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# Copyright (c) Facebook, Inc. and its affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/Mask2Former/tree/main/mask2former/data/dataset_mappers/dataset_mapper.py
import copy
import logging
import numpy as np
import torch
from detectron2.config import configurable
from detectron2.data impo... | CutLER-main | videocutler/mask2former/data/dataset_mappers/coco_instance_new_baseline_dataset_mapper.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# Modified by XuDong from https://github.com/facebookresearch/Mask2Former/tree/main/mask2former/data/dataset_mappers/
import copy
import logging
import numpy as np
import pycocotools.mask as mask_util
import torch
from torch.nn import functional as F
from detectron2... | CutLER-main | videocutler/mask2former/data/dataset_mappers/mask_former_instance_dataset_mapper.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import os
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.data.datasets import load_sem_seg
ADE20K_SEM_SEG_FULL_CATEGORIES = [
{"name": "wall", "id": 2978, "trainId": 0},
{"name": "building, edifice", "id": 312, "trainId": 1},
... | CutLER-main | videocutler/mask2former/data/datasets/register_ade20k_full.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import os
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.data.datasets import load_sem_seg
MAPILLARY_VISTAS_SEM_SEG_CATEGORIES = [
{
"color": [165, 42, 42],
"instances": True,
"readable": "Bird",
"name"... | CutLER-main | videocutler/mask2former/data/datasets/register_mapillary_vistas.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from . import (
register_ade20k_full,
register_ade20k_panoptic,
register_coco_stuff_10k,
register_mapillary_vistas,
register_coco_panoptic_annos_semseg,
register_ade20k_instance,
register_mapillary_vistas_panoptic,
)
| CutLER-main | videocutler/mask2former/data/datasets/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import json
import os
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.utils.file_io import PathManager
MAPILLARY_VISTAS_SEM_SEG_CATEGORIES = [
{'color': [165, 42, 42],
'id': 1,
'isthing': 1,
'name': 'Bird',
'supercateg... | CutLER-main | videocutler/mask2former/data/datasets/register_mapillary_vistas_panoptic.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import json
import logging
import numpy as np
import os
from PIL import Image
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.data.datasets.coco import load_coco_json, register_coco_instances
from detectron2.utils.file_io import PathManager... | CutLER-main | videocutler/mask2former/data/datasets/register_ade20k_instance.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import json
import os
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.data.datasets import load_sem_seg
from detectron2.data.datasets.builtin_meta import COCO_CATEGORIES
from detectron2.utils.file_io import PathManager
_PREDEFINED_SPLITS_... | CutLER-main | videocutler/mask2former/data/datasets/register_coco_panoptic_annos_semseg.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import json
import os
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.utils.file_io import PathManager
ADE20K_150_CATEGORIES = [
{"color": [120, 120, 120], "id": 0, "isthing": 0, "name": "wall"},
{"color": [180, 120, 120], "id": 1,... | CutLER-main | videocutler/mask2former/data/datasets/register_ade20k_panoptic.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import os
from detectron2.data import DatasetCatalog, MetadataCatalog
from detectron2.data.datasets import load_sem_seg
COCO_CATEGORIES = [
{"color": [220, 20, 60], "isthing": 1, "id": 1, "name": "person"},
{"color": [119, 11, 32], "isthing": 1, "id": 2, "nam... | CutLER-main | videocutler/mask2former/data/datasets/register_coco_stuff_10k.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import os
from pathlib import Path
import numpy as np
import tqdm
from PIL import Image
def convert(input, output):
img = np.asarray(Image.open(input))
assert img.dtype == np.uint8
img = img - 1 # 0 (ignore... | CutLER-main | videocutler/datasets/prepare_ade20k_sem_seg.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import glob
import json
import os
from collections import Counter
import numpy as np
import tqdm
from panopticapi.utils import IdGenerator, save_json
from PIL import Image
import pycocotools.mask as mask_util
if __name_... | CutLER-main | videocutler/datasets/prepare_ade20k_ins_seg.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import glob
import json
import os
from collections import Counter
import numpy as np
import tqdm
from panopticapi.utils import IdGenerator, save_json
from PIL import Image
ADE20K_SEM_SEG_CATEGORIES = [
"wall",
"b... | CutLER-main | videocutler/datasets/prepare_ade20k_pan_seg.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import functools
import json
import multiprocessing as mp
import numpy as np
import os
import time
from fvcore.common.download import download
from panopticapi.utils import rgb2id
from PIL import Image
from detectron2.da... | CutLER-main | videocutler/datasets/prepare_coco_semantic_annos_from_panoptic_annos.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from: https://github.com/sukjunhwang/IFC/blob/master/projects/IFC/demo/predictor.py
import atexit
import bisect
import multiprocessing as mp
from collections import deque
import cv2
import torch
from visualizer import TrackVisualizer
from... | CutLER-main | videocutler/demo_video/predictor.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# copied from https://github.com/facebookresearch/detectron2/blob/main/detectron2/utils/colormap.py
"""
An awesome colormap for really neat visualizations.
Copied from Detectron, and removed gray colors.
"""
import numpy as np
import random
__all__ = ["colormap", ... | CutLER-main | videocutler/demo_video/colormap.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang
import argparse
import glob
import multiprocessing as mp
import os
# fmt: off
import sys
sys.path.insert(1, os.path.join(sys.path[0], '..'))
# fmt: on
import tempfile
import time
import cv2
import numpy as np
from torch.cuda.amp import ... | CutLER-main | videocutler/demo_video/demo.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from : https://github.com/sukjunhwang/IFC/blob/master/projects/IFC/demo/visualizer.py
import torch
import numpy as np
import matplotlib.colors as mplc
from detectron2.utils.visualizer import ColorMode, GenericMask, Visualizer, _create_text... | CutLER-main | videocutler/demo_video/visualizer.py |
# -*- coding: utf-8 -*-
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/Mask2Former/tree/main/mask2former_video
from detectron2.config import CfgNode as CN
def add_maskformer2_video_config(cfg):
# video data
# DataLoader
cfg.INPUT.SA... | CutLER-main | videocutler/mask2former_video/config.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from . import modeling
# config
from .config import add_maskformer2_video_config
# models
from .video_maskformer_model import VideoMaskFormer
# video
from .data_video import (
YTVISDatasetMapper,
YTVISEvaluator,
build_detection_train_loader,
build_de... | CutLER-main | videocutler/mask2former_video/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
import math
from typing import Tuple
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import configurable
from detectron2.data import MetadataCatalog
from detectron2.modeling import META_ARCH_REGISTRY, build... | CutLER-main | videocutler/mask2former_video/video_maskformer_model.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# Modified by Bowen Cheng from https://github.com/sukjunhwang/IFC
import itertools
import logging
import torch.utils.data
from detectron2.config import CfgNode, configurable
from detectron2.data.build import (
build_batch_data_loader,
load_proposals_into_data... | CutLER-main | videocutler/mask2former_video/data_video/build.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# Modified by Bowen Cheng from https://github.com/sukjunhwang/IFC
import contextlib
import copy
import io
import itertools
import json
import logging
import numpy as np
import os
from collections import OrderedDict
import pycocotools.mask as mask_util
import torch
fro... | CutLER-main | videocutler/mask2former_video/data_video/ytvis_eval.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# Modified by Bowen Cheng from https://github.com/sukjunhwang/IFC
import numpy as np
import logging
import sys
from fvcore.transforms.transform import (
HFlipTransform,
NoOpTransform,
VFlipTransform,
)
from PIL import Image
from detectron2.data import tra... | CutLER-main | videocutler/mask2former_video/data_video/augmentation.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# Modified by Bowen Cheng from https://github.com/sukjunhwang/IFC
from .dataset_mapper import YTVISDatasetMapper, CocoClipDatasetMapper
from .build import *
from .datasets import *
from .ytvis_eval import YTVISEvaluator
| CutLER-main | videocutler/mask2former_video/data_video/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# Modified by Bowen Cheng from https://github.com/sukjunhwang/IFC
import copy
import logging
import random
import numpy as np
from typing import List, Union
import torch
from detectron2.config import configurable
from detectron2.structures import (
BitMasks,
... | CutLER-main | videocutler/mask2former_video/data_video/dataset_mapper.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/Mask2Former/tree/main/mask2former_video
from . import builtin # ensure the builtin datasets are registered
__all__ = [k for k in globals().keys() if "builtin" not in k and not k.startswith("_")]
| CutLER-main | videocutler/mask2former_video/data_video/datasets/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/Mask2Former/tree/main/mask2former_video
import os
from .ytvis import (
register_ytvis_instances,
_get_ytvis_2019_instances_meta,
_get_ytvis_2021_instances_meta,
_get_imagenet_cls_agn... | CutLER-main | videocutler/mask2former_video/data_video/datasets/builtin.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/Mask2Former/tree/main/mask2former_video
import contextlib
import io
import json
import logging
import numpy as np
import os
import pycocotools.mask as mask_util
from fvcore.common.file_io import Pat... | CutLER-main | videocutler/mask2former_video/data_video/datasets/ytvis.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# Modified by Bowen Cheng from https://github.com/youtubevos/cocoapi
__author__ = 'ychfan'
import numpy as np
import datetime
import time
from collections import defaultdict
from pycocotools import mask as maskUtils
import copy
class YTVOSeval:
# Interface for e... | CutLER-main | videocutler/mask2former_video/data_video/datasets/ytvis_api/ytvoseval.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# Modified by Bowen Cheng from https://github.com/youtubevos/cocoapi
| CutLER-main | videocutler/mask2former_video/data_video/datasets/ytvis_api/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# Modified by Bowen Cheng from https://github.com/youtubevos/cocoapi
__author__ = 'ychfan'
# Interface for accessing the YouTubeVIS dataset.
# The following API functions are defined:
# YTVOS - YTVOS api class that loads YouTubeVIS annotation file and prepare ... | CutLER-main | videocutler/mask2former_video/data_video/datasets/ytvis_api/ytvos.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import logging
from contextlib import contextmanager
from functools import wraps
import torch
from torch.cuda.amp import autocast
__all__ = ["retry_if_cuda_oom"]
@contextmanager
def _ignore_torch_cuda_oom():
"""
A context which ignores CUDA OOM exception fr... | CutLER-main | videocutler/mask2former_video/utils/memory.py |
# Copyright (c) Facebook, Inc. and its affiliates.
| CutLER-main | videocutler/mask2former_video/utils/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# Modified by Bowen Cheng from https://github.com/facebookresearch/detr/blob/master/models/matcher.py
"""
Modules to compute the matching cost and solve the corresponding LSAP.
"""
import torch
import torch.nn.functional as F
from scipy.optimize import linear_sum_assig... | CutLER-main | videocutler/mask2former_video/modeling/matcher.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .transformer_decoder.video_mask2former_transformer_decoder import VideoMultiScaleMaskedTransformerDecoder
| CutLER-main | videocutler/mask2former_video/modeling/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# Modified by Bowen Cheng from https://github.com/facebookresearch/detr/blob/master/models/detr.py
"""
MaskFormer criterion.
"""
import logging
import torch
import torch.nn.functional as F
from torch import nn
from detectron2.utils.comm import get_world_size
from det... | CutLER-main | videocutler/mask2former_video/modeling/criterion.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# # Modified by Bowen Cheng from: https://github.com/facebookresearch/detr/blob/master/models/position_encoding.py
"""
Various positional encodings for the transformer.
"""
import math
import torch
from torch import nn
class PositionEmbeddingSine3D(nn.Module):
"... | CutLER-main | videocutler/mask2former_video/modeling/transformer_decoder/position_encoding.py |
# Copyright (c) Facebook, Inc. and its affiliates.
from .video_mask2former_transformer_decoder import VideoMultiScaleMaskedTransformerDecoder
| CutLER-main | videocutler/mask2former_video/modeling/transformer_decoder/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# Modified by Bowen Cheng from: https://github.com/facebookresearch/detr/blob/master/models/detr.py
import logging
import fvcore.nn.weight_init as weight_init
from typing import Optional
import torch
from torch import nn, Tensor
from torch.nn import functional as F
fr... | CutLER-main | videocutler/mask2former_video/modeling/transformer_decoder/video_mask2former_transformer_decoder.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from .train_loop import *
__all__ = [k for k in globals().keys() if not k.startswith("_")]
from .defaults import * | CutLER-main | videocutler/mask2former_video/engine/__init__.py |
# -*- coding: utf-8 -*-
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/engine/train_loop.py
import torch
from torch.nn.parallel import DataParallel, DistributedDataParallel
import numpy as np
import time
import to... | CutLER-main | videocutler/mask2former_video/engine/train_loop.py |
# -*- coding: utf-8 -*-
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/engine/defaults.py
"""
This file contains components with some default boilerplate logic user may need
in training / testing. They will not wor... | CutLER-main | videocutler/mask2former_video/engine/defaults.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import config
import engine
import modeling
import structures
import tools
import demo
# dataset loading
from . import data # register all new datasets
from data import datasets # register all new datasets
from solver import *
# from .data import register_all_i... | CutLER-main | cutler/__init__.py |
#!/usr/bin/env python
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/tools/train_net.py
"""
A main training script.
This scripts reads a given config file and runs the training or evaluation.
It is an entry point that is mad... | CutLER-main | cutler/train_net.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
import atexit
import bisect
import multiprocessing as mp
from collections import deque
import cv2
import torch
from detectron2.data import MetadataCatalog
import sys
sys.path.append('./')
from engine.defaults import DefaultPredictor
from detectron2.utils.video_visua... | CutLER-main | cutler/demo/predictor.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from demo import *
from predictor import *
__all__ = [k for k in globals().keys() if not k.startswith("_")] | CutLER-main | cutler/demo/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/demo/demo.py
import argparse
import glob
import multiprocessing as mp
import numpy as np
import os
import tempfile
import time
import warnings
import cv2
import tqdm
from detect... | CutLER-main | cutler/demo/demo.py |
#!/usr/bin/env python
# Copyright (c) Meta Platforms, Inc. and affiliates.
import os
import json
import tqdm
import torch
import datetime
import argparse
import pycocotools.mask as cocomask
from detectron2.utils.file_io import PathManager
INFO = {
"description": "ImageNet-1K: Self-train",
"url": "",
"vers... | CutLER-main | cutler/tools/get_self_training_ann.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from .boxes import pairwise_iou_max_scores
__all__ = [k for k in globals().keys() if not k.startswith("_")]
from detectron2.utils.env import fixup_module_metadata
fixup_module_metadata(__name__, globals(), __all__)
del fixup_module_metadata
| CutLER-main | cutler/structures/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/structures/boxes.py
import torch
def pairwise_iou_max_scores(boxes1: torch.Tensor, boxes2: torch.Tensor) -> torch.Tensor:
"""
Given two lists of boxes of size... | CutLER-main | cutler/structures/boxes.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from detectron2.config import CfgNode as CN
def add_cutler_config(cfg):
cfg.DATALOADER.COPY_PASTE = False
cfg.DATALOADER.COPY_PASTE_RATE = 0.0
cfg.DATALOADER.COPY_PASTE_MIN_RATIO = 0.5
cfg.DATALOADER.COPY_PASTE_MAX_RATIO = 1.0
cfg.DATALOADER.COP... | CutLER-main | cutler/config/cutler_config.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from .cutler_config import add_cutler_config | CutLER-main | cutler/config/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/solver/build.py
import copy
import itertools
import logging
from collections import defaultdict
from enum import Enum
from typing import Any, Callable, Dict, Iterable,... | CutLER-main | cutler/solver/build.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from .build import build_lr_scheduler, build_optimizer, get_default_optimizer_params
__all__ = [k for k in globals().keys() if not k.startswith("_")]
| CutLER-main | cutler/solver/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from .roi_heads import (
ROI_HEADS_REGISTRY,
ROIHeads,
CustomStandardROIHeads,
FastRCNNOutputLayers,
build_roi_heads,
)
from .roi_heads.custom_cascade_rcnn import CustomCascadeROIHeads
from .roi_heads.fast_rcnn import FastRCNNOutputLayers
from .m... | CutLER-main | cutler/modeling/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/modeling/meta_arch/build.py
import torch
from detectron2.utils.logger import _log_api_usage
from detectron2.utils.registry import Registry
META_ARCH_REGISTRY = Regis... | CutLER-main | cutler/modeling/meta_arch/build.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/modeling/meta_arch/rcnn.py
import logging
import numpy as np
from typing import Dict, List, Optional, Tuple
import torch
from torch import nn
from detectron2.config i... | CutLER-main | cutler/modeling/meta_arch/rcnn.py |
# -*- coding: utf-8 -*-
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/modeling/meta_arch/__init__.py
from .build import META_ARCH_REGISTRY, build_model # isort:skip
__all__ = list(globals().keys())
| CutLER-main | cutler/modeling/meta_arch/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/modeling/roi_heads/cascade_rcnn.py
from typing import List
import torch
from torch import nn
from torch.autograd.function import Function
from detectron2.config impor... | CutLER-main | cutler/modeling/roi_heads/custom_cascade_rcnn.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/modeling/roi_heads/fast_rcnn.py
import logging
from typing import Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import f... | CutLER-main | cutler/modeling/roi_heads/fast_rcnn.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from .roi_heads import (
ROI_HEADS_REGISTRY,
ROIHeads,
Res5ROIHeads,
CustomStandardROIHeads,
build_roi_heads,
select_foreground_proposals,
)
from .custom_cascade_rcnn import CustomCascadeROIHeads
from .fast_rcnn import FastRCNNOutputLayers
f... | CutLER-main | cutler/modeling/roi_heads/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/modeling/roi_heads/roi_heads.py
import inspect
import logging
import numpy as np
from typing import Dict, List, Optional, Tuple
import torch
from torch import nn
from... | CutLER-main | cutler/modeling/roi_heads/roi_heads.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from .coco_evaluation import COCOEvaluator | CutLER-main | cutler/evaluation/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/evaluation/coco_evaluation.py
# supports evaluation of object detection only, although the prediction contains both segmentation and detection results.
import contextl... | CutLER-main | cutler/evaluation/coco_evaluation.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/data/build.py
import itertools
import logging
import numpy as np
import operator
import pickle
from typing import Any, Callable, Dict, List, Optional, Union
import tor... | CutLER-main | cutler/data/build.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from . import datasets # ensure the builtin datasets are registered
from .detection_utils import * # isort:skip
from .build import (
build_batch_data_loader,
build_detection_train_loader,
build_detection_test_loader,
get_detection_dataset_dicts,... | CutLER-main | cutler/data/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/data/detection_utils.py
"""
Common data processing utilities that are used in a
typical object detection data pipeline.
"""
import logging
import numpy as np
from typi... | CutLER-main | cutler/data/detection_utils.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/data/dataset_mapper.py
import copy
import logging
import numpy as np
from typing import List, Optional, Union
import torch
from detectron2.config import configurable
... | CutLER-main | cutler/data/dataset_mapper.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/data/datasets/coco.py
import contextlib
import datetime
import io
import json
import logging
import numpy as np
import os
import shutil
import pycocotools.mask as mask... | CutLER-main | cutler/data/datasets/coco.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from .coco import load_coco_json, load_sem_seg, register_coco_instances, convert_to_coco_json
from .builtin import (
register_all_imagenet,
register_all_uvo,
register_all_coco_ca,
register_all_coco_semi,
register_all_lvis,
register_all_voc,
... | CutLER-main | cutler/data/datasets/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/data/datasets/builtin.py
"""
This file registers pre-defined datasets at hard-coded paths, and their metadata.
We hard-code metadata for common datasets. This will en... | CutLER-main | cutler/data/datasets/builtin.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/data/datasets/builtin_meta.py
"""
Note:
For your custom dataset, there is no need to hard-code metadata anywhere in the code.
For example, for COCO-format dataset, met... | CutLER-main | cutler/data/datasets/builtin_meta.py |
# -*- coding: utf-8 -*-
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/data/transforms/augmentation_impl.py
"""
Implement many useful :class:`Augmentation`.
"""
import numpy as np
import sys
from typing import Tupl... | CutLER-main | cutler/data/transforms/augmentation_impl.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/data/transforms/__init__.py
from fvcore.transforms.transform import *
from .transform import *
from detectron2.data.transforms.augmentation import *
from .augmentation... | CutLER-main | cutler/data/transforms/__init__.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/data/transforms/transform.py
"""
See "Data Augmentation" tutorial for an overview of the system:
https://detectron2.readthedocs.io/tutorials/augmentation.html
"""
imp... | CutLER-main | cutler/data/transforms/transform.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
from .train_loop import *
__all__ = [k for k in globals().keys() if not k.startswith("_")]
from .defaults import * | CutLER-main | cutler/engine/__init__.py |
# -*- coding: utf-8 -*-
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/engine/train_loop.py and https://github.com/NVlabs/FreeSOLO/tree/main/freesolo/engine/trainer.py
import torch
from torch.nn.parallel import Dat... | CutLER-main | cutler/engine/train_loop.py |
# -*- coding: utf-8 -*-
# Copyright (c) Meta Platforms, Inc. and affiliates.
# Modified by XuDong Wang from https://github.com/facebookresearch/detectron2/blob/main/detectron2/engine/defaults.py
"""
This file contains components with some default boilerplate logic user may need
in training / testing. They will not wor... | CutLER-main | cutler/engine/defaults.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# copied from https://github.com/facebookresearch/detectron2/blob/main/detectron2/utils/colormap.py
"""
An awesome colormap for really neat visualizations.
Copied from Detectron, and removed gray colors.
"""
import numpy as np
import random
__all__ = ["colormap", "r... | CutLER-main | maskcut/colormap.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# modfied by Xudong Wang based on https://github.com/lucasb-eyer/pydensecrf/blob/master/pydensecrf/tests/test_dcrf.py and third_party/TokenCut
import numpy as np
import pydensecrf.densecrf as dcrf
import pydensecrf.utils as utils
import torch
import torch.nn.functio... | CutLER-main | maskcut/crf.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
#!/usr/bin/env python3
import os
import sys
sys.path.append('../')
import argparse
import numpy as np
from tqdm import tqdm
import re
import datetime
import PIL
import PIL.Image as Image
import torch
import torch.nn.functional as F
from torchvision import transforms... | CutLER-main | maskcut/maskcut_with_submitit.py |
"""
download pretrained weights to ./weights
wget https://dl.fbaipublicfiles.com/dino/dino_vitbase8_pretrain/dino_vitbase8_pretrain.pth
wget https://dl.fbaipublicfiles.com/dino/dino_deitsmall8_300ep_pretrain/dino_deitsmall8_300ep_pretrain.pth
"""
import sys
sys.path.append("maskcut")
import numpy as np
import PIL.Ima... | CutLER-main | maskcut/predict.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
"""
A script to run multinode training with submitit.
"""
import sys
sys.path.append('./')
sys.path.append('./MaskCut')
sys.path.append('./third_party')
import argparse
import os
import uuid
from pathlib import Path
import maskcut_with_submitit as main_func
impor... | CutLER-main | maskcut/run_with_submitit_maskcut_array.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# merge all ImageNet annotation files as a single one.
import os
import json
import argparse
if __name__ == "__main__":
# load model arguments
parser = argparse.ArgumentParser(description='Merge json files')
parser.add_argument('--base-dir', type=str,
... | CutLER-main | maskcut/merge_jsons.py |
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
import os
import sys
sys.path.append('../')
import argparse
import numpy as np
from tqdm import tqdm
import re
import datetime
import PIL
import PIL.Image as Image
import torch
import torch.nn.functional as F
from torchvision import transforms... | CutLER-main | maskcut/maskcut.py |
# Copyright (c) Meta Platforms, Inc. and affiliates.
"""
Copied from Dino repo. https://github.com/facebookresearch/dino
Mostly copy-paste from timm library.
https://github.com/rwightman/pytorch-image-models/blob/master/timm/models/vision_transformer.py
"""
import math
from functools import partial
import torch
impor... | CutLER-main | maskcut/dino.py |
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
import os
import sys
sys.path.append('../')
import argparse
import numpy as np
import PIL.Image as Image
import torch
from torchvision import transforms
from scipy import ndimage
from detectron2.utils.colormap import random_color
import dino ... | CutLER-main | maskcut/demo.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
from torch.nn import functional as F
from torchvision.utils import make_grid, save_image
import numpy as np
import argparse
import os
import sys
sys.path.append('vae_submodule')
from utils.helpers import FormatterNoDuplicate, chec... | amortized-optimization-tutorial-main | code/evaluate_amortization_speed_vae.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import torch
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('bmh')
params = {
"text.usetex" : True,
"font.family" : "serif",
"font.serif" : ["Computer Modern Serif"]
}
plt.rcParams.update(params)
import os
import time
def evaluate_amor... | amortized-optimization-tutorial-main | code/evaluate_amortization_speed_function.py |
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
import torch
from torch import nn
import numpy as np
import os
import matplotlib.pyplot as plt
plt.style.use('bmh')
import sys
from IPython.core import ultratb
sys.excepthook = ultratb.FormattedTB(
mode='Plain', color_scheme='Neutral', c... | amortized-optimization-tutorial-main | code/train-sphere.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import torch
import argparse
import os
import sys
import pickle as pkl
import shutil
from omegaconf import OmegaConf
from collections import namedtuple
import dmc2gym
import matplotlib.pyplot as plt
plt.style.use('bmh')
from... | amortized-optimization-tutorial-main | code/evaluate_amortization_speed_control.py |
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
import jax
import jax.numpy as jnp
import os
plt.rcParams.update({
"text.usetex": True,
"font.family": "serif",
"font.sans-serif": ["Computer Modern Rom... | amortized-optimization-tutorial-main | code/figures/ctrl.py |
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
import jax
import jax.numpy as jnp
import os
plt.rcParams.update({
"text.usetex": True,
"font.family": "serif",
"font.sans-serif": ["Computer Modern Rom... | amortized-optimization-tutorial-main | code/figures/smoothed-loss.py |
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
import jax
import jax.numpy as jnp
import shutil
import os
plt.rcParams.update({
"text.usetex": True,
"font.family": "serif",
"font.sans-serif": ["Comp... | amortized-optimization-tutorial-main | code/figures/maxent-animation.py |
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
import jax
import jax.numpy as jnp
import os
plt.rcParams.update({
"text.usetex": True,
"font.family": "serif",
"font.sans-serif": ["Computer Modern Rom... | amortized-optimization-tutorial-main | code/figures/main-example.py |
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
import jax
import jax.numpy as jnp
import os
plt.rcParams.update({
"text.usetex": True,
"font.family": "serif",
"font.sans-serif": ["Computer Modern Rom... | amortized-optimization-tutorial-main | code/figures/fixed-point.py |
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
import jax
import jax.numpy as jnp
import os
plt.rcParams.update({
"text.usetex": True,
"font.family": "serif",
"font.sans-serif": ["Computer Modern Rom... | amortized-optimization-tutorial-main | code/figures/loss-comp.py |
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
import jax
import jax.numpy as jnp
import os
plt.rcParams.update({
"text.usetex": True,
"font.family": "serif",
"font.sans-serif": ["Computer Modern Rom... | amortized-optimization-tutorial-main | code/figures/imaml.py |
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
import jax
import jax.numpy as jnp
import os
plt.rcParams.update({
"text.usetex": True,
"font.family": "serif",
"font.sans-serif": ["Computer Modern Rom... | amortized-optimization-tutorial-main | code/figures/maxent.py |
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