_old/projects/DensePose/tests/test_image_resize_transform.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import io
import tempfile
import unittest
from contextlib import ExitStack
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from detectron2.utils import comm
from densepose.evaluation.tensor_storage import (
SingleProcessFileTenso... | banmo-main | third_party/detectron2_old/projects/DensePose/tests/test_tensor_storage.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import unittest
from densepose.data.datasets.builtin import COCO_DATASETS, DENSEPOSE_ANNOTATIONS_DIR, LVIS_DATASETS
from densepose.data.datasets.coco import load_coco_json
from densepose.data.datasets.lvis import load_lvis_json
from densepose.data... | banmo-main | third_party/detectron2_old/projects/DensePose/tests/test_dataset_loaded_annotations.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
"""
Panoptic-DeepLab Training Script.
This script is a simplified version of the training script in detectron2/tools.
"""
import os
import torch
import detectron2.data.transforms as T
import detectron2.utils.comm as comm
from detectron2.checkp... | banmo-main | third_party/detectron2_old/projects/Panoptic-DeepLab/train_net.py |
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.config import CfgNode as CN
from detectron2.projects.deeplab import add_deeplab_config
def add_panoptic_deeplab_config(cfg):
"""
Add config for Panoptic-DeepLab.
"""
# Reuse DeepLab config.
add_deeplab_conf... | banmo-main | third_party/detectron2_old/projects/Panoptic-DeepLab/panoptic_deeplab/config.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .config import add_panoptic_deeplab_config
from .dataset_mapper import PanopticDeeplabDatasetMapper
from .panoptic_seg import (
PanopticDeepLab,
INS_EMBED_BRANCHES_REGISTRY,
build_ins_embed_branch,
PanopticDeepLabSemSegHead,
PanopticDeepLabInsE... | banmo-main | third_party/detectron2_old/projects/Panoptic-DeepLab/panoptic_deeplab/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import copy
import logging
import numpy as np
from typing import Callable, List, Union
import torch
from panopticapi.utils import rgb2id
from detectron2.config import configurable
from detectron2.data import MetadataCatalog
from detectron2.data import detection_utils ... | banmo-main | third_party/detectron2_old/projects/Panoptic-DeepLab/panoptic_deeplab/dataset_mapper.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
from typing import Callable, Dict, List, 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.data import MetadataCatalog
... | banmo-main | third_party/detectron2_old/projects/Panoptic-DeepLab/panoptic_deeplab/panoptic_seg.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# Reference: https://github.com/bowenc0221/panoptic-deeplab/blob/master/segmentation/model/post_processing/instance_post_processing.py # noqa
from collections import Counter
import torch
import torch.nn.functional as F
def find_instance_center(center_heatmap, thres... | banmo-main | third_party/detectron2_old/projects/Panoptic-DeepLab/panoptic_deeplab/post_processing.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# Reference: https://github.com/bowenc0221/panoptic-deeplab/blob/aa934324b55a34ce95fea143aea1cb7a6dbe04bd/segmentation/data/transforms/target_transforms.py#L11 # noqa
import numpy as np
import torch
class PanopticDeepLabTargetGenerator(object):
"""
Generates... | banmo-main | third_party/detectron2_old/projects/Panoptic-DeepLab/panoptic_deeplab/target_generator.py |
#!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates.
"""
Point supervision Training Script.
This script is a simplified version of the training script in detectron2/tools.
"""
import os
import detectron2.utils.comm as comm
from detectron2.checkpoint import DetectionCheckpointer
from detectron2.co... | banmo-main | third_party/detectron2_old/projects/PointSup/train_net.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import json
import numpy as np
import os
import sys
import pycocotools.mask as mask_utils
from detectron2.utils.env import seed_all_rng
from detectron2.utils.file_io import PathManager
d... | banmo-main | third_party/detectron2_old/projects/PointSup/tools/prepare_coco_point_annotations_without_masks.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
from typing import Any, List
from detectron2.modeling import ROI_MASK_HEAD_REGISTRY
from detectron2.modeling.roi_heads.mask_head import MaskRCNNConvUpsampleHead, mask_rcnn_inference
from detectron2.projects.point_rend import Impl... | banmo-main | third_party/detectron2_old/projects/PointSup/point_sup/mask_head.py |
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
def add_point_sup_config(cfg):
"""
Add config for point supervision.
"""
# Use point annotation
cfg.INPUT.POINT_SUP = False
# Sample only part of points in each iteration.
# Default: 0, use all a... | banmo-main | third_party/detectron2_old/projects/PointSup/point_sup/config.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from . import register_point_annotations
from .config import add_point_sup_config
from .dataset_mapper import PointSupDatasetMapper
from .mask_head import MaskRCNNConvUpsamplePointSupHead
from .point_utils import get_point_coords_from_point_annotati... | banmo-main | third_party/detectron2_old/projects/PointSup/point_sup/__init__.py |
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
import torch
# fmt: off
from detectron2.data.detection_utils import \
annotations_to_instances as base_annotations_to_instances
from detectron2.data.detection_utils import \
transform_instance_ann... | banmo-main | third_party/detectron2_old/projects/PointSup/point_sup/detection_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import logging
import numpy as np
from typing import List, Union
import torch
import detectron2.data.detection_utils as utils
import detectron2.data.transforms as T
from detectron2.config import configurable
from .detection_utils impor... | banmo-main | third_party/detectron2_old/projects/PointSup/point_sup/dataset_mapper.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from detectron2.layers import cat
def get_point_coords_from_point_annotation(instances):
"""
Load point coords and their corresponding labels from point annotation.
Args:
instances (list[Instances]): A list of N ... | banmo-main | third_party/detectron2_old/projects/PointSup/point_sup/point_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import os
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.data.datasets.builtin import _get_builtin_metadata
from detectron2.data.datasets.coco import load_coco_json
logger = logging.getLogger(__name__)
... | banmo-main | third_party/detectron2_old/projects/PointSup/point_sup/register_point_annotations.py |
#!/usr/bin/env python
import sys
import torch
from fvcore.nn.precise_bn import update_bn_stats
from torch import nn
from detectron2.checkpoint import DetectionCheckpointer
from detectron2.config import LazyConfig, instantiate
from detectron2.evaluation import inference_on_dataset
from detectron2.utils.events import Ev... | banmo-main | third_party/detectron2_old/projects/Rethinking-BatchNorm/retinanet-eval-domain-specific.py |
import math
import torch
import torch.distributed as dist
from detectron2.modeling.roi_heads import FastRCNNConvFCHead, MaskRCNNConvUpsampleHead
from detectron2.utils import comm
from fvcore.nn.distributed import differentiable_all_gather
def concat_all_gather(input):
bs_int = input.shape[0]
size_list = comm... | banmo-main | third_party/detectron2_old/projects/Rethinking-BatchNorm/configs/mask_rcnn_BNhead_shuffle.py |
from detectron2.model_zoo import get_config
model = get_config("common/models/mask_rcnn_fpn.py").model
model.backbone.bottom_up.freeze_at = 2
model.roi_heads.box_head.conv_norm = model.roi_heads.mask_head.conv_norm = "BN"
# 4conv1fc head
model.roi_heads.box_head.conv_dims = [256, 256, 256, 256]
model.roi_heads.box_h... | banmo-main | third_party/detectron2_old/projects/Rethinking-BatchNorm/configs/mask_rcnn_BNhead.py |
from .mask_rcnn_BNhead import model, dataloader, lr_multiplier, optimizer, train
model.roi_heads.box_head.conv_norm = model.roi_heads.mask_head.conv_norm = "SyncBN"
| banmo-main | third_party/detectron2_old/projects/Rethinking-BatchNorm/configs/mask_rcnn_SyncBNhead.py |
from torch.nn import BatchNorm2d
from torch.nn import functional as F
class BatchNormBatchStat(BatchNorm2d):
"""
BN that uses batch stat in inference
"""
def forward(self, input):
if self.training:
return super().forward(input)
return F.batch_norm(input, None, None, self.w... | banmo-main | third_party/detectron2_old/projects/Rethinking-BatchNorm/configs/mask_rcnn_BNhead_batch_stats.py |
from typing import List
import torch
from torch import Tensor, nn
from detectron2.modeling.meta_arch.retinanet import RetinaNetHead
def apply_sequential(inputs, modules):
for mod in modules:
if isinstance(mod, (nn.BatchNorm2d, nn.SyncBatchNorm)):
# for BN layer, normalize all inputs together
... | banmo-main | third_party/detectron2_old/projects/Rethinking-BatchNorm/configs/retinanet_SyncBNhead_SharedTraining.py |
from detectron2.model_zoo import get_config
model = get_config("common/models/retinanet.py").model
model.backbone.bottom_up.freeze_at = 2
model.head.norm = "SyncBN"
dataloader = get_config("common/data/coco.py").dataloader
lr_multiplier = get_config("common/coco_schedule.py").lr_multiplier_3x
optimizer = get_config("... | banmo-main | third_party/detectron2_old/projects/Rethinking-BatchNorm/configs/retinanet_SyncBNhead.py |
#!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates.
import glob
import os
from setuptools import find_packages, setup
import torch
from torch.utils.cpp_extension import CUDA_HOME, CppExtension, CUDAExtension
def get_extensions():
this_dir = os.path.dirname(os.path.abspath(__file__))
exte... | banmo-main | third_party/detectron2_old/projects/TensorMask/setup.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
"""
TensorMask Training Script.
This script is a simplified version of the training script in detectron2/tools.
"""
import os
import detectron2.utils.comm as comm
from detectron2.checkpoint import DetectionCheckpointer
from detectron2.config ... | banmo-main | third_party/detectron2_old/projects/TensorMask/train_net.py |
# Copyright (c) Facebook, Inc. and its affiliates.
| banmo-main | third_party/detectron2_old/projects/TensorMask/tests/__init__.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
import unittest
import torch
from torch.autograd import gradcheck
from tensormask.layers.swap_align2nat import SwapAlign2Nat
class SwapAlign2NatTest(unittest.TestCase):
@unittest.skipIf(not torch.cuda.is_available(), "CUDA not available")... | banmo-main | third_party/detectron2_old/projects/TensorMask/tests/test_swap_align2nat.py |
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.config import CfgNode as CN
def add_tensormask_config(cfg):
"""
Add config for TensorMask.
"""
cfg.MODEL.TENSOR_MASK = CN()
# Anchor parameters
cfg.MODEL.TENSOR_MASK.IN_FEATURES = ["p2", "p3", "p4", "p... | banmo-main | third_party/detectron2_old/projects/TensorMask/tensormask/config.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import copy
import math
from typing import List
import torch
import torch.nn.functional as F
from fvcore.nn import sigmoid_focal_loss_star_jit, smooth_l1_loss
from torch import nn
from detectron2.layers import ShapeSpec, batched_nms, cat, paste_masks_in_image
from det... | banmo-main | third_party/detectron2_old/projects/TensorMask/tensormask/arch.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .config import add_tensormask_config
from .arch import TensorMask
| banmo-main | third_party/detectron2_old/projects/TensorMask/tensormask/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from tensormask import _C
class _SwapAlign2Nat(Function):
@staticmethod
def forward(ctx, X, lambda_val, pad_val):
ctx.lambda_val = lambda... | banmo-main | third_party/detectron2_old/projects/TensorMask/tensormask/layers/swap_align2nat.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .swap_align2nat import SwapAlign2Nat, swap_align2nat
__all__ = [k for k in globals().keys() if not k.startswith("_")]
| banmo-main | third_party/detectron2_old/projects/TensorMask/tensormask/layers/__init__.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
"""
DeepLab Training Script.
This script is a simplified version of the training script in detectron2/tools.
"""
import os
import torch
import detectron2.data.transforms as T
import detectron2.utils.comm as comm
from detectron2.checkpoint imp... | banmo-main | third_party/detectron2_old/projects/DeepLab/train_net.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import math
from typing import List
import torch
from detectron2.solver.lr_scheduler import _get_warmup_factor_at_iter
# NOTE: PyTorch's LR scheduler interface uses names that assume the LR changes
# only on epoch boundaries. We typically use iteration based schedule... | banmo-main | third_party/detectron2_old/projects/DeepLab/deeplab/lr_scheduler.py |
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
def add_deeplab_config(cfg):
"""
Add config for DeepLab.
"""
# We retry random cropping until no single category in semantic segmentation GT occupies more
# than `SINGLE_CATEGORY_MAX_AREA` part of the crop.
cfg.INPUT.CR... | banmo-main | third_party/detectron2_old/projects/DeepLab/deeplab/config.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .build_solver import build_lr_scheduler
from .config import add_deeplab_config
from .resnet import build_resnet_deeplab_backbone
from .semantic_seg import DeepLabV3Head, DeepLabV3PlusHead
| banmo-main | third_party/detectron2_old/projects/DeepLab/deeplab/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
import torch.nn as nn
class DeepLabCE(nn.Module):
"""
Hard pixel mining with cross entropy loss, for semantic segmentation.
This is used in TensorFlow DeepLab frameworks.
Paper: DeeperLab: Single-Shot Image Parser
Reference: https://g... | banmo-main | third_party/detectron2_old/projects/DeepLab/deeplab/loss.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import fvcore.nn.weight_init as weight_init
import torch.nn.functional as F
from detectron2.layers import CNNBlockBase, Conv2d, get_norm
from detectron2.modeling import BACKBONE_REGISTRY
from detectron2.modeling.backbone.resnet import (
BasicStem,
BottleneckBl... | banmo-main | third_party/detectron2_old/projects/DeepLab/deeplab/resnet.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
from detectron2.config import CfgNode
from detectron2.solver import build_lr_scheduler as build_d2_lr_scheduler
from .lr_scheduler import WarmupPolyLR
def build_lr_scheduler(
cfg: CfgNode, optimizer: torch.optim.Optimizer
) -> torch.optim.lr_schedu... | banmo-main | third_party/detectron2_old/projects/DeepLab/deeplab/build_solver.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from typing import Callable, Dict, List, 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 ASPP, Conv2d, De... | banmo-main | third_party/detectron2_old/projects/DeepLab/deeplab/semantic_seg.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
"""
PointRend Training Script.
This script is a simplified version of the training script in detectron2/tools.
"""
import os
import torch
import detectron2.data.transforms as T
import detectron2.utils.comm as comm
from detectron2.checkpoint i... | banmo-main | third_party/detectron2_old/projects/PointRend/train_net.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
from torch.nn import functional as F
from detectron2.layers import cat
from detectron2.structures import BitMasks, Boxes
"""
Shape shorthand in this module:
N: minibatch dimension size, i.e. the number of RoIs for instance segmenation or the
... | banmo-main | third_party/detectron2_old/projects/PointRend/point_rend/point_features.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
import math
import numpy as np
from typing import Dict, List, Tuple
import fvcore.nn.weight_init as weight_init
import torch
from torch import Tensor, nn
from torch.nn import functional as F
from detectron2.config import configurable
from detectron2.lay... | banmo-main | third_party/detectron2_old/projects/PointRend/point_rend/mask_head.py |
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.config import CfgNode as CN
def add_pointrend_config(cfg):
"""
Add config for PointRend.
"""
# We retry random cropping until no single category in semantic segmentation GT occupies more
# than `SINGLE_CATE... | banmo-main | third_party/detectron2_old/projects/PointRend/point_rend/config.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .config import add_pointrend_config
from .mask_head import PointRendMaskHead, ImplicitPointRendMaskHead
from .semantic_seg import PointRendSemSegHead
from .color_augmentation import ColorAugSSDTransform
from . import roi_heads as _ # only registration
| banmo-main | third_party/detectron2_old/projects/PointRend/point_rend/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import fvcore.nn.weight_init as weight_init
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.layers import ShapeSpec, cat
from detectron2.utils.events import get_event_storage
from detectron2.utils.registry impo... | banmo-main | third_party/detectron2_old/projects/PointRend/point_rend/point_head.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
from detectron2.modeling import ROI_HEADS_REGISTRY, StandardROIHeads
@ROI_HEADS_REGISTRY.register()
class PointRendROIHeads(StandardROIHeads):
"""
Identical to StandardROIHeads, except for some weights conversion code to
handle old models.... | banmo-main | third_party/detectron2_old/projects/PointRend/point_rend/roi_heads.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import random
import cv2
from fvcore.transforms.transform import Transform
class ColorAugSSDTransform(Transform):
"""
A color related data augmentation used in Single Shot Multibox Detector (SSD).
Wei Liu, Dragomir Anguelov, Dumitru Er... | banmo-main | third_party/detectron2_old/projects/PointRend/point_rend/color_augmentation.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
from typing import Dict
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.layers import ShapeSpec, cat
from detectron2.modeling import SEM_SEG_HEADS_REGISTRY
from .point_features import (
get_uncertain_point... | banmo-main | third_party/detectron2_old/projects/PointRend/point_rend/semantic_seg.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import copy
import json
import os
from collections import defaultdict
# This mapping is extracted from the official LVIS mapping:
# https://github.com/lvis-dataset/lvis-api/blob/master/data/coco_to_synset.json
COCO_SYNSE... | banmo-main | third_party/detectron2_old/datasets/prepare_cocofied_lvis.py |
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