repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
value |
|---|---|---|---|---|---|---|
us_hep_funding | us_hep_funding-main/us_hep_funding/data/downloaders/__init__.py | from ._doe_downloader import DoeDataDownloader
from ._usa_spending_downloader import UsaSpendingDataDownloader
from ._suli_student_data import SuliStudentDataDownloader
| 169 | 41.5 | 63 | py |
us_hep_funding | us_hep_funding-main/us_hep_funding/mapping/__init__.py | from ._suli_student_map_maker import SuliStudentMapMaker
| 57 | 28 | 56 | py |
us_hep_funding | us_hep_funding-main/us_hep_funding/mapping/_suli_student_map_maker.py | import numpy as np
import matplotlib.pyplot as plt
import cartopy
import pandas as pd
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import cartopy.io.shapereader as shpreader
from us_hep_funding.constants import CLEANED_DBS_PATH
class SuliStudentMapMaker:
def __init__(self):
geo_students... | 4,203 | 34.931624 | 126 | py |
houghnet | houghnet-master/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/main.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import sys
import os
sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
import src._init_paths
import os
import torch
import torch.utils.data
from src.lib.opts import opts
from src.... | 3,606 | 32.398148 | 78 | py |
houghnet | houghnet-master/src/test.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import sys
import os
sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
import src._init_paths
import os
import json
import cv2
import numpy as np
import time
from progress.bar impor... | 4,351 | 32.476923 | 79 | py |
houghnet | houghnet-master/src/_init_paths.py | import os.path as osp
import sys
def add_path(path):
if path not in sys.path:
sys.path.insert(0, path)
this_dir = osp.dirname(__file__)
# Add lib to PYTHONPATH
lib_path = osp.join(this_dir, 'lib')
add_path(lib_path)
| 231 | 16.846154 | 36 | py |
houghnet | houghnet-master/src/demo.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import src._init_paths
import os
import cv2
from src.lib.opts import opts
from src.lib.detectors.detector_factory import detector_factory
image_ext = ['jpg', 'jpeg', 'png', 'webp']
video_ext = ['mp4', 'mov',... | 1,694 | 28.736842 | 70 | py |
houghnet | houghnet-master/src/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/tools/merge_pascal_json.py | import json
# ANNOT_PATH = '/home/zxy/Datasets/VOC/annotations/'
ANNOT_PATH = 'voc/annotations/'
OUT_PATH = ANNOT_PATH
INPUT_FILES = ['pascal_train2012.json', 'pascal_val2012.json',
'pascal_train2007.json', 'pascal_val2007.json']
OUTPUT_FILE = 'pascal_trainval0712.json'
KEYS = ['images', 'type', 'annota... | 1,058 | 33.16129 | 62 | py |
houghnet | houghnet-master/src/tools/eval_coco_hp.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pycocotools.coco as coco
from pycocotools.cocoeval import COCOeval
import sys
import cv2
import numpy as np
import pickle
import os
this_dir = os.path.dirname(__file__)
ANN_PATH = this_dir + '../../data... | 795 | 24.677419 | 81 | py |
houghnet | houghnet-master/src/tools/eval_coco.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pycocotools.coco as coco
from pycocotools.cocoeval import COCOeval
import sys
import cv2
import numpy as np
import pickle
import os
this_dir = os.path.dirname(__file__)
ANN_PATH = this_dir + '../../data... | 669 | 22.928571 | 74 | py |
houghnet | houghnet-master/src/tools/reval.py | #!/usr/bin/env python
# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# Modified by Xingyi Zhou
# --------------------------------------------------------
# Reval = re-eval. Re-... | 2,377 | 29.101266 | 74 | py |
houghnet | houghnet-master/src/tools/convert_kitti_to_coco.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pickle
import json
import numpy as np
import cv2
DATA_PATH = '../../data/kitti/'
DEBUG = False
# VAL_PATH = DATA_PATH + 'training/label_val/'
import os
SPLITS = ['3dop', 'subcnn']
import src._init_paths... | 5,955 | 37.928105 | 81 | py |
houghnet | houghnet-master/src/tools/_init_paths.py | import os.path as osp
import sys
def add_path(path):
if path not in sys.path:
sys.path.insert(0, path)
this_dir = osp.dirname(__file__)
# Add lib to PYTHONPATH
lib_path = osp.join(this_dir, '../lib')
add_path(lib_path)
| 234 | 17.076923 | 39 | py |
houghnet | houghnet-master/src/tools/calc_coco_overlap.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pycocotools.coco as COCO
import cv2
import numpy as np
from pycocotools import mask as maskUtils
ANN_PATH = '../../data/coco/annotations/'
IMG_PATH = '../../data/coco/'
ANN_FILES = {'train': 'instances_t... | 10,869 | 32.653251 | 101 | py |
houghnet | houghnet-master/src/tools/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/tools/vis_pred.py | import pycocotools.coco as coco
from pycocotools.cocoeval import COCOeval
import sys
import cv2
import numpy as np
import pickle
IMG_PATH = '../../data/coco/val2017/'
ANN_PATH = '../../data/coco/annotations/instances_val2017.json'
DEBUG = True
def _coco_box_to_bbox(box):
bbox = np.array([box[0], box[1], box[0] + box... | 3,571 | 33.019048 | 82 | py |
houghnet | houghnet-master/src/tools/convert_hourglass_weight.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
MODEL_PATH = '../../models/ExtremeNet_500000.pkl'
OUT_PATH = '../../models/ExtremeNet_500000.pth'
import torch
state_dict = torch.load(MODEL_PATH)
key_map = {'t_heats': 'hm_t', 'l_heats': 'hm_l', 'b_heats': 'h... | 905 | 28.225806 | 69 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/setup.py | # --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
import os
from os.path import join as pjoin
import numpy as np
from dis... | 5,397 | 36.227586 | 91 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/tools/voc_eval_lib/datasets/voc_eval.py | # --------------------------------------------------------
# Fast/er R-CNN
# Licensed under The MIT License [see LICENSE for details]
# Written by Bharath Hariharan
# --------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
from __future__ import pr... | 6,802 | 30.49537 | 76 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/datasets/pascal_voc.py | # --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick and Xinlei Chen
# --------------------------------------------------------
from __future__ import absolute_import
from __future__ i... | 11,414 | 35.353503 | 85 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/datasets/imdb.py | # --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick and Xinlei Chen
# Modified by Xingyi Zhou
# --------------------------------------------------------
from __future__ import absolut... | 9,374 | 33.851301 | 74 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/datasets/ds_utils.py | # --------------------------------------------------------
# Fast/er R-CNN
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
from __future__ import print_... | 1,402 | 27.06 | 70 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/datasets/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/tools/voc_eval_lib/utils/visualization.py | # --------------------------------------------------------
# Tensorflow Faster R-CNN
# Licensed under The MIT License [see LICENSE for details]
# Written by Xinlei Chen
# --------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
from __future__ impor... | 4,016 | 43.633333 | 99 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/utils/timer.py | # --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
import time
class Timer(object):
"""A simple timer."""
def __i... | 948 | 27.757576 | 71 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/utils/blob.py | # --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
"""Blob helper functions."""
from __future__ import absolute_import
fro... | 1,504 | 30.354167 | 73 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/utils/__init__.py | # --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
| 248 | 34.571429 | 58 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/model/test.py | # --------------------------------------------------------
# Tensorflow Faster R-CNN
# Licensed under The MIT License [see LICENSE for details]
# Written by Xinlei Chen
# --------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
from __future__ impor... | 6,490 | 32.458763 | 99 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/model/bbox_transform.py | # --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
f... | 2,549 | 28.651163 | 77 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/model/nms_wrapper.py | # --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
f... | 787 | 31.833333 | 58 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/model/config.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import os.path as osp
import numpy as np
# `pip install easydict` if you don't have it
from easydict import EasyDict as edict
__C = edict()
# Consumers can get config by:
# from fast_rcnn_config im... | 11,010 | 27.378866 | 91 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/model/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/tools/voc_eval_lib/nms/py_cpu_nms.py | # --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
import numpy as np
def py_cpu_nms(dets, thresh):
"""Pure Python NM... | 1,051 | 25.974359 | 59 | py |
houghnet | houghnet-master/src/tools/voc_eval_lib/nms/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/lib/opts.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import os
import sys
class opts(object):
def __init__(self):
self.parser = argparse.ArgumentParser()
# basic experiment setting
# houghnet
self.parser.add_argument('--houghn... | 19,660 | 47.545679 | 115 | py |
houghnet | houghnet-master/src/lib/logger.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
# Code referenced from https://gist.github.com/gyglim/1f8dfb1b5c82627ae3efcfbbadb9f514
import os
import time
import sys
import torch
USE_TENSORBOARD = True
try:
import tensorboardX
print('Using tensorboardX... | 2,228 | 29.534247 | 86 | py |
houghnet | houghnet-master/src/lib/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/lib/external/setup.py | import numpy
from distutils.core import setup
from distutils.extension import Extension
from Cython.Build import cythonize
extensions = [
Extension(
"nms",
["nms.pyx"],
extra_compile_args=["-Wno-cpp", "-Wno-unused-function"]
)
]
setup(
name="coco",
ext_modules=cythonize(extens... | 368 | 18.421053 | 63 | py |
houghnet | houghnet-master/src/lib/external/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/lib/detectors/exdet.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import src._init_paths
import os
import cv2
import numpy as np
from progress.bar import Bar
import time
import torch
from src.lib.external.nms import soft_nms
from src.lib.models.decode import exct_decode, a... | 5,149 | 37.721805 | 80 | py |
houghnet | houghnet-master/src/lib/detectors/ctdet.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import cv2
import numpy as np
from progress.bar import Bar
import time
import torch
from src.lib.external.nms import soft_nms
from src.lib.models.decode import ctdet_decode
from src.lib.models.utils import fli... | 3,566 | 37.771739 | 78 | py |
houghnet | houghnet-master/src/lib/detectors/ddd.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import cv2
import numpy as np
from progress.bar import Bar
import time
import torch
from src.lib.external.nms import soft_nms
from src.lib.models.decode import ddd_decode
from src.lib.models.utils import flip_... | 4,110 | 37.783019 | 81 | py |
houghnet | houghnet-master/src/lib/detectors/multi_pose.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import cv2
import numpy as np
from progress.bar import Bar
import time
import torch
from src.lib.external.nms import soft_nms_39
from src.lib.models.decode import multi_pose_decode
from src.lib.models.utils im... | 3,850 | 37.89899 | 79 | py |
houghnet | houghnet-master/src/lib/detectors/detector_factory.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from .exdet import ExdetDetector
from .ddd import DddDetector
from .ctdet import CtdetDetector
from .multi_pose import MultiPoseDetector
from .ctseg import CtsegDetector
detector_factory = {
'exdet': ExdetDe... | 439 | 23.444444 | 41 | py |
houghnet | houghnet-master/src/lib/detectors/base_detector.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import cv2
import numpy as np
from progress.bar import Bar
import time
import torch
from src.lib.models.model import create_model, load_model
from src.lib.utils.image import get_affine_transform
from src.lib.u... | 5,206 | 34.910345 | 116 | py |
houghnet | houghnet-master/src/lib/detectors/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/lib/detectors/ctseg.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import cv2
import numpy as np
from progress.bar import Bar
import time
import torch
from pycocotools import mask as mask_utils
try:
from external.nms import soft_nms
except:
print('NMS not imported! If... | 3,141 | 38.275 | 127 | py |
houghnet | houghnet-master/src/lib/models/decode.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch
import torch.nn as nn
from .utils import _gather_feat, _tranpose_and_gather_feat
from detectron2.structures import Boxes # Each row is (x1, y1, x2, y2).
from detectron2.layers import paste_masks_i... | 24,358 | 36.824534 | 96 | py |
houghnet | houghnet-master/src/lib/models/losses.py | # ------------------------------------------------------------------------------
# Portions of this code are from
# CornerNet (https://github.com/princeton-vl/CornerNet)
# Copyright (c) 2018, University of Michigan
# Licensed under the BSD 3-Clause License
# -------------------------------------------------------------... | 12,420 | 35.212828 | 103 | py |
houghnet | houghnet-master/src/lib/models/data_parallel.py | import torch
from torch.nn.modules import Module
from torch.nn.parallel.scatter_gather import gather
from torch.nn.parallel.replicate import replicate
from torch.nn.parallel.parallel_apply import parallel_apply
from .scatter_gather import scatter_kwargs
class _DataParallel(Module):
r"""Implements data parallelis... | 5,176 | 39.445313 | 101 | py |
houghnet | houghnet-master/src/lib/models/utils.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch
import torch.nn as nn
def _sigmoid(x):
y = torch.clamp(x.sigmoid_(), min=1e-4, max=1-1e-4)
return y
def _gather_feat(feat, ind, mask=None):
dim = feat.size(2)
ind = ind.unsqueeze(2)... | 1,570 | 30.42 | 65 | py |
houghnet | houghnet-master/src/lib/models/model.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch
import torch.nn as nn
from .networks.msra_resnet import get_pose_net
from .networks.resnet_dcn import get_pose_net as get_pose_net_dcn
from .networks.large_hourglass import get_large_hourglass_net... | 3,752 | 37.295918 | 96 | py |
houghnet | houghnet-master/src/lib/models/scatter_gather.py | import torch
from torch.autograd import Variable
from torch.nn.parallel._functions import Scatter, Gather
def scatter(inputs, target_gpus, dim=0, chunk_sizes=None):
r"""
Slices variables into approximately equal chunks and
distributes them across given GPUs. Duplicates
references to objects that are n... | 1,535 | 38.384615 | 77 | py |
houghnet | houghnet-master/src/lib/models/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/lib/models/networks/resnet_dcn.py | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bin Xiao ([email protected])
# Modified by Dequan Wang and Xingyi Zhou
# ------------------------------------------------------------------------------
from __f... | 10,495 | 34.221477 | 80 | py |
houghnet | houghnet-master/src/lib/models/networks/houghnet_large_hourglass.py | # ------------------------------------------------------------------------------
# This code is base on
# CornerNet (https://github.com/princeton-vl/CornerNet)
# Copyright (c) 2018, University of Michigan
# Licensed under the BSD 3-Clause License
# ----------------------------------------------------------------------... | 11,454 | 34.030581 | 118 | py |
houghnet | houghnet-master/src/lib/models/networks/houghnet_dcn.py | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bin Xiao ([email protected])
# Modified by Dequan Wang and Xingyi Zhou
# ------------------------------------------------------------------------------
from __f... | 11,486 | 34.673913 | 112 | py |
houghnet | houghnet-master/src/lib/models/networks/pose_dla_dcn.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import math
import logging
import numpy as np
from os.path import join
import torch
from torch import nn
import torch.nn.functional as F
import torch.utils.model_zoo as model_zoo
from .DCNv2.dcn_v2 ... | 17,594 | 34.617409 | 106 | py |
houghnet | houghnet-master/src/lib/models/networks/msra_resnet.py | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bin Xiao ([email protected])
# Modified by Xingyi Zhou
# ------------------------------------------------------------------------------
from __future__ import a... | 10,167 | 35.185053 | 94 | py |
houghnet | houghnet-master/src/lib/models/networks/large_hourglass.py | # ------------------------------------------------------------------------------
# This code is base on
# CornerNet (https://github.com/princeton-vl/CornerNet)
# Copyright (c) 2018, University of Michigan
# Licensed under the BSD 3-Clause License
# ----------------------------------------------------------------------... | 9,942 | 32.033223 | 118 | py |
houghnet | houghnet-master/src/lib/models/networks/houghnet_resnet.py | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bin Xiao ([email protected])
# Modified by Xingyi Zhou
# ------------------------------------------------------------------------------
from __future__ import a... | 13,125 | 36.289773 | 113 | py |
houghnet | houghnet-master/src/lib/models/networks/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/lib/models/networks/pose_dla_dcn_hough.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import math
import logging
import numpy as np
from os.path import join
import torch
from torch import nn
import torch.nn.functional as F
import torch.utils.model_zoo as model_zoo
from src.lib.models.networks.... | 19,013 | 35.28626 | 111 | py |
houghnet | houghnet-master/src/lib/models/networks/dlav0.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import math
from os.path import join
import torch
from torch import nn
import torch.utils.model_zoo as model_zoo
import numpy as np
BatchNorm = nn.BatchNorm2d
d... | 22,681 | 34.003086 | 86 | py |
houghnet | houghnet-master/src/lib/models/networks/hough_module.py |
import torch
import torch.nn as nn
import numpy as np
PI = np.pi
class Hough(nn.Module):
def __init__(self, angle=90, R2_list=[4, 64, 256, 1024],
num_classes=80, region_num=9, vote_field_size=17,
voting_map_size_w=128, voting_map_size_h=128, model_v1=False):
super(Hough... | 4,491 | 34.370079 | 113 | py |
houghnet | houghnet-master/src/lib/models/networks/DCNv2/test.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import time
import torch
import torch.nn as nn
from torch.autograd import gradcheck
from dcn_v2 import dcn_v2_conv, DCNv2, DCN
from dcn_v2 import dcn_v2_pooling, DCNv2Pooling, DCNPooling
... | 8,506 | 30.391144 | 81 | py |
houghnet | houghnet-master/src/lib/models/networks/DCNv2/setup.py | #!/usr/bin/env python
import os
import glob
import torch
from torch.utils.cpp_extension import CUDA_HOME
from torch.utils.cpp_extension import CppExtension
from torch.utils.cpp_extension import CUDAExtension
from setuptools import find_packages
from setuptools import setup
requirements = ["torch", "torchvision"]
... | 1,977 | 28.969697 | 73 | py |
houghnet | houghnet-master/src/lib/models/networks/DCNv2/dcn_v2.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import _... | 12,081 | 38.743421 | 92 | py |
houghnet | houghnet-master/src/lib/models/networks/DCNv2/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/lib/trains/train_factory.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from .ctdet import CtdetTrainer
from .ddd import DddTrainer
from .exdet import ExdetTrainer
from .multi_pose import MultiPoseTrainer
from .ctseg import CtsegTrainer
train_factory = {
'exdet': ExdetTrainer,
... | 427 | 22.777778 | 40 | py |
houghnet | houghnet-master/src/lib/trains/exdet.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch
import numpy as np
import cv2
import sys
import time
from src.lib.utils.debugger import Debugger
from src.lib.models.data_parallel import DataParallel
from src.lib.models.losses import FocalLoss, R... | 3,645 | 41.395349 | 79 | py |
houghnet | houghnet-master/src/lib/trains/ctdet.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch
import numpy as np
from src.lib.models.losses import FocalLoss
from src.lib.models.losses import RegL1Loss, RegLoss, NormRegL1Loss, RegWeightedL1Loss
from src.lib.models.decode import ctdet_decode... | 5,574 | 41.234848 | 86 | py |
houghnet | houghnet-master/src/lib/trains/ddd.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch
import numpy as np
from src.lib.models.losses import FocalLoss, L1Loss, BinRotLoss
from src.lib.models.decode import ddd_decode
from src.lib.models.utils import _sigmoid
from src.lib.utils.debugge... | 6,967 | 43.954839 | 80 | py |
houghnet | houghnet-master/src/lib/trains/multi_pose.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch
import numpy as np
from src.lib.models.losses import FocalLoss, RegL1Loss, RegLoss, RegWeightedL1Loss
from src.lib.models.decode import multi_pose_decode
from src.lib.models.utils import _sigmoid,... | 7,300 | 44.347826 | 82 | py |
houghnet | houghnet-master/src/lib/trains/base_trainer.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import time
import torch
from progress.bar import Bar
from src.lib.models.data_parallel import DataParallel
from src.lib.utils.utils import AverageMeter
class ModleWithLoss(torch.nn.Module):
def __init__(se... | 3,929 | 32.02521 | 80 | py |
houghnet | houghnet-master/src/lib/trains/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/lib/trains/ctseg.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch
import numpy as np
from src.lib.models.losses import FocalLoss,SegLoss
from src.lib.models.losses import RegL1Loss, RegLoss, NormRegL1Loss, RegWeightedL1Loss
from src.lib.models.decode import ctde... | 6,685 | 47.100719 | 97 | py |
houghnet | houghnet-master/src/lib/datasets/dataset_factory.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from .sample.ddd import DddDataset
from .sample.exdet import EXDetDataset
from .sample.ctdet import CTDetDataset
from .sample.multi_pose import MultiPoseDataset
from .sample.ctseg import CTSegDataset
from src.... | 972 | 23.325 | 65 | py |
houghnet | houghnet-master/src/lib/datasets/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/lib/datasets/sample/exdet.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch.utils.data as data
import pycocotools.coco as coco
import numpy as np
import torch
import json
import cv2
import os
from utils.image import flip, color_aug
from utils.image import get_affine_transf... | 5,722 | 40.773723 | 81 | py |
houghnet | houghnet-master/src/lib/datasets/sample/ctdet.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch.utils.data as data
import numpy as np
import torch
import json
import cv2
import os
from src.lib.utils.image import flip, color_aug
from src.lib.utils.image import get_affine_transform, affine_tran... | 5,835 | 39.248276 | 88 | py |
houghnet | houghnet-master/src/lib/datasets/sample/ddd.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch.utils.data as data
import pycocotools.coco as coco
import numpy as np
import torch
import json
import cv2
import os
import math
from src.lib.utils.image import flip, color_aug
from src.lib.utils.im... | 6,825 | 38.918129 | 90 | py |
houghnet | houghnet-master/src/lib/datasets/sample/multi_pose.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch.utils.data as data
import numpy as np
import torch
import json
import cv2
import os
from utils.image import flip, color_aug
from utils.image import get_affine_transform, affine_transform
from utils... | 7,913 | 42.01087 | 81 | py |
houghnet | houghnet-master/src/lib/datasets/sample/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/lib/datasets/sample/ctseg.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch.utils.data as data
import numpy as np
import torch
import json
import cv2
import os
from src.lib.utils.image import flip, color_aug
from src.lib.utils.image import get_affine_transform, affine_tran... | 7,112 | 43.735849 | 97 | py |
houghnet | houghnet-master/src/lib/datasets/dataset/kitti.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch.utils.data as data
import pycocotools.coco as coco
import numpy as np
import torch
import json
import cv2
import os
import math
import torch.utils.data as data
class KITTI(data.Dataset):
num_c... | 3,060 | 33.011111 | 79 | py |
houghnet | houghnet-master/src/lib/datasets/dataset/coco_hp.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pycocotools.coco as coco
from pycocotools.cocoeval import COCOeval
import numpy as np
import json
import os
import torch.utils.data as data
class COCOHP(data.Dataset):
num_classes = 1
num_joints = ... | 4,244 | 34.375 | 80 | py |
houghnet | houghnet-master/src/lib/datasets/dataset/pascal.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pycocotools.coco as coco
import numpy as np
import torch
import json
import os
import torch.utils.data as data
class PascalVOC(data.Dataset):
num_classes = 20
default_resolution = [384, 384]
mean... | 3,032 | 35.542169 | 80 | py |
houghnet | houghnet-master/src/lib/datasets/dataset/__init__.py | 0 | 0 | 0 | py | |
houghnet | houghnet-master/src/lib/datasets/dataset/coco_seg.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pycocotools.coco as coco
from pycocotools.cocoeval import COCOeval
import numpy as np
import json
import os
import torch.utils.data as data
class COCOSEG(data.Dataset):
num_classes = 80
default_res... | 6,004 | 38.768212 | 82 | py |
houghnet | houghnet-master/src/lib/datasets/dataset/coco.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pycocotools.coco as coco
from pycocotools.cocoeval import COCOeval
import numpy as np
import json
import os
import torch.utils.data as data
class COCO(data.Dataset):
num_classes = 80
default_resolu... | 5,426 | 39.2 | 82 | py |
houghnet | houghnet-master/src/lib/utils/post_process.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from .image import transform_preds
from .ddd_utils import ddd2locrot
from .image import transform_preds, get_affine_transform
from pycocotools import mask as mask_utils
import cv2
def get_pr... | 5,149 | 34.273973 | 78 | py |
houghnet | houghnet-master/src/lib/utils/image.py | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bin Xiao ([email protected])
# Modified by Xingyi Zhou
# ------------------------------------------------------------------------------
from __future__ import a... | 7,720 | 31.305439 | 88 | py |
houghnet | houghnet-master/src/lib/utils/debugger.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import cv2
from .ddd_utils import compute_box_3d, project_to_image, draw_box_3d
class Debugger(object):
def __init__(self, ipynb=False, theme='black',
num_classes=-1, datas... | 21,612 | 37.872302 | 107 | py |
houghnet | houghnet-master/src/lib/utils/oracle_utils.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import numba
@numba.jit(nopython=True, nogil=True)
def gen_oracle_map(feat, ind, w, h):
# feat: B x maxN x featDim
# ind: B x maxN
batch_size = feat.shape[0]
max_objs = feat.shape[1]... | 1,317 | 30.380952 | 76 | py |
houghnet | houghnet-master/src/lib/utils/utils.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch
class AverageMeter(object):
"""Computes and stores the average and current value"""
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0... | 542 | 22.608696 | 59 | py |
houghnet | houghnet-master/src/lib/utils/__init__.py | 0 | 0 | 0 | py |
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