repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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Bone_MRI | Bone_MRI-main/scripts_notebooks/segmentation_disease_region/dice_generalization.py | import torch
class Dice():
'''
Puprose: compute an approximation of the Dice coefficient (area overlap), averaged over
- two classes (foreground, background);
- number of prediction - (binary) reference standard slice pairs in the batch;
! Note: the code was written, taking into ac... | 4,923 | 42.192982 | 99 | py |
pose-baselines | pose-baselines-main/utils_common.py |
import open3d as o3d
import torch
import numpy as np
from torch.utils.data import Dataset
from tqdm import tqdm
import pandas as pd
import seaborn as sns
#
import pickle5 as pickle
# import pickle
import matplotlib.pyplot as plt
from pytorch3d import ops
def translation_error(t, t_):
"""
inputs:
t: torc... | 8,049 | 24.394322 | 123 | py |
pose-baselines | pose-baselines-main/ransac.py | import numpy as np
import open3d as o3d
import torch
from utils_common import pos_tensor_to_o3d
# ransac from open3d
def ransac(source_points, target_points):
"""
inputs:
source_points : torch.tensor of shape (3, m)
target_points : torch.tensor of shape (3, m)
outputs:
R : torch.tensor... | 2,465 | 25.516129 | 91 | py |
pose-baselines | pose-baselines-main/teaser.py | import torch
import teaserpp_python
def teaser(source_points, target_points):
"""
inputs:
source_points : torch.tensor of shape (3, m)
target_points : torch.tensor of shape (3, n)
outputs:
R : torch.tensor of shape (3, 3)
t : torch.tensor of shape (3, 1)
Note:
Input a... | 2,599 | 26.956989 | 94 | py |
pose-baselines | pose-baselines-main/icp.py |
import torch
import open3d as o3d
import numpy as np
from utils_common import pos_tensor_to_o3d
from teaser import TEASER
from ransac import RANSAC
def icp(source_points, target_points, R0, t0):
"""
inputs:
source_points : torch.tensor of shape (3, m)
target_points : torch.tensor of shape (3, n)... | 7,947 | 30.792 | 124 | py |
pose-baselines | pose-baselines-main/shapenet.py | import numpy as np
import os
# choose one, depending on the environment
# import pickle
import pickle5 as pickle
import json
import torch
import open3d as o3d
from tqdm import tqdm
import math
import copy
from scipy.spatial.transform import Rotation as Rot
# from pytorch3d import transforms, ops
import random
# BASE_... | 25,076 | 33.684647 | 129 | py |
pose-baselines | pose-baselines-main/utils_dataset.py |
import torch
import numpy as np
# credit: pointnetlk_revisited. This induces rotation errors, which we use to create "easy" dataset.
class RandomTransformSE3:
""" randomly generate rigid transformations """
def __init__(self, mag=0.8, mag_randomly=True):
# mag=0.8 is the pointnetlk_revisited dataset... | 7,262 | 28.052 | 101 | py |
pose-baselines | pose-baselines-main/ycb.py | # import copy
# import csv
# import json
import numpy as np
import open3d as o3d
import os
import pickle
from tqdm import tqdm
# import pytorch3d
import sys
import torch
# from pytorch3d import transforms, ops
from scipy.spatial.transform import Rotation as Rot
from utils_common import visualize_model_n_keypoints, visu... | 33,700 | 35.552061 | 138 | py |
pose-baselines | pose-baselines-main/fpfh_teaser/teaser_fpfh_icp.py | # import open3d as o3d
# import teaserpp_python
# import numpy as np
import torch
import copy
import sys
sys.path.append("../")
from teaser_utils.helpers import *
from utils_common import pos_tensor_to_o3d
def teaser_fpfh_icp(source_points, target_points, voxel_size=0.05, visualize=False):
"""
source_points ... | 5,709 | 33.817073 | 91 | py |
pose-baselines | pose-baselines-main/fpfh_teaser/evaluate_fpfh_teaser_icp.py | import argparse
import torch
from tqdm import tqdm
from torch.utils.tensorboard import SummaryWriter
from teaser_fpfh_icp import TEASER_FPFH_ICP
import sys
sys.path.append('../')
from shapenet import ShapeNet
from ycb import YCB
from utils_common import display_two_pcs
from utils_common import adds_error, rotation_err... | 4,943 | 34.568345 | 109 | py |
dimenet | dimenet-master/dimenet/training/metrics.py | import numpy as np
import tensorflow as tf
class Metrics:
def __init__(self, tag, targets, ex=None):
self.tag = tag
self.targets = targets
self.ex = ex
self.loss_metric = tf.keras.metrics.Mean()
self.mean_mae_metric = tf.keras.metrics.Mean()
self.maes_metric = tf.k... | 2,444 | 34.434783 | 99 | py |
dimenet | dimenet-master/dimenet/model/dimenet.py | import tensorflow as tf
from .layers.embedding_block import EmbeddingBlock
from .layers.bessel_basis_layer import BesselBasisLayer
from .layers.spherical_basis_layer import SphericalBasisLayer
from .layers.interaction_block import InteractionBlock
from .layers.output_block import OutputBlock
from .activations import s... | 4,834 | 37.991935 | 151 | py |
dimenet | dimenet-master/dimenet/model/dimenet_pp.py | import tensorflow as tf
from .layers.embedding_block import EmbeddingBlock
from .layers.bessel_basis_layer import BesselBasisLayer
from .layers.spherical_basis_layer import SphericalBasisLayer
from .layers.interaction_pp_block import InteractionPPBlock
from .layers.output_pp_block import OutputPPBlock
from .activation... | 5,223 | 37.411765 | 97 | py |
dimenet | dimenet-master/dimenet/model/layers/embedding_block.py | import numpy as np
import tensorflow as tf
from tensorflow.keras import layers
from ..initializers import GlorotOrthogonal
class EmbeddingBlock(layers.Layer):
def __init__(self, emb_size, activation=None,
name='embedding', **kwargs):
super().__init__(name=name, **kwargs)
self.emb... | 1,437 | 35.871795 | 97 | py |
dimenet | dimenet-master/dimenet/model/layers/residual_layer.py | from tensorflow.keras import layers
class ResidualLayer(layers.Layer):
def __init__(self, units, activation=None, use_bias=True,
kernel_initializer='glorot_uniform', bias_initializer='zeros',
name='residual', **kwargs):
super().__init__(name=name, **kwargs)
self.d... | 870 | 44.842105 | 84 | py |
dimenet | dimenet-master/dimenet/model/layers/output_pp_block.py | import tensorflow as tf
from tensorflow.keras import layers
from ..initializers import GlorotOrthogonal
class OutputPPBlock(layers.Layer):
def __init__(self, emb_size, out_emb_size, num_dense, num_targets=12,
activation=None, output_init='zeros', name='output', **kwargs):
super().__init_... | 1,436 | 34.04878 | 103 | py |
dimenet | dimenet-master/dimenet/model/layers/output_block.py | import tensorflow as tf
from tensorflow.keras import layers
from ..initializers import GlorotOrthogonal
class OutputBlock(layers.Layer):
def __init__(self, emb_size, num_dense, num_targets=12,
activation=None, output_init='zeros', name='output', **kwargs):
super().__init__(name=name, **k... | 1,275 | 34.444444 | 80 | py |
dimenet | dimenet-master/dimenet/model/layers/envelope.py | import tensorflow as tf
from tensorflow.keras import layers
class Envelope(layers.Layer):
"""
Envelope function that ensures a smooth cutoff
"""
def __init__(self, exponent, name='envelope', **kwargs):
super().__init__(name=name, **kwargs)
self.exponent = exponent
self.p = exp... | 722 | 29.125 | 118 | py |
dimenet | dimenet-master/dimenet/model/layers/interaction_block.py | import tensorflow as tf
from tensorflow.keras import layers
from .residual_layer import ResidualLayer
from ..initializers import GlorotOrthogonal
class InteractionBlock(layers.Layer):
def __init__(self, emb_size, num_bilinear, num_before_skip, num_after_skip,
activation=None, name='interaction',... | 3,329 | 40.111111 | 99 | py |
dimenet | dimenet-master/dimenet/model/layers/spherical_basis_layer.py | import sympy as sym
import tensorflow as tf
from tensorflow.keras import layers
from .basis_utils import bessel_basis, real_sph_harm
from .envelope import Envelope
class SphericalBasisLayer(layers.Layer):
def __init__(self, num_spherical, num_radial, cutoff, envelope_exponent=5,
name='spherical_... | 1,970 | 34.836364 | 104 | py |
dimenet | dimenet-master/dimenet/model/layers/bessel_basis_layer.py | import numpy as np
import tensorflow as tf
from tensorflow.keras import layers
from .envelope import Envelope
class BesselBasisLayer(layers.Layer):
def __init__(self, num_radial, cutoff, envelope_exponent=5,
name='bessel_basis', **kwargs):
super().__init__(name=name, **kwargs)
se... | 1,124 | 36.5 | 99 | py |
dimenet | dimenet-master/dimenet/model/layers/interaction_pp_block.py | import tensorflow as tf
from tensorflow.keras import layers
from .residual_layer import ResidualLayer
from ..initializers import GlorotOrthogonal
class InteractionPPBlock(layers.Layer):
def __init__(self, emb_size, int_emb_size, basis_emb_size, num_before_skip, num_after_skip,
activation=None, n... | 3,681 | 41.321839 | 102 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/setup.py | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import glob
import os
import shutil
from setuptools import find_packages, setup
from typing import List
import torch
from torch.utils.cpp_extension import CUDA_HOME, CppExtension, CUDAExtension
torch_ver = [int(x) for x in to... | 4,294 | 31.537879 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/hoglayer.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import math
import time
def timeit(x, func, iter=10):
torch.cuda.synchronize()
start = time.time()
for _ in range(iter):
y = func(x)
torch.cuda.synchronize()
runtime = (time.time()-start)/iter
return runtime
class HOG... | 5,424 | 32.487654 | 105 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/tools/benchmark.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
A script to benchmark builtin models.
Note: this script has an extra dependency of psutil.
"""
import itertools
import logging
import psutil
import torch
import tqdm
from fvcore.common.timer import Timer
from torch.nn.parallel import Distribut... | 4,533 | 28.828947 | 95 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/tools/visualize_data.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import argparse
import numpy as np
import os
from itertools import chain
import cv2
import tqdm
from PIL import Image
from detectron2.config import get_cfg
from detectron2.data import DatasetCatalog, MetadataCatalog, build_detection_train_loader
fr... | 3,720 | 36.969388 | 96 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/tools/plain_train_net.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
Detectron2 training script with a plain training loop.
This scripts reads a given config file and runs the training or evaluation.
It is an entry point that is able to train standard models in detectron2.
In order to let one script support tra... | 8,141 | 34.246753 | 99 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/tools/train_net.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
Detection Training Script.
This scripts reads a given config file and runs the training or evaluation.
It is an entry point that is made to train standard models in detectron2.
In order to let one script support training of many models,
this s... | 6,756 | 37.611429 | 115 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/model_zoo/model_zoo.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import os
import pkg_resources
import torch
from detectron2.checkpoint import DetectionCheckpointer
from detectron2.config import get_cfg
from detectron2.modeling import build_model
class ModelZooUrls(object):
"""
Mapping from names to of... | 7,261 | 54.015152 | 114 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/solver/lr_scheduler.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import math
from bisect import bisect_right
from typing import List
import torch
# NOTE: PyTorch's LR scheduler interface uses names that assume the LR changes
# only on epoch boundaries. We typically use iteration based schedules instead.
# As a r... | 4,163 | 34.589744 | 98 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/solver/build.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from typing import Any, Dict, List
import torch
from detectron2.config import CfgNode
from .lr_scheduler import WarmupCosineLR, WarmupMultiStepLR
def build_optimizer(cfg: CfgNode, model: torch.nn.Module, ty_opt=None) -> torch.optim.Optimizer:
... | 2,804 | 35.428571 | 96 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/evaluation/amodal_visible_evaluation.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import contextlib
import copy
import io
import itertools
import json
import logging
import numpy as np
import os
import pickle
from PIL import Image
from collections import OrderedDict
import pycocotools.mask as mask_util
import torch
from fvcore.co... | 38,265 | 45.103614 | 168 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/evaluation/lvis_evaluation.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import itertools
import json
import logging
import os
import pickle
from collections import OrderedDict
import torch
from fvcore.common.file_io import PathManager
import detectron2.utils.comm as comm
from detectron2.data import Metadata... | 13,169 | 37.621701 | 150 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/evaluation/cityscapes_evaluation.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import glob
import logging
import os
import tempfile
from collections import OrderedDict
import torch
from PIL import Image
from detectron2.data import MetadataCatalog
from detectron2.utils import comm
from .evaluator import DatasetEvaluator
cla... | 4,782 | 40.591304 | 139 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/evaluation/evaluator.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import datetime
import logging
import time
from collections import OrderedDict
from contextlib import contextmanager
from detectron2.utils.events import get_event_storage
from detectron2.utils.visualizer import Visualizer
from detectron2.modeling.po... | 12,599 | 39.514469 | 133 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/evaluation/sem_seg_evaluation.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import itertools
import json
import logging
import numpy as np
import os
from collections import OrderedDict
import PIL.Image as Image
import pycocotools.mask as mask_util
import torch
from fvcore.common.file_io import PathManager
from detectron2.d... | 6,791 | 40.414634 | 99 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/evaluation/pascal_voc_evaluation.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import numpy as np
import os
import tempfile
import xml.etree.ElementTree as ET
from collections import OrderedDict, defaultdict
from functools import lru_cache
import torch
from detectron2.data import Metada... | 10,459 | 34.699659 | 99 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/evaluation/coco_evaluation.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import contextlib
import copy
import io
import itertools
import json
import logging
import numpy as np
import os
import pickle
from PIL import Image
from collections import OrderedDict
import pycocotools.mask as mask_util
import torch
from fvcore.co... | 22,223 | 39.852941 | 168 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/checkpoint/c2_model_loading.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import logging
import re
import torch
from fvcore.common.checkpoint import (
get_missing_parameters_message,
get_unexpected_parameters_message,
)
def convert_basic_c2_names(original_keys):
"""
Apply some basic name conv... | 14,802 | 46.143312 | 99 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/checkpoint/detection_checkpoint.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import pickle
from fvcore.common.checkpoint import Checkpointer
from fvcore.common.file_io import PathManager
import detectron2.utils.comm as comm
from .c2_model_loading import align_and_update_state_dicts
class DetectionCheckpointer(Checkpointe... | 2,455 | 40.627119 | 91 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/layers/nms.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from torchvision.ops import boxes as box_ops
from torchvision.ops import nms # BC-compat
def batched_nms(boxes, scores, idxs, iou_threshold):
"""
Same as torchvision.ops.boxes.batched_nms, but safer.
... | 6,568 | 43.993151 | 98 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/layers/batch_norm.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import torch
import torch.distributed as dist
from torch import nn
from torch.autograd.function import Function
from detectron2.utils import comm
from .wrappers import BatchNorm2d
class FrozenBatchNorm2d(nn.Module):
"""
Ba... | 6,792 | 36.324176 | 99 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/layers/deform_conv.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
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 detectron2 import _C
from .wrap... | 15,825 | 30.971717 | 99 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/layers/roi_align.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
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 import _C
class _ROIAlign(Function):
@staticmethod
def forward(ctx, ... | 3,994 | 36.688679 | 96 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/layers/rotated_boxes.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from __future__ import absolute_import, division, print_function, unicode_literals
# import torch
from detectron2 import _C
def pairwise_iou_rotated(boxes1, boxes2):
"""
Return intersection-over-union (Jaccard index) of boxes.
Both s... | 684 | 26.4 | 82 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/layers/shape_spec.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from collections import namedtuple
class ShapeSpec(namedtuple("_ShapeSpec", ["channels", "height", "width", "stride"])):
"""
A simple structure that contains basic shape specification about a tensor.
It is often... | 672 | 31.047619 | 85 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/layers/wrappers.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
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
"""
... | 5,935 | 33.71345 | 97 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/layers/mask_ops.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
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 based ... | 9,423 | 37.942149 | 97 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/layers/roi_align_rotated.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
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 import _C
class _ROIAlignRotated(Function):
@staticmethod
def forwar... | 3,138 | 34.269663 | 90 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/engine/hooks.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import datetime
import logging
import os
import tempfile
import time
from collections import Counter
import torch
from fvcore.common.checkpoint import PeriodicCheckpointer as _PeriodicCheckpointer
from fvcore.common.file_io ... | 14,943 | 33.997658 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/engine/launch.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from detectron2.utils import comm
__all__ = ["launch"]
def _find_free_port():
import socket
sock = socket.socket(socket.AF_INET, socket.SOCK... | 3,140 | 36.392857 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/engine/defaults.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
This file contains components with some default boilerplate logic user may need
in training / testing. They will not work for everyone, but many users may find them useful.
The behavior of functions/classes in this file... | 24,896 | 39.417208 | 170 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/engine/train_loop.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import numpy as np
import time
import weakref
import torch
import detectron2.utils.comm as comm
from detectron2.utils.events import EventStorage
__all__ = ["HookBase", "TrainerBase", "SimpleTrainer"]
class... | 9,492 | 31.734483 | 96 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/utils/events.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import datetime
import json
import logging
import os
from collections import defaultdict
from contextlib import contextmanager
import torch
from fvcore.common.file_io import PathManager
from fvcore.common.history_buffer import HistoryBuffer
_CURREN... | 11,995 | 31.509485 | 97 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/utils/memory.py | # -*- coding: utf-8 -*-
import logging
from contextlib import contextmanager
from functools import wraps
import torch
__all__ = ["retry_if_cuda_oom"]
@contextmanager
def _ignore_torch_cuda_oom():
"""
A context which ignores CUDA OOM exception from pytorch.
"""
try:
yield
except RuntimeEr... | 2,578 | 28.643678 | 95 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/utils/comm.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
This file contains primitives for multi-gpu communication.
This is useful when doing distributed training.
"""
import functools
import logging
import numpy as np
import pickle
import torch
import torch.distributed as dist
_LOCAL_PROCESS_GROUP ... | 7,750 | 28.359848 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/utils/collect_env.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
import os
import subprocess
import sys
from collections import defaultdict
import PIL
import torch
import torchvision
from tabulate import tabulate
__all__ = ["collect_env_info"]
def collect_torch_env():
try:
import... | 2,797 | 29.086022 | 93 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/utils/visualizer.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import colorsys
import logging
import math
import numpy as np
from enum import Enum, unique
import cv2
import matplotlib as mpl
import matplotlib.colors as mplc
import matplotlib.figure as mplfigure
import pycocotools.mask as mask_util
import torch
... | 44,908 | 38.919111 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/utils/env.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import importlib
import importlib.util
import logging
import numpy as np
import os
import random
import sys
from datetime import datetime
import torch
__all__ = ["seed_all_rng"]
def seed_all_rng(seed=None):
"""
Set the random seed for the... | 3,283 | 29.981132 | 93 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/data/dataset_mapper.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import logging
import numpy as np
import torch
from fvcore.common.file_io import PathManager
from PIL import Image
from . import detection_utils as utils
from . import transforms as T
"""
This file contains the default mapping that's a... | 11,893 | 43.215613 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/data/detection_utils.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
Common data processing utilities that are used in a
typical object detection data pipeline.
"""
import logging
import numpy as np
import torch
from fvcore.common.file_io import PathManager
from PIL import Image, ImageOps... | 17,157 | 36.3 | 105 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/data/common.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import logging
import random
import torch.utils.data as data
from detectron2.utils.serialize import PicklableWrapper
__all__ = ["MapDataset", "DatasetFromList"]
class MapDataset(data.Dataset):
"""
Map a function over the elem... | 2,544 | 30.036585 | 86 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/data/build.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import bisect
import copy
import itertools
import logging
import numpy as np
import pickle
import torch.utils.data
from fvcore.common.file_io import PathManager
from tabulate import tabulate
from termcolor import colored
from detectron2.structures... | 19,310 | 37.933468 | 126 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/data/datasets/lvis_v0_5_categories.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
# Autogen with
# with open("lvis_v0.5_val.json", "r") as f:
# a = json.load(f)
# c = a["categories"]
# for x in c:
# del x["image_count"]
# del x["instance_count"]
# LVIS_CATEGORIES = repr(c) + " # noqa"
# fmt: off
LVIS_CATEGORIES = [{... | 223,777 | 15,983.142857 | 223,466 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/data/amodal_datasets/pycocotools/amodaleval.py | __author__ = 'yzhu'
import numpy as np
import datetime
import time
from collections import defaultdict
import json
from pycocotools import mask
import copy
import torchfile
import operator
import os.path
class AmodalEval:
def __init__(self, amodalGt=None, amodalDt=None):
'''
Initialize CocoEval u... | 18,633 | 41.35 | 123 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/data/samplers/grouped_batch_sampler.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
from torch.utils.data.sampler import BatchSampler, Sampler
class GroupedBatchSampler(BatchSampler):
"""
Wraps another sampler to yield a mini-batch of indices.
It enforces that the batch only contain elements from th... | 1,964 | 39.9375 | 98 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/data/samplers/distributed_sampler.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import itertools
import math
from collections import defaultdict
from typing import Optional
import torch
from torch.utils.data.sampler import Sampler
from detectron2.utils import comm
class TrainingSampler(Sampler):
"""
In training, we o... | 7,925 | 38.63 | 92 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/box_regression.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import math
import torch
# Value for clamping large dw and dh predictions. The heuristic is that we clamp
# such that dw and dh are no larger than what would transform a 16px box into a
# 1000px box (based on a small anchor, 16px, and a typical ima... | 8,992 | 41.620853 | 99 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/test_time_augmentation.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import numpy as np
from contextlib import contextmanager
from itertools import count
import torch
from torch import nn
from torch.nn.parallel import DistributedDataParallel
from detectron2.data.detection_utils import read_image
from det... | 9,767 | 38.228916 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/anchor_generator.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import copy
import math
from typing import List
import torch
from torch import nn
from detectron2.layers import ShapeSpec
from detectron2.structures import Boxes, RotatedBoxes
from detectron2.utils.registry import Registry
ANCHOR_GENERATOR_REGISTR... | 14,233 | 39.322946 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/matcher.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
class Matcher(object):
"""
This class assigns to each predicted "element" (e.g., a box) a ground-truth
element. Each predicted element will have exactly zero or one matches; each
ground-truth element may be matched to ... | 6,422 | 47.293233 | 99 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/sampling.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
__all__ = ["subsample_labels"]
def subsample_labels(labels, num_samples, positive_fraction, bg_label):
"""
Return `num_samples` (or fewer, if not enough found)
random samples from `labels` which is a mixture of positives ... | 2,288 | 43.882353 | 94 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/poolers.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import math
import sys
import torch
from torch import nn
from torchvision.ops import RoIPool
from detectron2.layers import ROIAlign, ROIAlignRotated, cat
__all__ = ["ROIPooler"]
def assign_boxes_to_levels(box_lists, min_level, max_level, canoni... | 10,508 | 43.529661 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/__init__.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from detectron2.layers import ShapeSpec
from .anchor_generator import build_anchor_generator, ANCHOR_GENERATOR_REGISTRY
from .backbone import (
BACKBONE_REGISTRY,
FPN,
Backbone,
ResNet,
ResNetBlockBase,
build_b... | 1,416 | 24.763636 | 120 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/postprocessing.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from torch.nn import functional as F
from detectron2.layers import paste_masks_in_image
from detectron2.structures import Instances
def detector_postprocess(results, output_height, output_width, mask_threshold=0.5):
"""
Resize the output ... | 4,844 | 39.041322 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/backbone/resnet.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
import fvcore.nn.weight_init as weight_init
import torch
import torch.nn.functional as F
from torch import nn
from detectron2.layers import (
Conv2d,
DeformConv,
FrozenBatchNorm2d,
ModulatedDeformConv,
ShapeSp... | 15,775 | 31.866667 | 97 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/backbone/backbone.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from abc import ABCMeta, abstractmethod
import torch.nn as nn
from detectron2.layers import ShapeSpec
__all__ = ["Backbone"]
class Backbone(nn.Module, metaclass=ABCMeta):
"""
Abstract base class for network backbones.
"""
def __... | 2,014 | 27.380282 | 97 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/backbone/fpn.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import math
import fvcore.nn.weight_init as weight_init
import torch.nn.functional as F
from torch import nn
from detectron2.layers import Conv2d, ShapeSpec, get_norm
from .backbone import Backbone
from .build import BACKBONE_REGISTRY
from .resnet... | 9,580 | 38.266393 | 99 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/meta_arch/rcnn.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import numpy as np
import torch
from torch import nn
from detectron2.structures import ImageList
from detectron2.utils.events import get_event_storage
from detectron2.utils.logger import log_first_n
from detectron2.utils.visualizer i... | 11,099 | 43.939271 | 111 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/meta_arch/retinanet.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import math
from typing import List
import torch
from fvcore.nn import sigmoid_focal_loss_jit, smooth_l1_loss
from torch import nn
from detectron2.layers import ShapeSpec, batched_nms, cat
from detectron2.structures import Boxes, Ima... | 18,950 | 42.969838 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/meta_arch/panoptic_fpn.py | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from torch import nn
from detectron2.structures import ImageList
from ..backbone import build_backbone
from ..postprocessing import detector_postprocess, sem_seg_postprocess
from ..proposal_generator import bu... | 8,447 | 37.930876 | 98 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/meta_arch/semantic_seg.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import numpy as np
from typing import Dict
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 Conv2d, ShapeSpec
from detectron2.structures import ImageLis... | 6,688 | 38.116959 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/roi_heads/recls_head.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
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.structures import Boxes, Instances, pairwise_iou
from detectron2.layers import Conv2d, ShapeSpec, ... | 11,316 | 43.207031 | 144 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/roi_heads/dis_head.py | import torch
import torch.nn as nn
from torch.nn import functional as F
import fvcore.nn.weight_init as weight_init
from detectron2.utils.events import get_event_storage
from detectron2.layers import Conv2d, ConvTranspose2d, ShapeSpec, cat, get_norm
from detectron2.utils.registry import Registry
from .mask_head import... | 4,846 | 30.679739 | 90 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/roi_heads/fast_rcnn.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import numpy as np
import torch
from fvcore.nn import smooth_l1_loss
from torch import nn
from torch.nn import functional as F
from detectron2.layers import batched_nms, cat
from detectron2.structures import Boxes, Instances
from det... | 25,008 | 43.420959 | 124 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/roi_heads/memo_functions.py | import torch
from torch.autograd import Function
class VectorQuantization(Function):
@staticmethod
def forward(ctx, inputs, codebook):
with torch.no_grad():
embedding_size = codebook.size(1)
inputs_size = inputs.size()
inputs_flatten = inputs.view(-1, embedding_size... | 2,501 | 34.742857 | 77 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/roi_heads/cascade_rcnn.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from torch import nn
from torch.autograd.function import Function
from detectron2.layers import ShapeSpec
from detectron2.structures import Boxes, Instances, pairwise_iou
from detectron2.utils.events import get_event_storage
from ..bo... | 10,422 | 41.717213 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/roi_heads/box_head.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
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 Conv2d, ShapeSpec, get_norm
from detectron2.utils.registry import Registry
ROI_BOX_... | 3,044 | 31.393617 | 89 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/roi_heads/keypoint_head.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.layers import Conv2d, ConvTranspose2d, ShapeSpec, cat, interpolate
from detectron2.structures import heatmaps_to_keypoints
from detectron2.utils.events import ge... | 7,084 | 40.923077 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/roi_heads/roi_heads.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import numpy as np
import os
from typing import Dict
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.layers import ShapeSpec
from typing import Dict, List, Optional, Tuple, Union
from detectron2... | 64,059 | 44.208186 | 151 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/roi_heads/recon_net.py | import math
import torch
import torch.nn as nn
from torch.nn import functional as F
from sklearn.cluster import KMeans
import torchvision.transforms as transforms
import fvcore.nn.weight_init as weight_init
from detectron2.layers import Conv2d, ConvTranspose2d, ShapeSpec, cat, get_norm
from detectron2.utils.events imp... | 33,073 | 44.745505 | 152 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/roi_heads/mask_amodal_head.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
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 Conv2d, ConvTranspose2d, ShapeSpec, cat, get_norm
from detectron2.utils.events import get_event_storage... | 10,050 | 41.409283 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/roi_heads/mask_visible_head.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
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 Conv2d, ConvTranspose2d, ShapeSpec, cat, get_norm
from detectron2.utils.events import get_event_storage... | 10,318 | 41.995833 | 122 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/roi_heads/rotated_fast_rcnn.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import numpy as np
from typing import Dict
import torch
from detectron2.layers import ShapeSpec, batched_nms_rotated
from detectron2.structures import Instances, RotatedBoxes, pairwise_iou_rotated
from detectron2.utils.events import ... | 12,434 | 40.588629 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/roi_heads/mask_head.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from PIL import Image
import copy
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 torchvision import transforms
from .memo_functions import vq, vq_st
from ty... | 46,170 | 43.869776 | 144 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/roi_heads/mask_invisible_head.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
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 Conv2d, ConvTranspose2d, ShapeSpec, cat, get_norm
from detectron2.utils.events import get_event_storage... | 8,466 | 44.767568 | 116 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/proposal_generator/rrpn.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
from typing import Dict
import torch
from detectron2.layers import ShapeSpec
from ..box_regression import Box2BoxTransformRotated
from .build import PROPOSAL_GENERATOR_REGISTRY
from .rpn import RPN
from .rrpn_outputs import RRPNOutp... | 3,349 | 37.068182 | 96 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/proposal_generator/rpn_outputs.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import itertools
import logging
import numpy as np
import torch
import torch.nn.functional as F
from fvcore.nn import smooth_l1_loss
from detectron2.layers import batched_nms, cat
from detectron2.structures import Boxes, Instances, pairwise_iou
fro... | 19,992 | 44.029279 | 100 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/proposal_generator/rpn.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from typing import Dict, List
import torch
import torch.nn.functional as F
from torch import nn
from detectron2.layers import ShapeSpec
from detectron2.utils.registry import Registry
from ..anchor_generator import build_anchor_generator
from ..box... | 7,810 | 40.328042 | 98 | py |
Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior | Amodal-Segmentation-Based-on-Visible-Region-Segmentation-and-Shape-Prior-main/detectron2/modeling/proposal_generator/proposal_utils.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import math
import torch
from detectron2.structures import Instances
def add_ground_truth_to_proposals(gt_boxes, proposals):
"""
Call `add_ground_truth_to_proposals_single_image` for all images.
Args:
gt_boxes(list[Boxes]): l... | 1,948 | 32.603448 | 93 | py |
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