repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
detectron2 | projects/DensePose/densepose/data/samplers/mask_from_densepose.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
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 Bi... | 31 | 968 |
detectron2 | projects/DensePose/densepose/data/samplers/densepose_cse_confidence_based.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
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... | 122 | 5,169 |
detectron2 | projects/DensePose/densepose/converters/segm_to_mask.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from typing import Any
import torch
from torch.nn import functional as F
from detectron2.structures import BitMasks, Boxes, BoxMode
from .base import IntTupleBox, make_int_box
from .to_mask import ImageSizeType
def resample_coarse_segm_tensor_to_bbo... | 155 | 6,148 |
detectron2 | projects/DensePose/densepose/converters/to_chart_result.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from typing import Any
from detectron2.structures import Boxes
from ..structures import DensePoseChartResult, DensePoseChartResultWithConfidences
from .base import BaseConverter
class ToChartResultConverter(BaseConverter):
"""
Converts vario... | 73 | 2,737 |
detectron2 | projects/DensePose/densepose/converters/to_mask.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from typing import Any, Tuple
from detectron2.structures import BitMasks, Boxes
from .base import BaseConverter
ImageSizeType = Tuple[int, int]
class ToMaskConverter(BaseConverter):
"""
Converts various DensePose predictor outputs to masks
... | 52 | 1,582 |
detectron2 | projects/DensePose/densepose/converters/__init__.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from .hflip import HFlipConverter
from .to_mask import ToMaskConverter
from .to_chart_result import ToChartResultConverter, ToChartResultConverterWithConfidences
from .segm_to_mask import (
predictor_output_with_fine_and_coarse_segm_to_mask,
pre... | 18 | 635 |
detectron2 | projects/DensePose/densepose/converters/hflip.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from typing import Any
from .base import BaseConverter
class HFlipConverter(BaseConverter):
"""
Converts various DensePose predictor outputs to DensePose results.
Each DensePose predictor output type has to register its convertion strateg... | 37 | 1,145 |
detectron2 | projects/DensePose/densepose/converters/builtin.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from ..structures import DensePoseChartPredictorOutput, DensePoseEmbeddingPredictorOutput
from . import (
HFlipConverter,
ToChartResultConverter,
ToChartResultConverterWithConfidences,
ToMaskConverter,
densepose_chart_predictor_outpu... | 34 | 1,127 |
detectron2 | projects/DensePose/densepose/converters/chart_output_hflip.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from dataclasses import fields
import torch
from densepose.structures import DensePoseChartPredictorOutput, DensePoseTransformData
def densepose_chart_predictor_output_hflip(
densepose_predictor_output: DensePoseChartPredictorOutput,
transform... | 74 | 2,848 |
detectron2 | projects/DensePose/densepose/converters/base.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from typing import Any, Tuple, Type
import torch
class BaseConverter:
"""
Converter base class to be reused by various converters.
Converter allows one to convert data from various source types to a particular
destination type. Each so... | 97 | 3,545 |
detectron2 | projects/DensePose/densepose/converters/chart_output_to_chart_result.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from typing import Dict
import torch
from torch.nn import functional as F
from detectron2.structures.boxes import Boxes, BoxMode
from ..structures import (
DensePoseChartPredictorOutput,
DensePoseChartResult,
DensePoseChartResultWithConfid... | 194 | 7,353 |
detectron2 | projects/DensePose/tests/test_video_keyframe_dataset.py | .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 ... | 99 | 3,903 |
detectron2 | projects/DensePose/tests/test_cse_annotations_accumulator.py | .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... | 241 | 8,664 |
detectron2 | projects/DensePose/tests/test_image_list_dataset.py | .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... | 49 | 1,820 |
detectron2 | projects/DensePose/tests/test_tensor_storage.py | .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... | 257 | 10,863 |
detectron2 | projects/DensePose/tests/test_image_resize_transform.py | .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... | 17 | 637 |
detectron2 | projects/DensePose/tests/test_model_e2e.py | .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 ... | 44 | 1,137 |
detectron2 | projects/DensePose/tests/test_setup.py | .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... | 37 | 1,033 |
detectron2 | projects/DensePose/tests/test_chart_based_annotations_accumulator.py | .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... | 77 | 3,535 |
detectron2 | projects/DensePose/tests/test_frame_selector.py | .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... | 61 | 1,951 |
detectron2 | projects/DensePose/tests/test_structures.py | .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, ... | 26 | 882 |
detectron2 | projects/DensePose/tests/common.py | .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... | 125 | 3,472 |
detectron2 | projects/DensePose/tests/test_combine_data_loader.py | .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 ... | 47 | 1,500 |
detectron2 | projects/DensePose/tests/test_dataset_loaded_annotations.py | .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... | 88 | 3,450 |
detectron2 | projects/Panoptic-DeepLab/train_net.py | .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
from detectron2.checkpoint import DetectionCheckpointer
fro... | 178 | 6,202 |
detectron2 | projects/Panoptic-DeepLab/panoptic_deeplab/target_generator.py | .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:
"""
Generates trainin... | 156 | 7,641 |
detectron2 | projects/Panoptic-DeepLab/panoptic_deeplab/__init__.py | .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... | 11 | 332 |
detectron2 | projects/Panoptic-DeepLab/panoptic_deeplab/post_processing.py | .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... | 235 | 9,600 |
detectron2 | projects/Panoptic-DeepLab/panoptic_deeplab/panoptic_seg.py | .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
... | 573 | 23,513 |
detectron2 | projects/Panoptic-DeepLab/panoptic_deeplab/config.py | .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... | 60 | 2,772 |
detectron2 | projects/Panoptic-DeepLab/panoptic_deeplab/dataset_mapper.py | .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 ... | 117 | 4,456 |
detectron2 | projects/TensorMask/setup.py | .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... | 70 | 2,040 |
detectron2 | projects/TensorMask/train_net.py | .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 ... | 75 | 1,947 |
detectron2 | projects/TensorMask/tests/test_swap_align2nat.py | .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")... | 33 | 1,048 |
detectron2 | projects/TensorMask/tensormask/arch.py | .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... | 914 | 42,115 |
detectron2 | projects/TensorMask/tensormask/config.py | .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... | 51 | 1,672 |
detectron2 | projects/TensorMask/tensormask/layers/__init__.py | .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("_")]
| 5 | 175 |
detectron2 | projects/TensorMask/tensormask/layers/swap_align2nat.py | .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... | 62 | 2,083 |
detectron2 | projects/MViTv2/configs/cascade_mask_rcnn_mvitv2_h_in21k_lsj_3x.py | .py | from .cascade_mask_rcnn_mvitv2_b_3x import model, optimizer, train, lr_multiplier
from .common.coco_loader_lsj import dataloader
model.backbone.bottom_up.embed_dim = 192
model.backbone.bottom_up.depth = 80
model.backbone.bottom_up.num_heads = 3
model.backbone.bottom_up.last_block_indexes = (3, 11, 71, 79)
model.backb... | 13 | 492 |
detectron2 | projects/MViTv2/configs/mask_rcnn_mvitv2_t_3x.py | .py | from functools import partial
import torch.nn as nn
from fvcore.common.param_scheduler import MultiStepParamScheduler
from detectron2 import model_zoo
from detectron2.config import LazyCall as L
from detectron2.solver import WarmupParamScheduler
from detectron2.modeling import MViT
from .common.coco_loader import dat... | 56 | 1,713 |
detectron2 | projects/MViTv2/configs/cascade_mask_rcnn_mvitv2_l_in21k_lsj_50ep.py | .py | from fvcore.common.param_scheduler import MultiStepParamScheduler
from detectron2.config import LazyCall as L
from detectron2.solver import WarmupParamScheduler
from .cascade_mask_rcnn_mvitv2_b_3x import model, optimizer, train
from .common.coco_loader_lsj import dataloader
model.backbone.bottom_up.embed_dim = 144
... | 32 | 987 |
detectron2 | projects/MViTv2/configs/cascade_mask_rcnn_mvitv2_s_3x.py | .py | from .cascade_mask_rcnn_mvitv2_t_3x import model, dataloader, optimizer, lr_multiplier, train
model.backbone.bottom_up.depth = 16
model.backbone.bottom_up.last_block_indexes = (0, 2, 13, 15)
train.init_checkpoint = "detectron2://ImageNetPretrained/mvitv2/MViTv2_S_in1k.pyth"
| 8 | 278 |
detectron2 | projects/MViTv2/configs/cascade_mask_rcnn_mvitv2_t_3x.py | .py | from detectron2.config import LazyCall as L
from detectron2.layers import ShapeSpec
from detectron2.modeling.box_regression import Box2BoxTransform
from detectron2.modeling.matcher import Matcher
from detectron2.modeling.roi_heads import FastRCNNOutputLayers, FastRCNNConvFCHead, CascadeROIHeads
from detectron2.layers.b... | 49 | 1,976 |
detectron2 | projects/MViTv2/configs/cascade_mask_rcnn_mvitv2_b_3x.py | .py | from .cascade_mask_rcnn_mvitv2_t_3x import model, dataloader, optimizer, lr_multiplier, train
model.backbone.bottom_up.depth = 24
model.backbone.bottom_up.last_block_indexes = (1, 4, 20, 23)
model.backbone.bottom_up.drop_path_rate = 0.4
train.init_checkpoint = "detectron2://ImageNetPretrained/mvitv2/MViTv2_B_in1k.py... | 9 | 324 |
detectron2 | projects/MViTv2/configs/cascade_mask_rcnn_mvitv2_b_in21k_3x.py | .py | from .cascade_mask_rcnn_mvitv2_b_3x import model, dataloader, optimizer, lr_multiplier, train
train.init_checkpoint = "detectron2://ImageNetPretrained/mvitv2/MViTv2_B_in21k.pyth"
| 4 | 180 |
detectron2 | projects/MViTv2/configs/common/coco_loader_lsj.py | .py | import detectron2.data.transforms as T
from detectron2 import model_zoo
from detectron2.config import LazyCall as L
from .coco_loader import dataloader
# Data using LSJ
image_size = 1024
dataloader.train.mapper.augmentations = [
L(T.RandomFlip)(horizontal=True), # flip first
L(T.ResizeScale)(
min_sca... | 20 | 627 |
detectron2 | projects/MViTv2/configs/common/coco_loader.py | .py | from omegaconf import OmegaConf
import detectron2.data.transforms as T
from detectron2.config import LazyCall as L
from detectron2.data import (
DatasetMapper,
build_detection_test_loader,
build_detection_train_loader,
get_detection_dataset_dicts,
)
from detectron2.evaluation import COCOEvaluator
data... | 60 | 1,843 |
detectron2 | configs/Misc/mmdet_mask_rcnn_R_50_FPN_1x.py | .py | # An example config to train a mmdetection model using detectron2.
from ..common.data.coco import dataloader
from ..common.coco_schedule import lr_multiplier_1x as lr_multiplier
from ..common.optim import SGD as optimizer
from ..common.train import train
from ..common.data.constants import constants
from detectron2.m... | 153 | 5,358 |
detectron2 | configs/Misc/torchvision_imagenet_R_50.py | .py | """
An example config file to train a ImageNet classifier with detectron2.
Model and dataloader both come from torchvision.
This shows how to use detectron2 as a general engine for any new models and tasks.
To run, use the following command:
python tools/lazyconfig_train_net.py --config-file configs/Misc/torchvision_... | 150 | 4,496 |
detectron2 | configs/COCO-InstanceSegmentation/mask_rcnn_regnetx_4gf_dds_fpn_1x.py | .py | from ..common.optim import SGD as optimizer
from ..common.coco_schedule import lr_multiplier_1x as lr_multiplier
from ..common.data.coco import dataloader
from ..common.models.mask_rcnn_fpn import model
from ..common.train import train
from detectron2.config import LazyCall as L
from detectron2.modeling.backbone impor... | 35 | 1,206 |
detectron2 | configs/COCO-InstanceSegmentation/mask_rcnn_regnety_4gf_dds_fpn_1x.py | .py | from ..common.optim import SGD as optimizer
from ..common.coco_schedule import lr_multiplier_1x as lr_multiplier
from ..common.data.coco import dataloader
from ..common.models.mask_rcnn_fpn import model
from ..common.train import train
from detectron2.config import LazyCall as L
from detectron2.modeling.backbone impor... | 36 | 1,226 |
detectron2 | configs/COCO-Detection/fcos_R_50_FPN_1x.py | .py | from ..common.optim import SGD as optimizer
from ..common.coco_schedule import lr_multiplier_1x as lr_multiplier
from ..common.data.coco import dataloader
from ..common.models.fcos import model
from ..common.train import train
dataloader.train.mapper.use_instance_mask = False
optimizer.lr = 0.01
model.backbone.bottom... | 12 | 410 |
detectron2 | configs/COCO-Detection/retinanet_R_50_FPN_1x.py | .py | from ..common.optim import SGD as optimizer
from ..common.coco_schedule import lr_multiplier_1x as lr_multiplier
from ..common.data.coco import dataloader
from ..common.models.retinanet import model
from ..common.train import train
dataloader.train.mapper.use_instance_mask = False
model.backbone.bottom_up.freeze_at = ... | 12 | 415 |
detectron2 | configs/common/train.py | .py | # Common training-related configs that are designed for "tools/lazyconfig_train_net.py"
# You can use your own instead, together with your own train_net.py
train = dict(
output_dir="./output",
init_checkpoint="",
max_iter=90000,
amp=dict(enabled=False), # options for Automatic Mixed Precision
ddp=d... | 19 | 635 |
detectron2 | configs/common/optim.py | .py | import torch
from detectron2.config import LazyCall as L
from detectron2.solver.build import get_default_optimizer_params
SGD = L(torch.optim.SGD)(
params=L(get_default_optimizer_params)(
# params.model is meant to be set to the model object, before instantiating
# the optimizer.
weight_de... | 29 | 707 |
detectron2 | configs/common/coco_schedule.py | .py | from fvcore.common.param_scheduler import MultiStepParamScheduler
from detectron2.config import LazyCall as L
from detectron2.solver import WarmupParamScheduler
def default_X_scheduler(num_X):
"""
Returns the config for a default multi-step LR scheduler such as "1x", "3x",
commonly referred to in papers,... | 48 | 1,657 |
detectron2 | configs/common/data/coco_keypoint.py | .py | from detectron2.data.detection_utils import create_keypoint_hflip_indices
from .coco import dataloader
dataloader.train.dataset.min_keypoints = 1
dataloader.train.dataset.names = "keypoints_coco_2017_train"
dataloader.test.dataset.names = "keypoints_coco_2017_val"
dataloader.train.mapper.update(
use_instance_mas... | 14 | 444 |
detectron2 | configs/common/data/constants.py | .py | constants = dict(
imagenet_rgb256_mean=[123.675, 116.28, 103.53],
imagenet_rgb256_std=[58.395, 57.12, 57.375],
imagenet_bgr256_mean=[103.530, 116.280, 123.675],
# When using pre-trained models in Detectron1 or any MSRA models,
# std has been absorbed into its conv1 weights, so the std needs to be se... | 10 | 437 |
detectron2 | configs/common/data/coco_panoptic_separated.py | .py | from detectron2.config import LazyCall as L
from detectron2.evaluation import (
COCOEvaluator,
COCOPanopticEvaluator,
DatasetEvaluators,
SemSegEvaluator,
)
from .coco import dataloader
dataloader.train.dataset.names = "coco_2017_train_panoptic_separated"
dataloader.train.dataset.filter_empty = False
d... | 27 | 659 |
detectron2 | configs/common/data/coco.py | .py | from omegaconf import OmegaConf
import detectron2.data.transforms as T
from detectron2.config import LazyCall as L
from detectron2.data import (
DatasetMapper,
build_detection_test_loader,
build_detection_train_loader,
get_detection_dataset_dicts,
)
from detectron2.evaluation import COCOEvaluator
data... | 49 | 1,377 |
detectron2 | configs/common/models/retinanet.py | .py | # -*- coding: utf-8 -*-
from detectron2.config import LazyCall as L
from detectron2.layers import ShapeSpec
from detectron2.modeling.meta_arch import RetinaNet
from detectron2.modeling.anchor_generator import DefaultAnchorGenerator
from detectron2.modeling.backbone.fpn import LastLevelP6P7
from detectron2.modeling.bac... | 56 | 2,054 |
detectron2 | configs/common/models/mask_rcnn_vitdet.py | .py | from functools import partial
import torch.nn as nn
from detectron2.config import LazyCall as L
from detectron2.modeling import ViT, SimpleFeaturePyramid
from detectron2.modeling.backbone.fpn import LastLevelMaxPool
from .mask_rcnn_fpn import model
from ..data.constants import constants
model.pixel_mean = constants.i... | 60 | 1,639 |
detectron2 | configs/common/models/keypoint_rcnn_fpn.py | .py | from detectron2.config import LazyCall as L
from detectron2.layers import ShapeSpec
from detectron2.modeling.poolers import ROIPooler
from detectron2.modeling.roi_heads import KRCNNConvDeconvUpsampleHead
from .mask_rcnn_fpn import model
[model.roi_heads.pop(x) for x in ["mask_in_features", "mask_pooler", "mask_head"]... | 34 | 1,178 |
detectron2 | configs/common/models/panoptic_fpn.py | .py | from detectron2.config import LazyCall as L
from detectron2.layers import ShapeSpec
from detectron2.modeling import PanopticFPN
from detectron2.modeling.meta_arch.semantic_seg import SemSegFPNHead
from .mask_rcnn_fpn import model
model._target_ = PanopticFPN
model.sem_seg_head = L(SemSegFPNHead)(
input_shape={
... | 21 | 604 |
detectron2 | configs/common/models/cascade_rcnn.py | .py | from detectron2.config import LazyCall as L
from detectron2.layers import ShapeSpec
from detectron2.modeling.box_regression import Box2BoxTransform
from detectron2.modeling.matcher import Matcher
from detectron2.modeling.roi_heads import FastRCNNOutputLayers, FastRCNNConvFCHead, CascadeROIHeads
from .mask_rcnn_fpn imp... | 37 | 1,259 |
detectron2 | configs/common/models/mask_rcnn_c4.py | .py | from detectron2.config import LazyCall as L
from detectron2.layers import ShapeSpec
from detectron2.modeling.meta_arch import GeneralizedRCNN
from detectron2.modeling.anchor_generator import DefaultAnchorGenerator
from detectron2.modeling.backbone import BasicStem, BottleneckBlock, ResNet
from detectron2.modeling.box_r... | 91 | 3,220 |
detectron2 | configs/common/models/fcos.py | .py | from detectron2.modeling.meta_arch.fcos import FCOS, FCOSHead
from .retinanet import model
model._target_ = FCOS
del model.anchor_generator
del model.box2box_transform
del model.anchor_matcher
del model.input_format
# Use P5 instead of C5 to compute P6/P7
# (Sec 2.2 of https://arxiv.org/abs/2006.09214)
model.backbo... | 24 | 606 |
detectron2 | configs/common/models/mask_rcnn_fpn.py | .py | from detectron2.config import LazyCall as L
from detectron2.layers import ShapeSpec
from detectron2.modeling.meta_arch import GeneralizedRCNN
from detectron2.modeling.anchor_generator import DefaultAnchorGenerator
from detectron2.modeling.backbone.fpn import LastLevelMaxPool
from detectron2.modeling.backbone import Bas... | 96 | 3,558 |
detectron2 | configs/new_baselines/mask_rcnn_R_50_FPN_100ep_LSJ.py | .py | import detectron2.data.transforms as T
from detectron2.config.lazy import LazyCall as L
from detectron2.layers.batch_norm import NaiveSyncBatchNorm
from detectron2.solver import WarmupParamScheduler
from fvcore.common.param_scheduler import MultiStepParamScheduler
from ..common.data.coco import dataloader
from ..commo... | 73 | 2,515 |
detectron2 | configs/new_baselines/mask_rcnn_R_50_FPN_50ep_LSJ.py | .py | from .mask_rcnn_R_50_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter //= 2 # 100ep -> 50ep
lr_multiplier.scheduler.milestones = [
milestone // 2 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = train.max_it... | 15 | 323 |
detectron2 | configs/new_baselines/mask_rcnn_R_50_FPN_200ep_LSJ.py | .py | from .mask_rcnn_R_50_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 2 # 100ep -> 200ep
lr_multiplier.scheduler.milestones = [
milestone * 2 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = train.max_ite... | 15 | 322 |
detectron2 | configs/new_baselines/mask_rcnn_regnetx_4gf_dds_FPN_100ep_LSJ.py | .py | from .mask_rcnn_R_50_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
from detectron2.config import LazyCall as L
from detectron2.modeling.backbone import RegNet
from detectron2.modeling.backbone.regnet import SimpleStem, ResBottleneckBlock
# Config source:
# https://git... | 30 | 829 |
detectron2 | configs/new_baselines/mask_rcnn_R_50_FPN_400ep_LSJ.py | .py | from .mask_rcnn_R_50_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 4 # 100ep -> 400ep
lr_multiplier.scheduler.milestones = [
milestone * 4 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = train.max_ite... | 15 | 322 |
detectron2 | configs/new_baselines/mask_rcnn_regnety_4gf_dds_FPN_200ep_LSJ.py | .py | from .mask_rcnn_regnety_4gf_dds_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 2 # 100ep -> 200ep
lr_multiplier.scheduler.milestones = [
milestone * 2 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = tr... | 15 | 333 |
detectron2 | configs/new_baselines/mask_rcnn_regnetx_4gf_dds_FPN_200ep_LSJ.py | .py | from .mask_rcnn_regnetx_4gf_dds_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 2 # 100ep -> 200ep
lr_multiplier.scheduler.milestones = [
milestone * 2 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = tr... | 15 | 333 |
detectron2 | configs/new_baselines/mask_rcnn_regnetx_4gf_dds_FPN_400ep_LSJ.py | .py | from .mask_rcnn_regnetx_4gf_dds_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 4 # 100ep -> 400ep
lr_multiplier.scheduler.milestones = [
milestone * 4 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = tr... | 15 | 333 |
detectron2 | configs/new_baselines/mask_rcnn_regnety_4gf_dds_FPN_100ep_LSJ.py | .py | from .mask_rcnn_R_50_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
from detectron2.config import LazyCall as L
from detectron2.modeling.backbone import RegNet
from detectron2.modeling.backbone.regnet import SimpleStem, ResBottleneckBlock
# Config source:
# https://git... | 31 | 848 |
detectron2 | configs/new_baselines/mask_rcnn_R_101_FPN_100ep_LSJ.py | .py | from .mask_rcnn_R_50_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
model.backbone.bottom_up.stages.depth = 101
| 10 | 163 |
detectron2 | configs/new_baselines/mask_rcnn_R_101_FPN_400ep_LSJ.py | .py | from .mask_rcnn_R_101_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 4 # 100ep -> 400ep
lr_multiplier.scheduler.milestones = [
milestone * 4 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = train.max_it... | 15 | 323 |
detectron2 | configs/new_baselines/mask_rcnn_regnety_4gf_dds_FPN_400ep_LSJ.py | .py | from .mask_rcnn_regnety_4gf_dds_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 4 # 100ep -> 400ep
lr_multiplier.scheduler.milestones = [
milestone * 4 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = tr... | 15 | 333 |
detectron2 | configs/new_baselines/mask_rcnn_R_101_FPN_200ep_LSJ.py | .py | from .mask_rcnn_R_101_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 2 # 100ep -> 200ep
lr_multiplier.scheduler.milestones = [
milestone * 2 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = train.max_it... | 15 | 323 |
detectron2 | detectron2/__init__.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
from .utils.env import setup_environment
setup_environment()
# This line will be programatically read/write by setup.py.
# Leave them at the bottom of this file and don't touch them.
__version__ = "0.6"
| 11 | 258 |
detectron2 | detectron2/layers/losses.py | .py | 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... | 134 | 4,202 |
detectron2 | detectron2/layers/deform_conv.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
import math
from functools import lru_cache
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
from torchvision.ops import deform_conv2d
from detectron2... | 515 | 16,978 |
detectron2 | detectron2/layers/aspp.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
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.Mod... | 145 | 5,764 |
detectron2 | detectron2/layers/roi_align_rotated.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
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
from detectron2.layers.wrappers import disable_torch_compiler
class _ROIAlignRotated(Function):
... | 104 | 3,843 |
detectron2 | detectron2/layers/nms.py | .py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
from torchvision.ops import boxes as box_ops
from torchvision.ops import nms # noqa . for compatibility
from detectron2.layers.wrappers import disable_torch_compiler
def batched_nms(
boxes: torch.Tensor, scores: torch.Tenso... | 148 | 6,698 |
detectron2 | detectron2/layers/__init__.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
from .batch_norm import FrozenBatchNorm2d, get_norm, NaiveSyncBatchNorm, CycleBatchNormList
from .deform_conv import DeformConv, ModulatedDeformConv
from .mask_ops import paste_masks_in_image
from .nms import batched_nms, batched_nms_rotated, nms, nms_rotated
from .roi... | 27 | 874 |
detectron2 | detectron2/layers/mask_ops.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
from typing import Tuple
import torch
from PIL import Image
from torch.nn import functional as F
__all__ = ["paste_masks_in_image"]
BYTES_PER_FLOAT = 4
# TODO: This memory limit may be too much or too little. It would be better to
# determine it b... | 276 | 10,869 |
detectron2 | detectron2/layers/wrappers.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
"""
Wrappers around on some nn functions, mainly to support empty tensors.
Ideally, add support directly in PyTorch to empty tensors in those functions.
These can be removed once https://github.com/pytorch/pytorch/issues/12013
is implemented
"""
import functools
imp... | 178 | 5,959 |
detectron2 | detectron2/layers/rotated_boxes.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
from __future__ import absolute_import, division, print_function, unicode_literals
import torch
def pairwise_iou_rotated(boxes1, boxes2):
"""
Return intersection-over-union (Jaccard index) of boxes.
Both sets of boxes are expected to be in
(x_center,... | 22 | 652 |
detectron2 | detectron2/layers/roi_align.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
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:
... | 75 | 3,098 |
detectron2 | detectron2/layers/batch_norm.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
import torch
import torch.distributed as dist
from fvcore.nn.distributed import differentiable_all_reduce
from torch import nn
from torch.nn import functional as F
from detectron2.utils import comm, env
from .wrappers import BatchNorm2d
class FrozenBatchNorm2d(nn.M... | 354 | 13,801 |
detectron2 | detectron2/layers/blocks.py | .py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
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 assume... | 112 | 3,024 |
detectron2 | detectron2/layers/shape_spec.py | .py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
from dataclasses import dataclass
from typing import Optional
@dataclass
class ShapeSpec:
"""
A simple structure that contains basic shape specification about a tensor.
It is often used as the auxiliary inputs/outputs of models,
... | 19 | 537 |
detectron2 | detectron2/export/caffe2_patch.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
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 imp... | 190 | 6,705 |
detectron2 | detectron2/export/flatten.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
import collections
from dataclasses import dataclass
from typing import Callable, List, Optional, Tuple
import torch
from torch import nn
from detectron2.structures import Boxes, Instances, ROIMasks
from detectron2.utils.registry import _convert_target_to_string, loca... | 331 | 11,807 |
detectron2 | detectron2/export/__init__.py | .py | # -*- coding: utf-8 -*-
import warnings
from .flatten import TracingAdapter
from .torchscript import dump_torchscript_IR, scripting_with_instances
try:
from caffe2.proto import caffe2_pb2 as _tmp
from caffe2.python import core
# caffe2 is optional
except ImportError:
pass
else:
from .api import ... | 31 | 673 |
detectron2 | detectron2/export/torchscript_patch.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
import os
import sys
import tempfile
from contextlib import ExitStack, contextmanager
from copy import deepcopy
from unittest import mock
import torch
from torch import nn
# need some explicit imports due to https://github.com/pytorch/pytorch/issues/38964
import dete... | 407 | 11,526 |
detectron2 | detectron2/export/shared.py | .py | # Copyright (c) Facebook, Inc. and its affiliates.
import collections
import copy
import functools
import logging
import numpy as np
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
from unittest import mock
import caffe2.python.utils as putils
import torch
import torch.nn.functional as F... | 1,041 | 38,321 |
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