python_code stringlengths 0 4.04M | repo_name stringlengths 7 58 | file_path stringlengths 5 147 |
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# Copyright (c) Facebook, Inc. and its affiliates.
import torch
from detectron2.modeling import PROPOSAL_GENERATOR_REGISTRY
from detectron2.modeling.proposal_generator.rpn import RPN
from detectron2.structures import ImageList
@PROPOSAL_GENERATOR_REGISTRY.register()
class TridentRPN(RPN):
"""
Trident RPN sub... | banmo-main | third_party/detectron2_old/projects/TridentNet/tridentnet/trident_rpn.py |
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.config import CfgNode as CN
def add_tridentnet_config(cfg):
"""
Add config for tridentnet.
"""
_C = cfg
_C.MODEL.TRIDENT = CN()
# Number of branches for TridentNet.
_C.MODEL.TRIDENT.NUM_BRANCH = 3... | banmo-main | third_party/detectron2_old/projects/TridentNet/tridentnet/config.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import fvcore.nn.weight_init as weight_init
import torch
import torch.nn.functional as F
from detectron2.layers import Conv2d, FrozenBatchNorm2d, get_norm
from detectron2.modeling import BACKBONE_REGISTRY, ResNet, ResNetBlockBase
from detectron2.modeling.backbone.resn... | banmo-main | third_party/detectron2_old/projects/TridentNet/tridentnet/trident_backbone.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .config import add_tridentnet_config
from .trident_backbone import (
TridentBottleneckBlock,
build_trident_resnet_backbone,
make_trident_stage,
)
from .trident_rpn import TridentRPN
from .trident_rcnn import TridentRes5ROIHeads, TridentStandardROIHeads... | banmo-main | third_party/detectron2_old/projects/TridentNet/tridentnet/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.layers import batched_nms
from detectron2.modeling import ROI_HEADS_REGISTRY, StandardROIHeads
from detectron2.modeling.roi_heads.roi_heads import Res5ROIHeads
from detectron2.structures import Instances
def merge_branch_instances(instances, num_branc... | banmo-main | third_party/detectron2_old/projects/TridentNet/tridentnet/trident_rcnn.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
from torch import nn
from torch.nn import functional as F
from torch.nn.modules.utils import _pair
from detectron2.layers.wrappers import _NewEmptyTensorOp
class TridentConv(nn.Module):
def __init__(
self,
in_channels,
out_ch... | banmo-main | third_party/detectron2_old/projects/TridentNet/tridentnet/trident_conv.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
import argparse
import logging
import os
import sys
from timeit import default_timer as timer
from typing import Any, ClassVar, Dict, List
import torch
from detectron2.data.catalog import DatasetCatalog
from detectron2.utils.file_io import Path... | banmo-main | third_party/detectron2_old/projects/DensePose/query_db.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
import argparse
import glob
import logging
import os
import pickle
import sys
from typing import Any, ClassVar, Dict, List
import torch
from detectron2.config import CfgNode, get_cfg
from detectron2.data.detection_utils import read_image
from d... | banmo-main | third_party/detectron2_old/projects/DensePose/apply_net.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
"""
DensePose Training Script.
This script is similar to the training script in detectron2/tools.
It is an example of how a user might use detectron2 for a new project.
"""
from datetime import timedelta
import detectron2.utils.comm as comm
... | banmo-main | third_party/detectron2_old/projects/DensePose/train_net.py |
# -*- coding = utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
# pyre-ignore-all-errors
from detectron2.config import CfgNode as CN
def add_dataset_category_config(cfg: CN):
"""
Add config for additional category-related dataset options
- category whitelisting
- category mapping
""... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/config.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .data.datasets import builtin # just to register data
from .converters import builtin as builtin_converters # register converters
from .config import (
add_densepose_config,
add_densepose_head_config,
add_hrnet_config,
add_dataset_category_config... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import torch
from torch.nn import functional as F
from densepose.data.meshes.catalog import MeshCatalog
from densepose.structures.mesh import load_mesh_symmetry
from densepose.structures.transform_data import DensePoseTransformData
class DensePose... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/structures/data_relative.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
from densepose.structures.data_relative import DensePoseDataRelative
class DensePoseList(object):
_TORCH_DEVICE_CPU = torch.device("cpu")
def __init__(self, densepose_datas, boxes_xyxy_abs, image_size_hw, device=_TORCH_DEVICE_CPU):
ass... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/structures/list.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from dataclasses import make_dataclass
from functools import lru_cache
from typing import Any, Optional
import torch
@lru_cache(maxsize=None)
def decorate_predictor_output_class_with_confidences(BasePredictorOutput: type) -> type:
"""
Create a new output cla... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/structures/chart_confidence.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from dataclasses import dataclass
from typing import Any, Optional, Tuple
import torch
@dataclass
class DensePoseChartResult:
"""
DensePose results for chart-based methods represented by labels and inner
coordinates (U, V) of individual charts. Each char... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/structures/chart_result.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from dataclasses import make_dataclass
from functools import lru_cache
from typing import Any, Optional
import torch
@lru_cache(maxsize=None)
def decorate_cse_predictor_output_class_with_confidences(BasePredictorOutput: type) -> type:
"""
Create a new output... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/structures/cse_confidence.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .chart import DensePoseChartPredictorOutput
from .chart_confidence import decorate_predictor_output_class_with_confidences
from .cse_confidence import decorate_cse_predictor_output_class_with_confidences
from .chart_result import (
DensePoseChartResult,
D... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/structures/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from dataclasses import dataclass
from typing import Union
import torch
@dataclass
class DensePoseChartPredictorOutput:
"""
Predictor output that contains segmentation and inner coordinates predictions for predefined
body parts:
* coarse segmentatio... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/structures/chart.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import pdb
import pickle
from functools import lru_cache
from typing import Dict, Optional, Tuple
import torch
from detectron2.utils.file_io import PathManager
from densepose.data.meshes.catalog import MeshCatalog, MeshInfo
def _maybe_copy_to_d... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/structures/mesh.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from typing import BinaryIO, Dict, Union
import torch
def normalized_coords_transform(x0, y0, w, h):
"""
Coordinates transform that maps top left corner to (-1, -1) and bottom
right corner to (1, 1). Used for torch.grid_sample to initialize the
grid
... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/structures/transform_data.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from dataclasses import dataclass
from typing import Union
import torch
@dataclass
class DensePoseEmbeddingPredictorOutput:
"""
Predictor output that contains embedding and coarse segmentation data:
* embedding: float tensor of size ... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/structures/cse.py |
# Copyright (c) Facebook, Inc. and its affiliates.
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
in bit mask... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/converters/to_mask.py |
# Copyright (c) Facebook, Inc. and its affiliates.
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,
DensePoseChartResultWithConfidences,
)
from .... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/converters/chart_output_to_chart_result.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from typing import Any
from detectron2.structures import Boxes
from ..structures import DensePoseChartResult, DensePoseChartResultWithConfidences
from .base import BaseConverter
class ToChartResultConverter(BaseConverter):
"""
Converts various DensePose pr... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/converters/to_chart_result.py |
# Copyright (c) Facebook, Inc. and its affiliates.
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,
predictor_output_w... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/converters/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from dataclasses import fields
import torch
from densepose.structures import DensePoseChartPredictorOutput, DensePoseTransformData
def densepose_chart_predictor_output_hflip(
densepose_predictor_output: DensePoseChartPredictorOutput,
transform_data: DensePos... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/converters/chart_output_hflip.py |
# Copyright (c) Facebook, Inc. and its affiliates.
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 strategy.
"""
... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/converters/hflip.py |
# Copyright (c) Facebook, Inc. and its affiliates.
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_bbox(coarse_segm: ... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/converters/segm_to_mask.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from ..structures import DensePoseChartPredictorOutput, DensePoseEmbeddingPredictorOutput
from . import (
HFlipConverter,
ToChartResultConverter,
ToChartResultConverterWithConfidences,
ToMaskConverter,
densepose_chart_predictor_output_hflip,
de... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/converters/builtin.py |
# Copyright (c) Facebook, Inc. and its affiliates.
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 source type needs... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/converters/base.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
def verbosity_to_level(verbosity):
if verbosity is not None:
if verbosity == 0:
return logging.WARNING
elif verbosity == 1:
return logging.INFO
elif verbosity >= 2:
return logging.DEBUG
... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/utils/logger.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from typing import Any, Dict, Optional, Tuple
class EntrySelector(object):
"""
Base class for entry selectors
"""
@staticmethod
def from_string(spec: str) -> "EntrySelector":
if spec == "*":
return AllEntrySelector()
r... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/utils/dbhelper.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.data import MetadataCatalog
from detectron2.utils.file_io import PathManager
from densepose import DensePoseTransformData
def load_for_dataset(dataset_name):
path = MetadataCatalog.get(dataset_name).densepose_transform_src
densepose_transform... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/utils/transform.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from typing import Optional
from torch import nn
from detectron2.config import CfgNode
from .cse.embedder import Embedder
from .filter import DensePoseDataFilter
def build_densepose_predictor(cfg: CfgNode, input_channels: int):
"""
Create an instance of De... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/build.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bin Xiao (leoxiaobin@gmail.com)
# Modified by Bowen Cheng (bcheng9@illinois.edu)
# Adapted from https://github.com/... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/hrnet.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import copy
import numpy as np
import torch
from fvcore.transforms import HFlipTransform, TransformList
from torch.nn import functional as F
from detectron2.data.transforms import RandomRotation, RotationTransform, apply_transform_gens
from detectron2.modeling.postpro... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/test_time_augmentation.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from dataclasses import dataclass
from enum import Enum
from detectron2.config import CfgNode
class DensePoseUVConfidenceType(Enum):
"""
Statistical model type for confidence learning, possible values:
- "iid_iso": statistically independent identically... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/confidence.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from collections import OrderedDict
from detectron2.checkpoint import DetectionCheckpointer
def _rename_HRNet_weights(weights):
# We detect and rename HRNet weights for DensePose. 1956 and 1716 are values that are
# common to all HRNet pretrained weights, a... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/densepose_checkpoint.py |
# Copyright (c) Facebook, Inc. and its affiliates.
"""
MIT License
Copyright (c) 2019 Microsoft
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/hrfpn.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .confidence import DensePoseConfidenceModelConfig, DensePoseUVConfidenceType
from .filter import DensePoseDataFilter
from .inference import densepose_inference
from .utils import initialize_module_params
from .build import (
build_densepose_data_filter,
b... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from torch import nn
def initialize_module_params(module: nn.Module):
for name, param in module.named_parameters():
if "bias" in name:
nn.init.constant_(param, 0)
elif "weight" in name:
nn.init.kaiming_normal_(param, mode=... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from dataclasses import fields
from typing import Any, List
import torch
from detectron2.structures import Instances
def densepose_inference(densepose_predictor_output: Any, detections: List[Instances]):
"""
Splits DensePose predictor outputs into chunks, ea... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/inference.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from typing import List
import torch
from detectron2.config import CfgNode
from detectron2.structures import Instances
from detectron2.structures.boxes import matched_boxlist_iou
class DensePoseDataFilter(object):
def __init__(self, cfg: CfgNode):
self.... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/filter.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from dataclasses import dataclass
from typing import Any, Iterable, List, Optional
import torch
from torch.nn import functional as F
from detectron2.structures import Instances
@dataclass
class DataForMaskLoss:
"""
Contains mask GT and e... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/losses/mask.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from dataclasses import dataclass
from typing import Any, Optional
import torch
from detectron2.structures import BoxMode, Instances
from .utils import AnnotationsAccumulator
@dataclass
class PackedCseAnnotations:
x_gt: torch.Tensor
y_g... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/losses/embed_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from typing import Any, Dict, List
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import CfgNode
from detectron2.structures import Instances
from densepose.data.meshes.catalog import MeshCatalog
from... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/losses/soft_embed.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from typing import Any, List
import torch
from torch.nn import functional as F
from detectron2.config import CfgNode
from detectron2.structures import Instances
from .utils import resample_data
class SegmentationLoss:
"""
Segmentation l... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/losses/segm.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from typing import Any, Dict, List
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import CfgNode
from detectron2.structures import Instances
from densepose.data.meshes.catalog import MeshCatalog
from... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/losses/embed.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from typing import Any, List
import torch
from detectron2.config import CfgNode
from detectron2.structures import Instances
from .mask import MaskLoss
from .segm import SegmentationLoss
class MaskOrSegmentationLoss:
"""
Mask or segmenta... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/losses/mask_or_segm.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.utils.registry import Registry
DENSEPOSE_LOSS_REGISTRY = Registry("DENSEPOSE_LOSS")
| banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/losses/registry.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import random
from typing import Tuple
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import CfgNode
from densepose.structures.mesh import create_mesh
from .utils import sample_random_indices
clas... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/losses/cycle_shape2shape.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from typing import Any, List
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import CfgNode
from detectron2.structures import Instances
from densepose.data.meshes.catalog import MeshCatalog
from dense... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/losses/cycle_pix2shape.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .chart import DensePoseChartLoss
from .chart_with_confidences import DensePoseChartWithConfidenceLoss
from .cse import DensePoseCseLoss
from .registry import DENSEPOSE_LOSS_REGISTRY
__all__ = [
"DensePoseChartLoss",
"DensePoseChartWithConfidenceLoss",
... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/losses/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from typing import Any, List
import torch
from torch.nn import functional as F
from detectron2.config import CfgNode
from detectron2.structures import Instances
from .mask_or_segm import MaskOrSegmentationLoss
from .registry import DENSEPOSE_LOSS_REGISTRY
from .util... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/losses/chart.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import math
from typing import Any, List
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import CfgNode
from detectron2.structures import Instances
from .. import DensePoseConfidenceModelConfig, DensePoseUVConfidenceType
... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/losses/chart_with_confidences.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Any, Dict, List, Optional, Tuple
import torch
from torch.nn import functional as F
from detectron2.structures import BoxMode, Instances
from densepose import DensePoseDataRelati... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/losses/utils.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from typing import Any, List
from torch import nn
from detectron2.config import CfgNode
from detectron2.structures import Instances
from .cycle_pix2shape import PixToShapeCycleLoss
from .cycle_shape2shape import ShapeToShapeCycleLoss
from .embed ... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/losses/cse.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from typing import Any
import torch
from torch.nn import functional as F
from detectron2.config import CfgNode
from detectron2.layers import ConvTranspose2d
from ...structures import decorate_predictor_output_class_with_confidences
from ..confidence import DensePose... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/predictors/chart_confidence.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.utils.registry import Registry
DENSEPOSE_PREDICTOR_REGISTRY = Registry("DENSEPOSE_PREDICTOR")
| banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/predictors/registry.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from typing import Any
import torch
from torch.nn import functional as F
from detectron2.config import CfgNode
from detectron2.layers import ConvTranspose2d
from densepose.modeling.confidence import DensePoseConfidenceModelConfig
from densepose.modeling.utils import... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/predictors/cse_confidence.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from . import DensePoseChartConfidencePredictorMixin, DensePoseChartPredictor
from .registry import DENSEPOSE_PREDICTOR_REGISTRY
@DENSEPOSE_PREDICTOR_REGISTRY.register()
class DensePoseChartWithConfidencePredictor(
DensePoseChartConfidencePredictorMixin, DensePo... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/predictors/chart_with_confidence.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .chart import DensePoseChartPredictor
from .chart_confidence import DensePoseChartConfidencePredictorMixin
from .chart_with_confidence import DensePoseChartWithConfidencePredictor
from .cse import DensePoseEmbeddingPredictor
from .cse_confidence import DensePoseE... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/predictors/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
from torch import nn
from detectron2.config import CfgNode
from detectron2.layers import ConvTranspose2d, interpolate
from ...structures import DensePoseChartPredictorOutput
from ..utils import initialize_module_params
from .registry import DENSEPOSE_PR... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/predictors/chart.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from . import DensePoseEmbeddingConfidencePredictorMixin, DensePoseEmbeddingPredictor
from .registry import DENSEPOSE_PREDICTOR_REGISTRY
@DENSEPOSE_PREDICTOR_REGISTRY.register()
class DensePoseEmbeddingWithConfidencePredictor(
DensePoseEmbeddingConfidencePredict... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/predictors/cse_with_confidence.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from torch import nn
from detectron2.config import CfgNode
from detectron2.layers import ConvTranspose2d, interpolate
from ...structures import DensePoseEmbeddingPredictorOutput
from ..utils import initialize_module_params
from .regi... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/predictors/cse.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from .vertex_direct_embedder import VertexDirectEmbedder
from .vertex_feature_embedder import VertexFeatureEmbedder
from .embedder import Embedder
| banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/cse/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from torch.nn import functional as F
def squared_euclidean_distance_matrix(pts1: torch.Tensor, pts2: torch.Tensor) -> torch.Tensor:
"""
Get squared Euclidean Distance Matrix
Computes pairwise squared Euclidean distances b... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/cse/utils.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import numpy as np
import pickle
from enum import Enum
from typing import Optional
import torch
from torch import nn
from detectron2.config import CfgNode
from detectron2.utils.file_io import PathManager
from .vertex_direct_embedde... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/cse/embedder.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import pickle
import torch
from torch import nn
from detectron2.utils.file_io import PathManager
from .utils import normalize_embeddings
class VertexDirectEmbedder(nn.Module):
"""
Class responsible for embedding vertices. Vertex embeddi... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/cse/vertex_direct_embedder.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import pickle
import torch
from torch import nn
from detectron2.utils.file_io import PathManager
from .utils import normalize_embeddings
class VertexFeatureEmbedder(nn.Module):
"""
Class responsible for embedding vertex features. Mappin... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/cse/vertex_feature_embedder.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
from typing import Dict, List, Optional
import fvcore.nn.weight_init as weight_init
import torch
import torch.nn as nn
from torch.nn import functional as F
from detectron2.layers import Conv2d, ShapeSpec, get_norm
from detectron2.modeling import RO... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/roi_heads/roi_head.py |
# Copyright (c) Facebook, Inc. and its affiliates.
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 CfgNode
from detectron2.layers import Conv2d
from .registry import ROI_DENSEPOSE_HEAD_REGISTRY
@ROI_DENSEPOSE_HEAD_REGI... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/roi_heads/deeplab.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.utils.registry import Registry
ROI_DENSEPOSE_HEAD_REGISTRY = Registry("ROI_DENSEPOSE_HEAD")
| banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/roi_heads/registry.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .v1convx import DensePoseV1ConvXHead
from .deeplab import DensePoseDeepLabHead
from .registry import ROI_DENSEPOSE_HEAD_REGISTRY
from .roi_head import Decoder, DensePoseROIHeads
| banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/roi_heads/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import CfgNode
from detectron2.layers import Conv2d
from ..utils import initialize_module_params
from .registry import ROI_DENSEPOSE_HEAD_REGISTRY
@ROI_DENSEPOSE_HEAD_REG... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/modeling/roi_heads/v1convx.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
import numpy as np
from typing import List, Optional, Tuple
import cv2
import torch
from densepose.structures import DensePoseDataRelative
from ..structures import DensePoseChartResult
from .base import Boxes, Image, MatrixVisualizer
class DensePoseR... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/vis/densepose_results.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
from typing import Iterable, Optional, Tuple
import cv2
from densepose.structures import DensePoseDataRelative
from .base import Boxes, Image, MatrixVisualizer, PointsVisualizer
class DensePoseDataCoarseSegmentationVisualizer(object):
"""
... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/vis/densepose_data_points.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
from typing import Optional, Tuple
import cv2
from densepose.structures import DensePoseDataRelative
from ..structures import DensePoseChartPredictorOutput
from .base import Boxes, Image, MatrixVisualizer
class DensePoseOutputsVisualizer(object):... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/vis/densepose_outputs_iuv.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
from typing import List, Optional, Sequence, Tuple
import torch
from detectron2.layers.nms import batched_nms
from detectron2.structures.instances import Instances
from densepose.converters import ToChartResultConverterWithConfidences
from densepose.st... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/vis/extractor.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .base import RectangleVisualizer, TextVisualizer
class BoundingBoxVisualizer(object):
def __init__(self):
self.rectangle_visualizer = RectangleVisualizer()
def visualize(self, image_bgr, boxes_xywh):
for bbox_xywh in boxes_xywh:
... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/vis/bounding_box.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import json
import numpy as np
from functools import lru_cache
from typing import Dict, List, Optional, Tuple
import cv2
import torch
from detectron2.utils.file_io import PathManager
from densepose.modeling import build_densepose_embedder
from den... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/vis/densepose_outputs_vertex.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
from typing import List, Optional, Tuple
import torch
from detectron2.data.detection_utils import read_image
from ..structures import DensePoseChartResult
from .base import Boxes, Image
from .densepose_results import DensePoseResultsVisualizer
de... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/vis/densepose_results_textures.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
import numpy as np
import cv2
import torch
Image = np.ndarray
Boxes = torch.Tensor
class MatrixVisualizer(object):
"""
Base visualizer for matrix data
"""
def __init__(
self,
inplace=True,
cmap=cv2.COLORMAP_PAR... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/vis/base.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import json
import logging
from typing import List, Optional
import torch
from torch import nn
from detectron2.utils.file_io import PathManager
from densepose.structures.mesh import create_mesh
class MeshAlignmentEvaluator:
"""
Class fo... | banmo-main | third_party/detectron2_old/projects/DensePose/densepose/evaluation/mesh_alignment_evaluator.py |
# 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 |
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