python_code stringlengths 0 4.04M | repo_name stringlengths 7 58 | file_path stringlengths 5 147 |
|---|---|---|
import torch.nn as nn
from models.backbone.sparseconv.models_sparseconv.modules.common import ConvType, NormType, get_norm, conv
from MinkowskiEngine import MinkowskiReLU
class BasicBlockBase(nn.Module):
expansion = 1
NORM_TYPE = NormType.BATCH_NORM
def __init__(self,
inplanes,
... | ContrastiveSceneContexts-main | downstream/votenet/models/backbone/sparseconv/models_sparseconv/modules/resnet_block.py |
import torch.nn as nn
import MinkowskiEngine as ME
from models.modules.common import ConvType, NormType
from models.modules.resnet_block import BasicBlock, Bottleneck
class SELayer(nn.Module):
def __init__(self, channel, reduction=16, D=-1):
# Global coords does not require coords_key
super(SELayer, self... | ContrastiveSceneContexts-main | downstream/votenet/models/backbone/sparseconv/models_sparseconv/modules/senet_block.py |
ContrastiveSceneContexts-main | downstream/votenet/models/backbone/sparseconv/models_sparseconv/modules/__init__.py | |
import collections
from enum import Enum
import torch.nn as nn
import MinkowskiEngine as ME
class NormType(Enum):
BATCH_NORM = 0
INSTANCE_NORM = 1
INSTANCE_BATCH_NORM = 2
def get_norm(norm_type, n_channels, D, bn_momentum=0.1):
if norm_type == NormType.BATCH_NORM:
return ME.MinkowskiBatchNorm(n_channel... | ContrastiveSceneContexts-main | downstream/votenet/models/backbone/sparseconv/models_sparseconv/modules/common.py |
ContrastiveSceneContexts-main | downstream/votenet/models/backbone/sparseconv/lib/__init__.py | |
from scipy.sparse import csr_matrix
import torch
class SparseMM(torch.autograd.Function):
"""
Sparse x dense matrix multiplication with autograd support.
Implementation by Soumith Chintala:
https://discuss.pytorch.org/t/
does-pytorch-support-autograd-on-sparse-matrix/6156/7
"""
def forward(self, matrix... | ContrastiveSceneContexts-main | downstream/votenet/models/backbone/sparseconv/lib/math_functions.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
''' Modified based on Ref: https://github.com/erikwijmans/Pointnet2_PyTorch '''
import torch
import torch.nn as nn
from typing import List, T... | ContrastiveSceneContexts-main | downstream/votenet/models/backbone/pointnet2/pytorch_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import glob
import os
from setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
this_dir = os.path.d... | ContrastiveSceneContexts-main | downstream/votenet/models/backbone/pointnet2/setup.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
''' Modified based on: https://github.com/erikwijmans/Pointnet2_PyTorch '''
from __future__ import (
division,
absolute_import,
w... | ContrastiveSceneContexts-main | downstream/votenet/models/backbone/pointnet2/pointnet2_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
''' Testing customized ops. '''
import torch
from torch.autograd import gradcheck
import numpy as np
import os
import sys
BASE_DIR = os.pat... | ContrastiveSceneContexts-main | downstream/votenet/models/backbone/pointnet2/pointnet2_test.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
''' Pointnet2 layers.
Modified based on: https://github.com/erikwijmans/Pointnet2_PyTorch
Extended with the following:
1. Uniform sampling in... | ContrastiveSceneContexts-main | downstream/votenet/models/backbone/pointnet2/pointnet2_modules.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import os
import sys
import logging
import numpy as np
import importlib
import warnings
import argparse
import torch.optim as ... | ContrastiveSceneContexts-main | downstream/votenet/lib/ddp_trainer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
#!/usr/bin/env python3
import os
import time
import torch
import signal
import pickle
import threading
import random
import functools
impor... | ContrastiveSceneContexts-main | downstream/votenet/lib/distributed.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
""" Utility functions for metric evaluation.
Author: Or Litany and Charles R. Qi
"""
import os
import sys
import torch
BASE_DIR = os.path.d... | ContrastiveSceneContexts-main | downstream/votenet/lib/utils/metric_util.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
""" Generic Code for Object Detection Evaluation
Input:
For each class:
For each image:
Predictions: box, score
... | ContrastiveSceneContexts-main | downstream/votenet/lib/utils/eval_det.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
""" Chamfer distance in Pytorch.
Author: Charles R. Qi
"""
import torch
import torch.nn as nn
import numpy as np
def huber_loss(error, del... | ContrastiveSceneContexts-main | downstream/votenet/lib/utils/nn_distance.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
""" Utility functions for processing point clouds.
Author: Charles R. Qi and Or Litany
"""
import os
import sys
BASE_DIR = os.path.dirname(... | ContrastiveSceneContexts-main | downstream/votenet/lib/utils/pc_util.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
from pc_util import bbox_corner_dist_measure
# boxes are axis aigned 2D boxes of shape (n,5) in FLOAT numbers with (x1,y1... | ContrastiveSceneContexts-main | downstream/votenet/lib/utils/nms.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
'''Code adapted from https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix'''
import os
import time
BASE_DIR = os.path.dirname(os.path.absp... | ContrastiveSceneContexts-main | downstream/votenet/lib/utils/tf_visualizer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import numpy as np
import trimesh
# color palette for nyu40 labels
def create_color_palette():
return [
(0, 0, 0),
... | ContrastiveSceneContexts-main | downstream/votenet/lib/utils/io3d.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import tensorflow as tf
import numpy as np
import scipy.misc
try:
from StringIO import StringIO # Python 2.7
except ImportError:
fr... | ContrastiveSceneContexts-main | downstream/votenet/lib/utils/tf_logger.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
""" Helper functions for calculating 2D and 3D bounding box IoU.
Collected and written by Charles R. Qi
Last modified: Jul 2019
"""
from __f... | ContrastiveSceneContexts-main | downstream/votenet/lib/utils/box_util.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import glob, os
import numpy as np
import cv2
import argparse
from plyfile import PlyData, PlyElement
# params
parser = argparse.ArgumentP... | ContrastiveSceneContexts-main | pretrain/scannet_pair/point_cloud_extractor.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import glob, os, sys
from SensorData import SensorData
# params
parser = argparse.ArgumentParser()
# data paths
parser.add... | ContrastiveSceneContexts-main | pretrain/scannet_pair/generage_list.py |
import os, struct
import numpy as np
import zlib
import imageio
import cv2
COMPRESSION_TYPE_COLOR = {-1:'unknown', 0:'raw', 1:'png', 2:'jpeg'}
COMPRESSION_TYPE_DEPTH = {-1:'unknown', 0:'raw_ushort', 1:'zlib_ushort', 2:'occi_ushort'}
class RGBDFrame():
def load(self, file_handle):
self.camera_to_world = np.asar... | ContrastiveSceneContexts-main | pretrain/scannet_pair/SensorData.py |
# Copyright 2014 Darsh Ranjan
#
# This file is part of python-plyfile.
#
# python-plyfile is free software: you can redistribute it and/or
# modify it under the terms of the GNU General Public License as
# published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any ... | ContrastiveSceneContexts-main | pretrain/scannet_pair/plyfile.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import copy
import numpy as np
import math
import glob, os
import argparse
import open3d as o3d
def make_open3d_point_cloud(xyz, color=None... | ContrastiveSceneContexts-main | pretrain/scannet_pair/compute_full_overlapping.py |
import argparse
import os, sys
from SensorData import SensorData
# params
parser = argparse.ArgumentParser()
# data paths
parser.add_argument('--filename', required=True, help='path to sens file to read')
parser.add_argument('--output_path', required=True, help='path to output folder')
parser.add_argument('--export_d... | ContrastiveSceneContexts-main | pretrain/scannet_pair/reader.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import sys
import os
import json
import logging
import torch
from omegaconf import OmegaConf
from easydict import EasyDict as edict
import ... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/ddp_train.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
import sys
import os
from model.pointnet2.pointnet2_mo... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/model/pointnet2backbone.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import model.res16unet as res16unet
import model.pointnet2backbone as pointnet2
MODELS = []
def add_models(module):
MODELS.extend([geta... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/model/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from model.resnet import ResNetBase, get_norm
from model.modules.common import ConvType, NormType, conv, conv_tr
from model.modules.resnet_bl... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/model/res16unet.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn as nn
import MinkowskiEngine as ME
from MinkowskiEngine import MinkowskiNetwork
from model.modules.common import ConvType,... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/model/resnet.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
''' Modified based on Ref: https://github.com/erikwijmans/Pointnet2_PyTorch '''
import torch
import torch.nn as nn
from typing import List, T... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/model/pointnet2/pytorch_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import glob
import os
from setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
this_dir = os.path.d... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/model/pointnet2/setup.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
''' Modified based on: https://github.com/erikwijmans/Pointnet2_PyTorch '''
from __future__ import (
division,
absolute_import,
w... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/model/pointnet2/pointnet2_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
''' Testing customized ops. '''
import torch
from torch.autograd import gradcheck
import numpy as np
import os
import sys
BASE_DIR = os.pat... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/model/pointnet2/pointnet2_test.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
''' Pointnet2 layers.
Modified based on: https://github.com/erikwijmans/Pointnet2_PyTorch
Extended with the following:
1. Uniform sampling in... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/model/pointnet2/pointnet2_modules.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn as nn
from model.modules.common import ConvType, NormType, get_norm, conv
from MinkowskiEngine import MinkowskiReLU
class B... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/model/modules/resnet_block.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree. | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/model/modules/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import collections
from enum import Enum
import MinkowskiEngine as ME
class NormType(Enum):
BATCH_NORM = 0
SPARSE_LAYER_NORM = 1
SPA... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/model/modules/common.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
import random
class Compose:
def __init__(self, transforms):
self.transforms = transforms
def __call__(self, ... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/transforms.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import time
class AverageMeter(object):
"""Computes and stores the average and current value"""
def __init__(self):
self.reset()
... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/timer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree. | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/__init__.py |
# Written by Chris Choy <chrischoy@ai.stanford.edu>
# Distributed under MIT License
import logging
import random
import torch
import torch.utils.data
import numpy as np
import glob
import os
import copy
from tqdm import tqdm
from scipy.linalg import expm, norm
from lib.io3d import write_triangle_mesh
import lib.transf... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/ddp_data_loaders.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import os.path as osp
import gc
import logging
import numpy as np
import json
from omegaconf import OmegaConf
import torch.nn as nn... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/ddp_trainer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
import trimesh
# color palette for nyu40 labels
def create_color_palette():
return [
(0, 0, 0),
(174, ... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/io3d.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
#!/usr/bin/env python3
"""Distributed helpers."""
import pickle
import time
import functools
import logging
import torch
import torch.dis... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/distributed.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
#!/usr/bin/env python3
"""Multiprocessing helpers."""
import multiprocessing as mp
import traceback
from lib.error_handler import ErrorHa... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/multiprocessing_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import torch
import numpy as np
class ShapeContext(object):
def __init__(self, r1=0.125, r2=2, nbins_xy=2, nbins_zy=2):
... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/shape_context.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
#!/usr/bin/env python3
"""Multiprocessing error handler."""
import os
import signal
import threading
class ChildException(Exception):
... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/error_handler.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
from torch import nn
class NCESoftmaxLoss(nn.Module):
def __init__(self):
super(NCESoftmaxLoss, self).__init__()
... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/criterion.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
from torch.utils.data.sampler import Sampler
import torch.distributed as dist
import math
class InfSampler(Sampler):
def __i... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/data_sampler.py |
# Evaluates semantic label task
# Input:
# - path to .txt prediction files
# - path to .txt ground truth files
# - output file to write results to
# Note that only the valid classes are used for evaluation,
# i.e., any ground truth label not in the valid label set
# is ignored in the evaluation.
#
# example usage... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/evaluation/evaluate_semantic_label.py |
# Evaluates semantic instance task
# Adapted from the CityScapes evaluation: https://github.com/mcordts/cityscapesScripts/tree/master/cityscapesscripts/evaluation
# Input:
# - path to .txt prediction files
# - path to .txt ground truth files
# - output file to write results to
# Each .txt prediction file look lik... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/evaluation/evaluate_semantic_instance.py |
import os, sys
import csv
try:
import numpy as np
except:
print("Failed to import numpy package.")
sys.exit(-1)
try:
import imageio
except:
print("Please install the module 'imageio' for image processing, e.g.")
print("pip install imageio")
sys.exit(-1)
# print an error message and quit
def... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/evaluation/scannet_benchmark_utils/util.py |
import os, sys
import json
try:
import numpy as np
except:
print("Failed to import numpy package.")
sys.exit(-1)
try:
from plyfile import PlyData, PlyElement
except:
print("Please install the module 'plyfile' for PLY i/o, e.g.")
print("pip install plyfile")
sys.exit(-1)
from . import util... | ContrastiveSceneContexts-main | pretrain/contrastive_scene_contexts/lib/evaluation/scannet_benchmark_utils/util_3d.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import argparse
import time
import torch
from mmcv import Config
from mmcv.parallel import MMDataParallel
from model.builder import build_estimator
def parse_args():
parser = argparse.ArgumentParser(description='MMSeg benchmark a model')
parser.add_argume... | CODD-main | benchmark_speed.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import argparse
import copy
import os
import os.path as osp
import time
import warnings
import mmcv
import torch
from mmcv.cnn.utils import revert_sync_batchnorm
from mmcv.runner import get_dist_info, init_dist
from mmcv.utils import Config, DictAction, get_git_has... | CODD-main | train.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import argparse
import os
import mmcv
import torch
from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
from mmcv.runner import (get_dist_info, init_dist, load_checkpoint, wrap_fp16_model)
from mmcv.utils import DictAction
from mmseg.datasets import ... | CODD-main | inference.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from .inference import single_gpu_inference, multi_gpu_inference
from .train import train_estimator
| CODD-main | apis/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import warnings
import torch
from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
from mmcv.runner import build_optimizer, build_runner
from mmseg.core import DistEvalHook, EvalHook
from mmseg.datasets import build_dataloader, build_dataset
from mmse... | CODD-main | apis/train.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import functools
import os.path as osp
import mmcv
import torch
import torch.distributed as dist
from mmcv.runner import get_dist_info
from mmcv.utils import print_log, mkdir_or_exist
from mmseg.utils import get_root_logger
from utils import RunningStatsWithBuffer... | CODD-main | apis/inference.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import math
import random
import cv2
import mmcv
import numpy as np
import torch
import torch.nn.functional as F
import torchvision.transforms as transforms
from mmseg.datasets import PIPELINES
@PIPELINES.register_module(force=True)
class RandomCrop(object):
... | CODD-main | datasets/transforms.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import copy
import os.path as osp
import re
import sys
import mmcv
import numpy as np
from mmcv.utils import print_log
from mmseg.datasets import DATASETS, CustomDataset
from mmseg.datasets.pipelines import Compose
from mmseg.utils import get_root_logger
from termi... | CODD-main | datasets/custom_stereo_mf.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from mmseg.datasets import DATASETS
from .scene_flow import SceneFlowMultiFrameDataset
@DATASETS.register_module()
class TartanAirMultiFrameDataset(SceneFlowMultiFrameDataset):
def __init__(self, **kwargs):
super(SceneFlowMultiFrameDataset, self).__in... | CODD-main | datasets/tartanair.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import copy
from mmcv.utils import print_log
from mmseg.datasets import DATASETS
from mmseg.utils import get_root_logger
from .custom_stereo_mf import CustomStereoMultiFrameDataset
@DATASETS.register_module()
class SceneFlowMultiFrameDataset(CustomStereoMultiFra... | CODD-main | datasets/scene_flow.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import re
import mmcv
# Requirements: Numpy as PIL/Pillow
import numpy as np
from PIL import Image
# sintel
# Check for endianness, based on Daniel Scharstein's optical flow code.
# Using little-endian architecture, these two should be equal.
TAG_FLOAT = 202021.25... | CODD-main | datasets/data_io.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from .formating import DefaultFormatBundle # NOQA
from .loading_stereo import * # NOQA
from .custom_stereo_mf import CustomStereoMultiFrameDataset # NOQA
from .kitti_depth import Kitti2015MultiFrameDataset, KittiDepthMultiFrameDataset # NOQA
from .scene_flow imp... | CODD-main | datasets/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from mmseg.datasets import DATASETS
from .scene_flow import SceneFlowMultiFrameDataset
@DATASETS.register_module()
class SintelMultiFrameDataset(SceneFlowMultiFrameDataset):
"""Person dataset.
In segmentation map annotation for ADE20K, 0 stands for backg... | CODD-main | datasets/sintel.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import os.path as osp
import mmcv
import numpy as np
from mmseg.datasets import PIPELINES
from mmseg.datasets.pipelines import LoadImageFromFile
from .data_io import disparity_read, flow_read, read_numpy_tartanair, read_numpy_tartanair_uint8, read_kitti_disp, \
... | CODD-main | datasets/loading_stereo.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from mmseg.datasets import DATASETS
from .scene_flow import SceneFlowMultiFrameDataset
@DATASETS.register_module()
class Kitti2015MultiFrameDataset(SceneFlowMultiFrameDataset):
def __init__(self, **kwargs):
super(SceneFlowMultiFrameDataset, self).__in... | CODD-main | datasets/kitti_depth.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import torch
import numpy as np
from mmcv.parallel import DataContainer as DC
from mmseg.datasets import PIPELINES
from mmseg.datasets.pipelines import to_tensor
@PIPELINES.register_module(force=True)
class DefaultFormatBundle(object):
"""Default formatting b... | CODD-main | datasets/formating.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import torch
from .warp import flow_warp
BF_DEFAULT = 1050 * 0.2 # baseline * focal length
__imagenet_stats = {'mean': [0.485, 0.456, 0.406],
'std': [0.229, 0.224, 0.225]}
def compute_valid_mask(gt_disp, meta, gt_semantic_seg=None, gt_flow_p... | CODD-main | utils/misc.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from .running_stats import *
from .metric import *
from .misc import *
from .warp import *
| CODD-main | utils/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import csv
import re
import numpy as np
class AverageMeter(object):
"""Computes and stores the average and current value"""
def __init__(self, name=' ', fmt=':f'):
self.name = name
self.fmt = fmt
self.reset()
def reset(self):... | CODD-main | utils/running_stats.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import numpy as np
import torch
EPSILON = 1e-8
def epe_metric(d_est, d_gt, mask, use_np=False):
d_est, d_gt = d_est[mask], d_gt[mask]
if use_np:
epe = np.mean(np.abs(d_est - d_gt))
else:
epe = torch.mean(torch.abs(d_est - d_gt))
r... | CODD-main | utils/metric.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import os
import re
from argparse import ArgumentParser
import numpy as np
from natsort import natsorted
def write_to_file(args, left_image, right_image, disparity, flow, disp_change, flow_occ, disp_frame2_in_frame1,
disp_occ, split):
fname ... | CODD-main | utils/generate_split_files.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import torch
import torch.nn.functional as F
def normalize_coords(grid):
"""Normalize coordinates of image scale to [-1, 1]
Args:
grid: [B, 2, H, W]
"""
assert grid.size(1) == 2
h, w = grid.size()[2:]
grid[:, 0, :, :] = 2 * (grid[:,... | CODD-main | utils/warp.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import os
import re
import time
from argparse import ArgumentParser
import cv2
import numpy as np
import open3d as o3d
from natsort import natsorted
from tqdm import tqdm
class InteractivePCDVisualizer(object):
def __call__(self, pcd_list):
o3d.visual... | CODD-main | utils/vis_point_cloud.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
_base_ = [
'models/consistent_online_depth_network.py', 'datasets/custom.py',
'default_runtime.py'
]
| CODD-main | configs/inference_config.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
_base_ = [
'models/codd.py', 'datasets/scene_flow.py',
'default_runtime.py', 'schedules/schedule_stereo.py'
] | CODD-main | configs/training_config.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
log_config = dict(
interval=50,
hooks=[
dict(type='TextLoggerHook'),
dict(type='TensorboardLoggerHook')
])
# yapf:enable
dist_params = dict(backend='nccl')
log_level = 'INFO'
load_from = None
resume_from = None
workflow = [('train', 1)]
c... | CODD-main | configs/default_runtime.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# pseudo camera parameters that doesn't really matter for inference
intrinsics = [640, 360, 1050, 1050]
calib = 210
disp_range = (1, 210)
depth_range = (calib / 210.0, calib / 1.0)
img_norm_cfg = dict(mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_... | CODD-main | configs/datasets/custom.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# dataset settings
dataset_type = "TartanAirMultiFrameDataset"
data_root = "PATH_TO_DATA"
train_split = "PATH_TO_SPLIT"
val_split = "PATH_TO_SPLIT"
test_split = "PATH_TO_SPLIT"
calib = 320 * 0.25 # from https://github.com/castacks/tartanair_tools/blob/master/data_... | CODD-main | configs/datasets/tartanair.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# dataset settings
dataset_type = "SceneFlowMultiFrameDataset"
data_root = "PATH_TO_STEREO_IMG"
disp_root = "PATH_TO_DISPARITY"
flow_root = "PATH_TO_FLOW"
disp_change_root = "PATH_TO_DISPARITY_CHANGE"
train_split = "PATH_TO_SPLIT"
val_split = "PATH_TO_SPLIT"
test_sp... | CODD-main | configs/datasets/scene_flow.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# dataset settings
dataset_type = "SintelMultiFrameDataset"
data_root = "PATH_TO_DATA"
flow_root = "PATH_TO_FLOW"
train_split = "PATH_TO_SPLIT"
val_split = "PATH_TO_SPLIT"
test_split = "PATH_TO_SPLIT"
calib = 688 * 0.01
disp_range = (1.0, 210.0)
depth_range = (cali... | CODD-main | configs/datasets/sintel.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# dataset settings
dataset_type = "KittiDepthMultiFrameDataset"
data_root = "PATH_TO_DATA"
train_split = "PATH_TO_SPLIT"
val_split = "PATH_TO_SPLIT"
test_split = "PATH_TO_SPLIT"
calib = 384.38 # from raw data calibration result
disp_range = (1.0, 210.0)
depth_rang... | CODD-main | configs/datasets/kitti_depth.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# dataset settings
dataset_type = "Kitti2015MultiFrameDataset"
data_root = "PATH_TO_DATA"
train_split = "PATH_TO_SPLIT"
val_split = "PATH_TO_SPLIT"
test_split = "PATH_TO_SPLIT"
calib = 384.38 # from raw data calibration result
disp_range = (1.0, 210.0)
depth_range... | CODD-main | configs/datasets/kitti_2015.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# model settings
max_disp = 320
iters = 1 # 16 for scene flow/KITTI, 1 for Sintel/TartanAir
motion_loss_weight = 1.0 # 0.5 for joint training tartan/KITTI, 1.0 for pretrain
freeze_stereo = True
freeze_motion = False
if freeze_stereo or freeze_motion:
find_un... | CODD-main | configs/models/stereo_motion.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# model settings
max_disp = 320
iters = 16 # 16 for scene flow/KITTI, 1 for Sintel/TartanAir
motion_loss_weight = 0.5 # 0.5 for joint training tartan/KITTI, 1.0 for pretrain
fusion_loss_weight = 1.0
wr_weight = 1.0
wf_weight = 1.0
freeze_stereo = False
freeze_mo... | CODD-main | configs/models/codd.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# model settings
max_disp = 320
freeze_stereo = False
freeze_motion = True
freeze_fusion = True
if freeze_stereo or freeze_motion or freeze_fusion:
find_unused_parameters = True
model = dict(
type='ConsistentOnlineDynamicDepth',
stereo=dict(
ty... | CODD-main | configs/models/stereo.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# optimizer
gpu_factor = 8
max_iter = 100000 // gpu_factor
optimizer = dict(type="Adam", lr=2e-4, weight_decay=0.00001)
optimizer_config = dict(grad_clip=dict(max_norm=1))
# learning policy
lr_config = dict(
policy="OneCycle",
max_lr=2e-4,
total_steps=ma... | CODD-main | configs/schedules/schedule_fusion.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# optimizer
optimizer = dict(type='Adam', lr=4e-4, betas=(0.9, 0.999))
optimizer_config = dict()
# learning policy
lr_config = dict(policy='MultiGamma', step=[225, 293, 315], gamma=[0.25, 0.4, 0.25])
# runtime settings
runner = dict(type='EpochBasedRunner', max_epo... | CODD-main | configs/schedules/schedule_stereo.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# optimizer
gpu_factor = 8
max_iter = 200000 // gpu_factor
optimizer = dict(type="Adam", lr=2e-4, weight_decay=0.00001)
optimizer_config = dict(grad_clip=dict(max_norm=1))
# learning policy
lr_config = dict(
policy="OneCycle",
max_lr=2e-4,
total_steps=ma... | CODD-main | configs/schedules/schedule_motion.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# optimizer
gpu_factor = 8
max_iter = 100000 // gpu_factor
optimizer = dict(type="Adam", lr=2e-5, weight_decay=1e-6)
optimizer_config = dict(grad_clip=dict(max_norm=1))
# learning policy
lr_config = dict(
policy="OneCycle",
max_lr=2e-5,
total_steps=max_i... | CODD-main | configs/schedules/schedule_motion_finetune.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# optimizer
gpu_factor = 8
max_iter = 50000 // gpu_factor
optimizer = dict(type="Adam", lr=2e-5, weight_decay=1e-6)
optimizer_config = dict(grad_clip=dict(max_norm=1))
# learning policy
lr_config = dict(
policy="OneCycle",
max_lr=2e-5,
total_steps=max_it... | CODD-main | configs/schedules/schedule_fusion_finetune.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# optimizer
gpu_factor = 8
max_iter = 100000 // gpu_factor
optimizer = dict(type="Adam", lr=2e-5, weight_decay=1e-6)
optimizer_config = dict(grad_clip=dict(max_norm=1))
# learning policy
lr_config = dict(
policy="OneCycle",
max_lr=2e-5,
total_steps=max_i... | CODD-main | configs/schedules/schedule_stereo_finetune.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import os.path as osp
from abc import ABCMeta
from collections import OrderedDict
import numpy as np
import torch
import torch.distributed as dist
from mmcv.runner import BaseModule, auto_fp16
from mmcv.utils import mkdir_or_exist
from mmseg.models.builder import M... | CODD-main | model/codd.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from .builder import *
from .codd import ConsistentOnlineDynamicDepth
from .fusion import *
from .losses import *
from .motion import *
from .stereo import *
from .lr_updater import *
__all__ = ["build_estimator"]
| CODD-main | model/__init__.py |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.