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 |
|---|---|---|---|---|---|
insightface | challenges/iccv19-lfr/gen_video_feature.py | .py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from datetime import datetime
import os.path
from easydict import EasyDict as edict
import time
import json
import glob
import sys
import numpy as np
import importlib
import itertools
import argparse... | 216 | 7,154 |
insightface | examples/demo_analysis.py | .py | import argparse
import cv2
import sys
import numpy as np
import insightface
from insightface.app import FaceAnalysis
from insightface.data import get_image as ins_get_image
assert insightface.__version__>='0.3'
parser = argparse.ArgumentParser(description='insightface app test')
# general
parser.add_argument('--ctx',... | 35 | 985 |
insightface | examples/mask_renderer.py | .py | import os, sys, datetime
import numpy as np
import os.path as osp
import cv2
import insightface
from insightface.app import MaskRenderer
from insightface.data import get_image as ins_get_image
if __name__ == "__main__":
#make sure that you have download correct insightface model pack.
#make sure that BFM.mat ... | 23 | 648 |
insightface | examples/mxnet_to_onnx.py | .py | import sys
import os
import argparse
import onnx
import json
import mxnet as mx
from onnx import helper
from onnx import TensorProto
from onnx import numpy_helper
import onnxruntime
import cv2
print('mxnet version:', mx.__version__)
print('onnx version:', onnx.__version__)
assert mx.__version__ >= '1.8', 'mxnet versi... | 179 | 5,693 |
insightface | examples/face_recognition/insightface_app.py | .py | import cv2
import insightface
import numpy as np
from insightface.app import FaceAnalysis
# Initialize face analysis model
app = FaceAnalysis(name='buffalo_l', providers=['CPUExecutionProvider']) # Use 'CUDAExecutionProvider' for GPU
app.prepare(ctx_id=-1) # ctx_id=-1 for CPU, 0 for GPU
def get_face_embedding(image... | 47 | 1,518 |
insightface | examples/person_detection/scrfd_person.py | .py | import datetime
import numpy as np
import os
import os.path as osp
import glob
import cv2
import insightface
assert insightface.__version__>='0.4'
def detect_person(img, detector):
bboxes, kpss = detector.detect(img)
bboxes = np.round(bboxes[:,:4]).astype(np.int)
kpss = np.round(kpss).astype(np.int)
... | 49 | 1,681 |
insightface | examples/in_swapper/inswapper_main.py | .py | import datetime
import numpy as np
import os
import os.path as osp
import glob
import cv2
import insightface
from insightface.app import FaceAnalysis
from insightface.data import get_image as ins_get_image
assert insightface.__version__>='0.7'
if __name__ == '__main__':
app = FaceAnalysis(name='buffalo_l')
a... | 36 | 972 |
insightface | detection/retinaface_anticov/retinaface_cov.py | .py | from __future__ import print_function
import sys
import os
import datetime
import time
import numpy as np
import mxnet as mx
from mxnet import ndarray as nd
import cv2
#from rcnn import config
#from rcnn.processing.bbox_transform import nonlinear_pred, clip_boxes, landmark_pred
from rcnn.processing.bbox_transform impor... | 753 | 31,010 |
insightface | detection/retinaface_anticov/test.py | .py | import cv2
import sys
import numpy as np
import datetime
import os
import glob
from retinaface_cov import RetinaFaceCoV
thresh = 0.8
mask_thresh = 0.2
scales = [640, 1080]
count = 1
gpuid = 0
#detector = RetinaFaceCoV('./model/mnet_cov1', 0, gpuid, 'net3')
detector = RetinaFaceCoV('./model/mnet_cov2', 0, gpuid, 'net... | 67 | 1,856 |
insightface | detection/retinaface_anticov/rcnn/processing/generate_anchor.py | .py | """
Generate base anchors on index 0
"""
from __future__ import print_function
import sys
from builtins import range
import numpy as np
from ..cython.anchors import anchors_cython
#from ..config import config
def anchors_plane(feat_h, feat_w, stride, base_anchor):
return anchors_cython(feat_h, feat_w, stride, bas... | 136 | 4,043 |
insightface | detection/retinaface_anticov/rcnn/processing/assign_levels.py | .py | from rcnn.config import config
import numpy as np
def compute_assign_targets(rois, threshold):
rois_area = np.sqrt(
(rois[:, 2] - rois[:, 0] + 1) * (rois[:, 3] - rois[:, 1] + 1))
num_rois = np.shape(rois)[0]
assign_levels = np.zeros(num_rois, dtype=np.uint8)
for i, stride in enumerate(config.R... | 37 | 1,167 |
insightface | detection/retinaface_anticov/rcnn/processing/nms.py | .py | import numpy as np
from ..cython.cpu_nms import cpu_nms
try:
from ..cython.gpu_nms import gpu_nms
except ImportError:
gpu_nms = None
def py_nms_wrapper(thresh):
def _nms(dets):
return nms(dets, thresh)
return _nms
def cpu_nms_wrapper(thresh):
def _nms(dets):
return cpu_nms(dets,... | 68 | 1,546 |
insightface | detection/retinaface_anticov/rcnn/processing/bbox_regression.py | .py | """
This file has functions about generating bounding box regression targets
"""
from ..pycocotools.mask import encode
import numpy as np
from ..logger import logger
from .bbox_transform import bbox_overlaps, bbox_transform
from rcnn.config import config
import math
import cv2
import PIL.Image as Image
import threadi... | 264 | 10,196 |
insightface | detection/retinaface_anticov/rcnn/processing/bbox_transform.py | .py | import numpy as np
from ..cython.bbox import bbox_overlaps_cython
#from rcnn.config import config
def bbox_overlaps(boxes, query_boxes):
return bbox_overlaps_cython(boxes, query_boxes)
def bbox_overlaps_py(boxes, query_boxes):
"""
determine overlaps between boxes and query_boxes
:param boxes: n * 4 ... | 224 | 7,386 |
insightface | detection/blazeface_paddle/test_blazeface.py | .py | # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 594 | 21,321 |
insightface | detection/scrfd/setup.py | .py | #!/usr/bin/env python
import os
from setuptools import find_packages, setup
import torch
from torch.utils.cpp_extension import (BuildExtension, CppExtension,
CUDAExtension)
def readme():
with open('README.md', encoding='utf-8') as f:
content = f.read()
return co... | 162 | 5,864 |
insightface | detection/scrfd/demo/image_demo.py | .py | from argparse import ArgumentParser
from mmdet.apis import inference_detector, init_detector, show_result_pyplot
def main():
parser = ArgumentParser()
parser.add_argument('img', help='Image file')
parser.add_argument('config', help='Config file')
parser.add_argument('checkpoint', help='Checkpoint fil... | 27 | 906 |
insightface | detection/scrfd/demo/webcam_demo.py | .py | import argparse
import cv2
import torch
from mmdet.apis import inference_detector, init_detector
def parse_args():
parser = argparse.ArgumentParser(description='MMDetection webcam demo')
parser.add_argument('config', help='test config file path')
parser.add_argument('checkpoint', help='checkpoint file')... | 47 | 1,260 |
insightface | detection/scrfd/mmdet/__init__.py | .py | import mmcv
from .version import __version__, short_version
def digit_version(version_str):
digit_version = []
for x in version_str.split('.'):
if x.isdigit():
digit_version.append(int(x))
elif x.find('rc') != -1:
patch_version = x.split('rc')
digit_version... | 30 | 859 |
insightface | detection/scrfd/mmdet/version.py | .py | # Copyright (c) Open-MMLab. All rights reserved.
__version__ = '2.7.0'
short_version = __version__
def parse_version_info(version_str):
version_info = []
for x in version_str.split('.'):
if x.isdigit():
version_info.append(int(x))
elif x.find('rc') != -1:
patch_version... | 20 | 529 |
insightface | detection/scrfd/mmdet/apis/inference.py | .py | import warnings
import matplotlib.pyplot as plt
import mmcv
import numpy as np
import torch
from mmcv.ops import RoIPool
from mmcv.parallel import collate, scatter
from mmcv.runner import load_checkpoint
from mmdet.core import get_classes
from mmdet.datasets.pipelines import Compose
from mmdet.models import build_det... | 188 | 6,415 |
insightface | detection/scrfd/mmdet/apis/train.py | .py | import random
import numpy as np
import torch
from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
from mmcv.runner import (HOOKS, DistSamplerSeedHook, EpochBasedRunner,
Fp16OptimizerHook, OptimizerHook, build_optimizer)
from mmcv.utils import build_from_cfg
from mmdet.core imp... | 151 | 5,700 |
insightface | detection/scrfd/mmdet/apis/__init__.py | .py | from .inference import (async_inference_detector, inference_detector,
init_detector, show_result_pyplot)
from .test import multi_gpu_test, single_gpu_test
from .train import get_root_logger, set_random_seed, train_detector
__all__ = [
'get_root_logger', 'set_random_seed', 'train_detector', ... | 11 | 455 |
insightface | detection/scrfd/mmdet/apis/test.py | .py | import os.path as osp
import pickle
import shutil
import tempfile
import time
import mmcv
import torch
import torch.distributed as dist
from mmcv.image import tensor2imgs
from mmcv.runner import get_dist_info
from mmdet.core import encode_mask_results
def single_gpu_test(model,
data_loader,
... | 191 | 6,826 |
insightface | detection/scrfd/mmdet/datasets/retinaface.py | .py | import itertools
import logging
import os.path as osp
import tempfile
from collections import OrderedDict
import mmcv
import numpy as np
from mmcv.utils import print_log
from terminaltables import AsciiTable
from mmdet.core import eval_recalls
from .builder import DATASETS
from .custom import CustomDataset
try:
... | 170 | 5,818 |
insightface | detection/scrfd/mmdet/datasets/utils.py | .py | import copy
import warnings
def replace_ImageToTensor(pipelines):
"""Replace the ImageToTensor transform in a data pipeline to
DefaultFormatBundle, which is normally useful in batch inference.
Args:
pipelines (list[dict]): Data pipeline configs.
Returns:
list: The new pipeline list w... | 63 | 2,488 |
insightface | detection/scrfd/mmdet/datasets/builder.py | .py | import copy
import platform
import random
from functools import partial
import numpy as np
from mmcv.parallel import collate
from mmcv.runner import get_dist_info
from mmcv.utils import Registry, build_from_cfg
from torch.utils.data import DataLoader
from .samplers import DistributedGroupSampler, DistributedSampler, ... | 144 | 5,291 |
insightface | detection/scrfd/mmdet/datasets/deepfashion.py | .py | from .builder import DATASETS
from .coco import CocoDataset
@DATASETS.register_module()
class DeepFashionDataset(CocoDataset):
CLASSES = ('top', 'skirt', 'leggings', 'dress', 'outer', 'pants', 'bag',
'neckwear', 'headwear', 'eyeglass', 'belt', 'footwear', 'hair',
'skin', 'face')
| 11 | 317 |
insightface | detection/scrfd/mmdet/datasets/dataset_wrappers.py | .py | import bisect
import math
from collections import defaultdict
import numpy as np
from mmcv.utils import print_log
from torch.utils.data.dataset import ConcatDataset as _ConcatDataset
from .builder import DATASETS
from .coco import CocoDataset
@DATASETS.register_module()
class ConcatDataset(_ConcatDataset):
"""A... | 283 | 11,088 |
insightface | detection/scrfd/mmdet/datasets/custom.py | .py | import os.path as osp
import warnings
from collections import OrderedDict
import mmcv
import numpy as np
from torch.utils.data import Dataset
from mmdet.core import eval_map, eval_recalls
from .builder import DATASETS
from .pipelines import Compose
@DATASETS.register_module()
class CustomDataset(Dataset):
"""Cu... | 364 | 12,932 |
insightface | detection/scrfd/mmdet/datasets/voc.py | .py | from collections import OrderedDict
from mmdet.core import eval_map, eval_recalls
from .builder import DATASETS
from .xml_style import XMLDataset
@DATASETS.register_module()
class VOCDataset(XMLDataset):
CLASSES = ('aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car',
'cat', 'chair', 'c... | 90 | 3,538 |
insightface | detection/scrfd/mmdet/datasets/__init__.py | .py | from .builder import DATASETS, PIPELINES, build_dataloader, build_dataset
from .cityscapes import CityscapesDataset
from .coco import CocoDataset
from .custom import CustomDataset
from .retinaface import RetinaFaceDataset
from .dataset_wrappers import (ClassBalancedDataset, ConcatDataset,
... | 25 | 1,111 |
insightface | detection/scrfd/mmdet/datasets/cityscapes.py | .py | # Modified from https://github.com/facebookresearch/detectron2/blob/master/detectron2/data/datasets/cityscapes.py # noqa
# and https://github.com/mcordts/cityscapesScripts/blob/master/cityscapesscripts/evaluation/evalInstanceLevelSemanticLabeling.py # noqa
import glob
import os
import os.path as osp
import tempfile
fr... | 335 | 14,288 |
insightface | detection/scrfd/mmdet/datasets/xml_style.py | .py | import os.path as osp
import xml.etree.ElementTree as ET
import mmcv
import numpy as np
from PIL import Image
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class XMLDataset(CustomDataset):
"""XML dataset for detection.
Args:
min_size (int | float, optio... | 170 | 5,753 |
insightface | detection/scrfd/mmdet/datasets/wider_face.py | .py | import os.path as osp
import xml.etree.ElementTree as ET
import mmcv
from .builder import DATASETS
from .xml_style import XMLDataset
@DATASETS.register_module()
class WIDERFaceDataset(XMLDataset):
"""Reader for the WIDER Face dataset in PASCAL VOC format.
Conversion scripts can be found in
https://gith... | 52 | 1,501 |
insightface | detection/scrfd/mmdet/datasets/lvis.py | .py | import itertools
import logging
import os.path as osp
import tempfile
from collections import OrderedDict
import numpy as np
from mmcv.utils import print_log
from terminaltables import AsciiTable
from .builder import DATASETS
from .coco import CocoDataset
@DATASETS.register_module()
class LVISV05Dataset(CocoDataset... | 745 | 46,540 |
insightface | detection/scrfd/mmdet/datasets/coco.py | .py | import itertools
import logging
import os.path as osp
import tempfile
from collections import OrderedDict
import mmcv
import numpy as np
from mmcv.utils import print_log
from pycocotools.coco import COCO
from pycocotools.cocoeval import COCOeval
from terminaltables import AsciiTable
from mmdet.core import eval_recall... | 545 | 22,583 |
insightface | detection/scrfd/mmdet/datasets/pipelines/auto_augment.py | .py | import copy
import cv2
import mmcv
import numpy as np
from ..builder import PIPELINES
from .compose import Compose
_MAX_LEVEL = 10
def level_to_value(level, max_value):
"""Map from level to values based on max_value."""
return (level / _MAX_LEVEL) * max_value
def enhance_level_to_value(level, a=1.8, b=0.... | 891 | 36,390 |
insightface | detection/scrfd/mmdet/datasets/pipelines/compose.py | .py | import collections
from mmcv.utils import build_from_cfg
from ..builder import PIPELINES
@PIPELINES.register_module()
class Compose(object):
"""Compose multiple transforms sequentially.
Args:
transforms (Sequence[dict | callable]): Sequence of transform object or
config dict to be compo... | 52 | 1,464 |
insightface | detection/scrfd/mmdet/datasets/pipelines/loading.py | .py | import os.path as osp
import mmcv
import numpy as np
import pycocotools.mask as maskUtils
from mmdet.core import BitmapMasks, PolygonMasks
from ..builder import PIPELINES
@PIPELINES.register_module()
class LoadImageFromFile(object):
"""Load an image from file.
Required keys are "img_prefix" and "img_info" ... | 481 | 16,712 |
insightface | detection/scrfd/mmdet/datasets/pipelines/__init__.py | .py | from .auto_augment import (AutoAugment, BrightnessTransform, ColorTransform,
ContrastTransform, EqualizeTransform, Rotate, Shear,
Translate)
from .compose import Compose
from .formating import (Collect, DefaultFormatBundle, ImageToTensor,
ToD... | 28 | 1,496 |
insightface | detection/scrfd/mmdet/datasets/pipelines/transforms.py | .py | import inspect
import mmcv
import numpy as np
from numpy import random
import cv2
from mmdet.core import PolygonMasks
from mmdet.core.evaluation.bbox_overlaps import bbox_overlaps
from ..builder import PIPELINES
try:
from imagecorruptions import corrupt
except ImportError:
corrupt = None
try:
import alb... | 2,038 | 80,945 |
insightface | detection/scrfd/mmdet/datasets/pipelines/instaboost.py | .py | import numpy as np
from ..builder import PIPELINES
@PIPELINES.register_module()
class InstaBoost(object):
r"""Data augmentation method in `InstaBoost: Boosting Instance
Segmentation Via Probability Map Guided Copy-Pasting
<https://arxiv.org/abs/1908.07801>`_.
Refer to https://github.com/GothicAi/Ins... | 99 | 3,494 |
insightface | detection/scrfd/mmdet/datasets/pipelines/test_time_aug.py | .py | import warnings
import mmcv
from ..builder import PIPELINES
from .compose import Compose
@PIPELINES.register_module()
class MultiScaleFlipAug(object):
"""Test-time augmentation with multiple scales and flipping.
An example configuration is as followed:
.. code-block::
img_scale=[(1333, 400), ... | 120 | 4,401 |
insightface | detection/scrfd/mmdet/datasets/pipelines/formating.py | .py | from collections.abc import Sequence
import mmcv
import numpy as np
import torch
from mmcv.parallel import DataContainer as DC
from ..builder import PIPELINES
def to_tensor(data):
"""Convert objects of various python types to :obj:`torch.Tensor`.
Supported types are: :class:`numpy.ndarray`, :class:`torch.T... | 365 | 12,054 |
insightface | detection/scrfd/mmdet/datasets/samplers/distributed_sampler.py | .py | import math
import torch
from torch.utils.data import DistributedSampler as _DistributedSampler
class DistributedSampler(_DistributedSampler):
def __init__(self, dataset, num_replicas=None, rank=None, shuffle=True):
super().__init__(dataset, num_replicas=num_replicas, rank=rank)
self.shuffle = s... | 33 | 1,104 |
insightface | detection/scrfd/mmdet/datasets/samplers/group_sampler.py | .py | from __future__ import division
import math
import numpy as np
import torch
from mmcv.runner import get_dist_info
from torch.utils.data import Sampler
class GroupSampler(Sampler):
def __init__(self, dataset, samples_per_gpu=1):
assert hasattr(dataset, 'flag')
self.dataset = dataset
self.... | 144 | 5,073 |
insightface | detection/scrfd/mmdet/datasets/samplers/__init__.py | .py | from .distributed_sampler import DistributedSampler
from .group_sampler import DistributedGroupSampler, GroupSampler
__all__ = ['DistributedSampler', 'DistributedGroupSampler', 'GroupSampler']
| 5 | 194 |
insightface | detection/scrfd/mmdet/core/mask/utils.py | .py | import mmcv
import numpy as np
import pycocotools.mask as mask_util
def split_combined_polys(polys, poly_lens, polys_per_mask):
"""Split the combined 1-D polys into masks.
A mask is represented as a list of polys, and a poly is represented as
a 1-D array. In dataset, all masks are concatenated into a sin... | 64 | 2,291 |
insightface | detection/scrfd/mmdet/core/mask/__init__.py | .py | from .mask_target import mask_target
from .structures import BaseInstanceMasks, BitmapMasks, PolygonMasks
from .utils import encode_mask_results, split_combined_polys
__all__ = [
'split_combined_polys', 'mask_target', 'BaseInstanceMasks', 'BitmapMasks',
'PolygonMasks', 'encode_mask_results'
]
| 9 | 303 |
insightface | detection/scrfd/mmdet/core/mask/structures.py | .py | from abc import ABCMeta, abstractmethod
import cv2
import mmcv
import numpy as np
import pycocotools.mask as maskUtils
import torch
from mmcv.ops.roi_align import roi_align
class BaseInstanceMasks(metaclass=ABCMeta):
"""Base class for instance masks."""
@abstractmethod
def rescale(self, scale, interpola... | 828 | 30,134 |
insightface | detection/scrfd/mmdet/core/mask/mask_target.py | .py | import numpy as np
import torch
from torch.nn.modules.utils import _pair
def mask_target(pos_proposals_list, pos_assigned_gt_inds_list, gt_masks_list,
cfg):
"""Compute mask target for positive proposals in multiple images.
Args:
pos_proposals_list (list[Tensor]): Positive proposals in... | 63 | 2,354 |
insightface | detection/scrfd/mmdet/core/fp16/deprecated_fp16_utils.py | .py | import warnings
from mmcv.runner import (Fp16OptimizerHook, auto_fp16, force_fp32,
wrap_fp16_model)
class DeprecatedFp16OptimizerHook(Fp16OptimizerHook):
"""A wrapper class for the FP16 optimizer hook. This class wraps
:class:`Fp16OptimizerHook` in `mmcv.runner` and shows a warning t... | 48 | 1,600 |
insightface | detection/scrfd/mmdet/core/fp16/__init__.py | .py | from .deprecated_fp16_utils import \
DeprecatedFp16OptimizerHook as Fp16OptimizerHook
from .deprecated_fp16_utils import deprecated_auto_fp16 as auto_fp16
from .deprecated_fp16_utils import deprecated_force_fp32 as force_fp32
from .deprecated_fp16_utils import \
deprecated_wrap_fp16_model as wrap_fp16_model
__... | 9 | 396 |
insightface | detection/scrfd/mmdet/core/export/__init__.py | .py | from .pytorch2onnx import (build_model_from_cfg,
generate_inputs_and_wrap_model,
preprocess_example_input)
__all__ = [
'build_model_from_cfg', 'generate_inputs_and_wrap_model',
'preprocess_example_input'
]
| 9 | 269 |
insightface | detection/scrfd/mmdet/core/export/pytorch2onnx.py | .py | from functools import partial
import mmcv
import numpy as np
import torch
from mmcv.runner import load_checkpoint
def generate_inputs_and_wrap_model(config_path, checkpoint_path, input_config):
"""Prepare sample input and wrap model for ONNX export.
The ONNX export API only accept args, and all inputs shoul... | 144 | 5,329 |
insightface | detection/scrfd/mmdet/core/bbox/builder.py | .py | from mmcv.utils import Registry, build_from_cfg
BBOX_ASSIGNERS = Registry('bbox_assigner')
BBOX_SAMPLERS = Registry('bbox_sampler')
BBOX_CODERS = Registry('bbox_coder')
def build_assigner(cfg, **default_args):
"""Builder of box assigner."""
return build_from_cfg(cfg, BBOX_ASSIGNERS, default_args)
def build... | 21 | 580 |
insightface | detection/scrfd/mmdet/core/bbox/__init__.py | .py | from .assigners import (AssignResult, BaseAssigner, CenterRegionAssigner,
MaxIoUAssigner)
from .builder import build_assigner, build_bbox_coder, build_sampler
from .coder import (BaseBBoxCoder, DeltaXYWHBBoxCoder, PseudoBBoxCoder,
TBLRBBoxCoder)
from .iou_calculators import B... | 28 | 1,575 |
insightface | detection/scrfd/mmdet/core/bbox/transforms.py | .py | import numpy as np
import torch
def bbox_flip(bboxes, img_shape, direction='horizontal'):
"""Flip bboxes horizontally or vertically.
Args:
bboxes (Tensor): Shape (..., 4*k)
img_shape (tuple): Image shape.
direction (str): Flip direction, options are "horizontal", "vertical",
... | 271 | 8,677 |
insightface | detection/scrfd/mmdet/core/bbox/demodata.py | .py | import numpy as np
import torch
def ensure_rng(rng=None):
"""Simple version of the ``kwarray.ensure_rng``
Args:
rng (int | numpy.random.RandomState | None):
if None, then defaults to the global rng. Otherwise this can be an
integer or a RandomState class
Returns:
(... | 64 | 1,748 |
insightface | detection/scrfd/mmdet/core/bbox/iou_calculators/builder.py | .py | from mmcv.utils import Registry, build_from_cfg
IOU_CALCULATORS = Registry('IoU calculator')
def build_iou_calculator(cfg, default_args=None):
"""Builder of IoU calculator."""
return build_from_cfg(cfg, IOU_CALCULATORS, default_args)
| 9 | 245 |
insightface | detection/scrfd/mmdet/core/bbox/iou_calculators/__init__.py | .py | from .builder import build_iou_calculator
from .iou2d_calculator import BboxOverlaps2D, bbox_overlaps
__all__ = ['build_iou_calculator', 'BboxOverlaps2D', 'bbox_overlaps']
| 5 | 173 |
insightface | detection/scrfd/mmdet/core/bbox/iou_calculators/iou2d_calculator.py | .py | import torch
from .builder import IOU_CALCULATORS
@IOU_CALCULATORS.register_module()
class BboxOverlaps2D(object):
"""2D Overlaps (e.g. IoUs, GIoUs) Calculator."""
def __call__(self, bboxes1, bboxes2, mode='iou', is_aligned=False):
"""Calculate IoU between 2D bboxes.
Args:
bboxe... | 160 | 6,184 |
insightface | detection/scrfd/mmdet/core/bbox/assigners/atss_assigner.py | .py | import torch
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
@BBOX_ASSIGNERS.register_module()
class ATSSAssigner(BaseAssigner):
"""Assign a corresponding gt bbox or background to each bbox.
... | 216 | 9,497 |
insightface | detection/scrfd/mmdet/core/bbox/assigners/grid_assigner.py | .py | import torch
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
@BBOX_ASSIGNERS.register_module()
class GridAssigner(BaseAssigner):
"""Assign a corresponding gt bbox or background to each bbox.
... | 156 | 6,816 |
insightface | detection/scrfd/mmdet/core/bbox/assigners/hungarian_assigner.py | .py | import torch
from scipy.optimize import linear_sum_assignment
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from ..transforms import bbox_cxcywh_to_xyxy, bbox_xyxy_to_cxcywh
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
@BBOX_ASSIGNERS.regis... | 159 | 7,173 |
insightface | detection/scrfd/mmdet/core/bbox/assigners/center_region_assigner.py | .py | import torch
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
def scale_boxes(bboxes, scale):
"""Expand an array of boxes by a given scale.
Args:
bboxes (Tensor): Shape (m, 4)
... | 336 | 15,429 |
insightface | detection/scrfd/mmdet/core/bbox/assigners/__init__.py | .py | from .approx_max_iou_assigner import ApproxMaxIoUAssigner
from .assign_result import AssignResult
from .atss_assigner import ATSSAssigner
from .base_assigner import BaseAssigner
from .center_region_assigner import CenterRegionAssigner
from .grid_assigner import GridAssigner
from .hungarian_assigner import HungarianAssi... | 16 | 606 |
insightface | detection/scrfd/mmdet/core/bbox/assigners/approx_max_iou_assigner.py | .py | import torch
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from .max_iou_assigner import MaxIoUAssigner
@BBOX_ASSIGNERS.register_module()
class ApproxMaxIoUAssigner(MaxIoUAssigner):
"""Assign a corresponding gt bbox or background to each bbox.
Each proposals will be... | 146 | 6,649 |
insightface | detection/scrfd/mmdet/core/bbox/assigners/max_iou_assigner.py | .py | import torch
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
@BBOX_ASSIGNERS.register_module()
class MaxIoUAssigner(BaseAssigner):
"""Assign a corresponding gt bbox or background to each bbox.
... | 213 | 9,750 |
insightface | detection/scrfd/mmdet/core/bbox/assigners/point_assigner.py | .py | import torch
from ..builder import BBOX_ASSIGNERS
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
@BBOX_ASSIGNERS.register_module()
class PointAssigner(BaseAssigner):
"""Assign a corresponding gt bbox or background to each point.
Each proposals will be assigned with `0`, or a... | 134 | 5,947 |
insightface | detection/scrfd/mmdet/core/bbox/assigners/assign_result.py | .py | import torch
from mmdet.utils import util_mixins
class AssignResult(util_mixins.NiceRepr):
"""Stores assignments between predicted and truth boxes.
Attributes:
num_gts (int): the number of truth boxes considered when computing this
assignment
gt_inds (LongTensor): for each predi... | 205 | 7,705 |
insightface | detection/scrfd/mmdet/core/bbox/assigners/base_assigner.py | .py | from abc import ABCMeta, abstractmethod
class BaseAssigner(metaclass=ABCMeta):
"""Base assigner that assigns boxes to ground truth boxes."""
@abstractmethod
def assign(self, bboxes, gt_bboxes, gt_bboxes_ignore=None, gt_labels=None):
"""Assign boxes to either a ground truth boxe or a negative boxe... | 11 | 339 |
insightface | detection/scrfd/mmdet/core/bbox/samplers/instance_balanced_pos_sampler.py | .py | import numpy as np
import torch
from ..builder import BBOX_SAMPLERS
from .random_sampler import RandomSampler
@BBOX_SAMPLERS.register_module()
class InstanceBalancedPosSampler(RandomSampler):
"""Instance balanced sampler that samples equal number of positive samples
for each instance."""
def _sample_pos... | 56 | 2,271 |
insightface | detection/scrfd/mmdet/core/bbox/samplers/iou_balanced_neg_sampler.py | .py | import numpy as np
import torch
from ..builder import BBOX_SAMPLERS
from .random_sampler import RandomSampler
@BBOX_SAMPLERS.register_module()
class IoUBalancedNegSampler(RandomSampler):
"""IoU Balanced Sampling.
arXiv: https://arxiv.org/pdf/1904.02701.pdf (CVPR 2019)
Sampling proposals according to th... | 158 | 6,696 |
insightface | detection/scrfd/mmdet/core/bbox/samplers/score_hlr_sampler.py | .py | import torch
from mmcv.ops import nms_match
from ..builder import BBOX_SAMPLERS
from ..transforms import bbox2roi
from .base_sampler import BaseSampler
from .sampling_result import SamplingResult
@BBOX_SAMPLERS.register_module()
class ScoreHLRSampler(BaseSampler):
r"""Importance-based Sample Reweighting (ISR_N),... | 265 | 11,187 |
insightface | detection/scrfd/mmdet/core/bbox/samplers/__init__.py | .py | from .base_sampler import BaseSampler
from .combined_sampler import CombinedSampler
from .instance_balanced_pos_sampler import InstanceBalancedPosSampler
from .iou_balanced_neg_sampler import IoUBalancedNegSampler
from .ohem_sampler import OHEMSampler
from .pseudo_sampler import PseudoSampler
from .random_sampler impor... | 16 | 628 |
insightface | detection/scrfd/mmdet/core/bbox/samplers/ohem_sampler.py | .py | import torch
from ..builder import BBOX_SAMPLERS
from ..transforms import bbox2roi
from .base_sampler import BaseSampler
@BBOX_SAMPLERS.register_module()
class OHEMSampler(BaseSampler):
r"""Online Hard Example Mining Sampler described in `Training Region-based
Object Detectors with Online Hard Example Mining... | 108 | 4,098 |
insightface | detection/scrfd/mmdet/core/bbox/samplers/random_sampler.py | .py | import torch
from ..builder import BBOX_SAMPLERS
from .base_sampler import BaseSampler
@BBOX_SAMPLERS.register_module()
class RandomSampler(BaseSampler):
"""Random sampler.
Args:
num (int): Number of samples
pos_fraction (float): Fraction of positive samples
neg_pos_up (int, optional... | 79 | 2,817 |
insightface | detection/scrfd/mmdet/core/bbox/samplers/sampling_result.py | .py | import torch
from mmdet.utils import util_mixins
class SamplingResult(util_mixins.NiceRepr):
"""Bbox sampling result.
Example:
>>> # xdoctest: +IGNORE_WANT
>>> from mmdet.core.bbox.samplers.sampling_result import * # NOQA
>>> self = SamplingResult.random(rng=10)
>>> print(f'... | 153 | 5,334 |
insightface | detection/scrfd/mmdet/core/bbox/samplers/pseudo_sampler.py | .py | import torch
from ..builder import BBOX_SAMPLERS
from .base_sampler import BaseSampler
from .sampling_result import SamplingResult
@BBOX_SAMPLERS.register_module()
class PseudoSampler(BaseSampler):
"""A pseudo sampler that does not do sampling actually."""
def __init__(self, **kwargs):
pass
def... | 42 | 1,415 |
insightface | detection/scrfd/mmdet/core/bbox/samplers/base_sampler.py | .py | from abc import ABCMeta, abstractmethod
import torch
from .sampling_result import SamplingResult
class BaseSampler(metaclass=ABCMeta):
"""Base class of samplers."""
def __init__(self,
num,
pos_fraction,
neg_pos_ub=-1,
add_gt_as_proposals=T... | 102 | 3,872 |
insightface | detection/scrfd/mmdet/core/bbox/samplers/combined_sampler.py | .py | from ..builder import BBOX_SAMPLERS, build_sampler
from .base_sampler import BaseSampler
@BBOX_SAMPLERS.register_module()
class CombinedSampler(BaseSampler):
"""A sampler that combines positive sampler and negative sampler."""
def __init__(self, pos_sampler, neg_sampler, **kwargs):
super(CombinedSamp... | 21 | 700 |
insightface | detection/scrfd/mmdet/core/bbox/coder/legacy_delta_xywh_bbox_coder.py | .py | import numpy as np
import torch
from ..builder import BBOX_CODERS
from .base_bbox_coder import BaseBBoxCoder
@BBOX_CODERS.register_module()
class LegacyDeltaXYWHBBoxCoder(BaseBBoxCoder):
"""Legacy Delta XYWH BBox coder used in MMDet V1.x.
Following the practice in R-CNN [1]_, this coder encodes bbox (x1, y1... | 213 | 8,147 |
insightface | detection/scrfd/mmdet/core/bbox/coder/delta_xywh_bbox_coder.py | .py | import numpy as np
import torch
from ..builder import BBOX_CODERS
from .base_bbox_coder import BaseBBoxCoder
@BBOX_CODERS.register_module()
class DeltaXYWHBBoxCoder(BaseBBoxCoder):
"""Delta XYWH BBox coder.
Following the practice in `R-CNN <https://arxiv.org/abs/1311.2524>`_,
this coder encodes bbox (x1... | 205 | 7,756 |
insightface | detection/scrfd/mmdet/core/bbox/coder/yolo_bbox_coder.py | .py | import torch
from ..builder import BBOX_CODERS
from .base_bbox_coder import BaseBBoxCoder
@BBOX_CODERS.register_module()
class YOLOBBoxCoder(BaseBBoxCoder):
"""YOLO BBox coder.
Following `YOLO <https://arxiv.org/abs/1506.02640>`_, this coder divide
image into grids, and encode bbox (x1, y1, x2, y2) into... | 87 | 3,417 |
insightface | detection/scrfd/mmdet/core/bbox/coder/pseudo_bbox_coder.py | .py | from ..builder import BBOX_CODERS
from .base_bbox_coder import BaseBBoxCoder
@BBOX_CODERS.register_module()
class PseudoBBoxCoder(BaseBBoxCoder):
"""Pseudo bounding box coder."""
def __init__(self, **kwargs):
super(BaseBBoxCoder, self).__init__(**kwargs)
def encode(self, bboxes, gt_bboxes):
... | 19 | 529 |
insightface | detection/scrfd/mmdet/core/bbox/coder/__init__.py | .py | from .base_bbox_coder import BaseBBoxCoder
from .bucketing_bbox_coder import BucketingBBoxCoder
from .delta_xywh_bbox_coder import DeltaXYWHBBoxCoder
from .legacy_delta_xywh_bbox_coder import LegacyDeltaXYWHBBoxCoder
from .pseudo_bbox_coder import PseudoBBoxCoder
from .tblr_bbox_coder import TBLRBBoxCoder
from .yolo_bb... | 14 | 518 |
insightface | detection/scrfd/mmdet/core/bbox/coder/base_bbox_coder.py | .py | from abc import ABCMeta, abstractmethod
class BaseBBoxCoder(metaclass=ABCMeta):
"""Base bounding box coder."""
def __init__(self, **kwargs):
pass
@abstractmethod
def encode(self, bboxes, gt_bboxes):
"""Encode deltas between bboxes and ground truth boxes."""
pass
@abstrac... | 20 | 474 |
insightface | detection/scrfd/mmdet/core/bbox/coder/tblr_bbox_coder.py | .py | import torch
from ..builder import BBOX_CODERS
from .base_bbox_coder import BaseBBoxCoder
@BBOX_CODERS.register_module()
class TBLRBBoxCoder(BaseBBoxCoder):
"""TBLR BBox coder.
Following the practice in `FSAF <https://arxiv.org/abs/1903.00621>`_,
this coder encodes gt bboxes (x1, y1, x2, y2) into (top, ... | 173 | 6,993 |
insightface | detection/scrfd/mmdet/core/bbox/coder/bucketing_bbox_coder.py | .py | import numpy as np
import torch
import torch.nn.functional as F
from ..builder import BBOX_CODERS
from ..transforms import bbox_rescale
from .base_bbox_coder import BaseBBoxCoder
@BBOX_CODERS.register_module()
class BucketingBBoxCoder(BaseBBoxCoder):
"""Bucketing BBox Coder for Side-Aware Bounday Localization (S... | 347 | 13,982 |
insightface | detection/scrfd/mmdet/core/anchor/utils.py | .py | import torch
def images_to_levels(target, num_levels):
"""Convert targets by image to targets by feature level.
[target_img0, target_img1] -> [target_level0, target_level1, ...]
"""
target = torch.stack(target, 0)
level_targets = []
start = 0
for n in num_levels:
end = start + n
... | 72 | 2,497 |
insightface | detection/scrfd/mmdet/core/anchor/builder.py | .py | from mmcv.utils import Registry, build_from_cfg
ANCHOR_GENERATORS = Registry('Anchor generator')
def build_anchor_generator(cfg, default_args=None):
return build_from_cfg(cfg, ANCHOR_GENERATORS, default_args)
| 8 | 216 |
insightface | detection/scrfd/mmdet/core/anchor/anchor_generator.py | .py | import mmcv
import numpy as np
import torch
from torch.nn.modules.utils import _pair
from .builder import ANCHOR_GENERATORS
@ANCHOR_GENERATORS.register_module()
class AnchorGenerator(object):
"""Standard anchor generator for 2D anchor-based detectors.
Args:
strides (list[int] | list[tuple[int, int]]... | 729 | 31,168 |
insightface | detection/scrfd/mmdet/core/anchor/__init__.py | .py | from .anchor_generator import (AnchorGenerator, LegacyAnchorGenerator,
YOLOAnchorGenerator)
from .builder import ANCHOR_GENERATORS, build_anchor_generator
from .point_generator import PointGenerator
from .utils import anchor_inside_flags, calc_region, images_to_levels
__all__ = [
'An... | 12 | 516 |
insightface | detection/scrfd/mmdet/core/anchor/point_generator.py | .py | import torch
from .builder import ANCHOR_GENERATORS
@ANCHOR_GENERATORS.register_module()
class PointGenerator(object):
def _meshgrid(self, x, y, row_major=True):
xx = x.repeat(len(y))
yy = y.view(-1, 1).repeat(1, len(x)).view(-1)
if row_major:
return xx, yy
else:
... | 38 | 1,362 |
insightface | detection/scrfd/mmdet/core/post_processing/bbox_nms.py | .py | import torch
from mmcv.ops.nms import batched_nms
from mmdet.core.bbox.iou_calculators import bbox_overlaps
def multiclass_nms(multi_bboxes,
multi_scores,
score_thr,
nms_cfg,
max_num=-1,
score_factors=None,
... | 150 | 5,446 |
insightface | detection/scrfd/mmdet/core/post_processing/merge_augs.py | .py | import numpy as np
import torch
from mmcv.ops import nms
from ..bbox import bbox_mapping_back
def merge_aug_proposals(aug_proposals, img_metas, rpn_test_cfg):
"""Merge augmented proposals (multiscale, flip, etc.)
Args:
aug_proposals (list[Tensor]): proposals from different testing
scheme... | 118 | 4,286 |
insightface | detection/scrfd/mmdet/core/post_processing/__init__.py | .py | from .bbox_nms import fast_nms, multiclass_nms
from .merge_augs import (merge_aug_bboxes, merge_aug_masks,
merge_aug_proposals, merge_aug_scores)
__all__ = [
'multiclass_nms', 'merge_aug_proposals', 'merge_aug_bboxes',
'merge_aug_scores', 'merge_aug_masks', 'fast_nms'
]
| 9 | 305 |
insightface | detection/scrfd/mmdet/core/evaluation/__init__.py | .py | from .class_names import (cityscapes_classes, coco_classes, dataset_aliases,
get_classes, imagenet_det_classes,
imagenet_vid_classes, voc_classes)
from .eval_hooks import DistEvalHook, EvalHook
from .mean_ap import average_precision, eval_map, print_map_summary
from .... | 18 | 860 |
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