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STTS
STTS-main/MViT/slowfast/datasets/loader.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """Data loader.""" import itertools import numpy as np from functools import partial import torch from torch.utils.data._utils.collate import default_collate from torch.utils.data.distributed import DistributedSampler from ...
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STTS
STTS-main/MViT/slowfast/datasets/imagenet.py
# Copyright (c) Facebook, Inc. and its affiliates. import json import numpy as np import os import random import re import torch import torch.utils.data from PIL import Image from torchvision import transforms as transforms_tv import slowfast.datasets.transform as transform import slowfast.utils.logging as logging #...
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STTS
STTS-main/MViT/slowfast/datasets/rand_augment.py
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """ This implementation is based on https://github.com/rwightman/pytorch-image-models/blob/master/timm/data/auto_augment.py pulished under an Apache License 2.0. COMMENT FROM ORIGINAL: AutoAugment, RandAugment, and AugMix for PyTorch This code im...
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STTS
STTS-main/MViT/slowfast/datasets/build.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. from fvcore.common.registry import Registry DATASET_REGISTRY = Registry("DATASET") DATASET_REGISTRY.__doc__ = """ Registry for dataset. The registered object will be called with `obj(cfg, split)`. The call should return a ...
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STTS
STTS-main/MViT/slowfast/visualization/async_predictor.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. import atexit import numpy as np import queue import torch import torch.multiprocessing as mp import slowfast.utils.logging as logging from slowfast.datasets import cv2_transform from slowfast.visualization.predictor import...
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STTS
STTS-main/MViT/slowfast/visualization/demo_loader.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. import atexit import copy import queue import threading import time import cv2 import slowfast.utils.logging as logging from slowfast.visualization.utils import TaskInfo logger = logging.get_logger(__name__) class VideoM...
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STTS
STTS-main/MViT/slowfast/visualization/predictor.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. import queue import cv2 import torch from detectron2 import model_zoo from detectron2.config import get_cfg from detectron2.engine import DefaultPredictor import slowfast.utils.checkpoint as cu from slowfast.datasets import...
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STTS
STTS-main/MViT/slowfast/visualization/gradcam_utils.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. import matplotlib.pyplot as plt import torch import torch.nn.functional as F import slowfast.datasets.utils as data_utils from slowfast.visualization.utils import get_layer class GradCAM: """ GradCAM class helps c...
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STTS
STTS-main/MViT/slowfast/visualization/utils.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. import itertools import numpy as np import matplotlib.pyplot as plt import torch from sklearn.metrics import confusion_matrix import slowfast.utils.logging as logging from slowfast.datasets.utils import pack_pathway_output,...
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STTS
STTS-main/MViT/slowfast/visualization/prediction_vis.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. import numpy as np import torch import slowfast.datasets.utils as data_utils import slowfast.utils.logging as logging import slowfast.visualization.tensorboard_vis as tb from slowfast.utils.misc import get_class_names from ...
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STTS
STTS-main/MViT/slowfast/visualization/ava_demo_precomputed_boxes.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. import numpy as np import os import cv2 import torch import tqdm import slowfast.utils.checkpoint as cu import slowfast.utils.logging as logging from slowfast.datasets.ava_helper import parse_bboxes_file from slowfast.datas...
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STTS
STTS-main/MViT/slowfast/visualization/tensorboard_vis.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. import logging as log import math import os import matplotlib.pyplot as plt import torch from torch.utils.tensorboard import SummaryWriter from torchvision.utils import make_grid import slowfast.utils.logging as logging imp...
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STTS
STTS-main/MViT/slowfast/visualization/__init__.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
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STTS
STTS-main/MViT/slowfast/visualization/video_visualizer.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. import itertools import logging as log import numpy as np import matplotlib.pyplot as plt import torch from detectron2.utils.visualizer import Visualizer import slowfast.utils.logging as logging from slowfast.utils.misc imp...
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STTS
STTS-main/MViT/slowfast/utils/c2_model_loading.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """Caffe2 to PyTorch checkpoint name converting utility.""" import re def get_name_convert_func(): """ Get the function to convert Caffe2 layer names to PyTorch layer names. Returns: (func): function t...
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STTS
STTS-main/MViT/slowfast/utils/ava_eval_helper.py
# Copyright (c) Facebook, Inc. and its affiliates. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ...
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STTS
STTS-main/MViT/slowfast/utils/parser.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """Argument parser functions.""" import argparse import sys import slowfast.utils.checkpoint as cu from slowfast.config.defaults import get_cfg def parse_args(): """ Parse the following arguments for a default pa...
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STTS
STTS-main/MViT/slowfast/utils/multigrid.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """Helper functions for multigrid training.""" import numpy as np import slowfast.utils.logging as logging logger = logging.get_logger(__name__) class MultigridSchedule(object): """ This class defines multigrid ...
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STTS
STTS-main/MViT/slowfast/utils/checkpoint.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """Functions that handle saving and loading of checkpoints.""" import copy import numpy as np import os import pickle from collections import OrderedDict import torch import slowfast.utils.distributed as du import slowfast...
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STTS
STTS-main/MViT/slowfast/utils/benchmark.py
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved """ Functions for benchmarks. """ import numpy as np import pprint import torch import tqdm from fvcore.common.timer import Timer import slowfast.utils.logging as logging import slowfast.utils.misc as misc from slowfast.datasets import loader from...
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STTS
STTS-main/MViT/slowfast/utils/logging.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """Logging.""" import atexit import builtins import decimal import functools import logging import os import sys import simplejson import slowfast.utils.distributed as du from slowfast.utils.env import pathmgr def _suppr...
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STTS
STTS-main/MViT/slowfast/utils/misc.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. import json import logging import math import numpy as np import os from datetime import datetime import psutil import torch from fvcore.nn.activation_count import activation_count from fvcore.nn.flop_count import flop_count...
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STTS
STTS-main/MViT/slowfast/utils/distributed.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """Distributed helpers.""" import functools import logging import pickle import torch import torch.distributed as dist _LOCAL_PROCESS_GROUP = None def all_gather(tensors): """ All gathers the provided tensors fro...
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STTS
STTS-main/MViT/slowfast/utils/metrics.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """Functions for computing metrics.""" import torch def topks_correct(preds, labels, ks): """ Given the predictions, labels, and a list of top-k values, compute the number of correct predictions for each top-k...
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STTS
STTS-main/MViT/slowfast/utils/__init__.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
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STTS
STTS-main/MViT/slowfast/utils/weight_init_helper.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """Utility function for weight initialization""" import torch.nn as nn from fvcore.nn.weight_init import c2_msra_fill def init_weights(model, fc_init_std=0.01, zero_init_final_bn=True): """ Performs ResNet style w...
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STTS
STTS-main/MViT/slowfast/utils/multiprocessing.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """Multiprocessing helpers.""" import torch def run( local_rank, num_proc, func, init_method, shard_id, num_shards, backend, cfg, output_queue=None, ): """ Runs a function from ...
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STTS
STTS-main/MViT/slowfast/utils/lr_policy.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """Learning rate policy.""" import math def get_lr_at_epoch(cfg, cur_epoch): """ Retrieve the learning rate of the current epoch with the option to perform warm up in the beginning of the training stage. A...
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STTS
STTS-main/MViT/slowfast/utils/env.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """Set up Environment.""" from iopath.common.file_io import PathManagerFactory _ENV_SETUP_DONE = False pathmgr = PathManagerFactory.get(key="pyslowfast") checkpoint_pathmgr = PathManagerFactory.get(key="pyslowfast_checkpoi...
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STTS
STTS-main/MViT/slowfast/utils/bn_helper.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """bn helper.""" import itertools import torch @torch.no_grad() def compute_and_update_bn_stats(model, data_loader, num_batches=200): """ Compute and update the batch norm stats to make it more precise. During ...
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STTS
STTS-main/MViT/slowfast/utils/meters.py
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """Meters.""" import datetime import numpy as np import os from collections import defaultdict, deque import torch from fvcore.common.timer import Timer from sklearn.metrics import average_precision_score import slowfast.d...
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STTS
STTS-main/MViT/slowfast/utils/ava_evaluation/label_map_util.py
# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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STTS
STTS-main/MViT/slowfast/utils/ava_evaluation/np_box_list_ops.py
# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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STTS
STTS-main/MViT/slowfast/utils/ava_evaluation/per_image_evaluation.py
# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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STTS
STTS-main/MViT/slowfast/utils/ava_evaluation/standard_fields.py
# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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STTS
STTS-main/MViT/slowfast/utils/ava_evaluation/np_box_mask_list.py
# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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STTS
STTS-main/MViT/slowfast/utils/ava_evaluation/np_mask_ops.py
# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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STTS
STTS-main/MViT/slowfast/utils/ava_evaluation/np_box_list.py
# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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STTS
STTS-main/MViT/slowfast/utils/ava_evaluation/metrics.py
# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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STTS
STTS-main/MViT/slowfast/utils/ava_evaluation/__init__.py
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STTS
STTS-main/MViT/slowfast/utils/ava_evaluation/np_box_mask_list_ops.py
# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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STTS
STTS-main/MViT/slowfast/utils/ava_evaluation/object_detection_evaluation.py
# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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STTS
STTS-main/MViT/slowfast/utils/ava_evaluation/np_box_ops.py
# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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STTS
STTS-main/VideoSwin/setup.py
from setuptools import find_packages, setup def readme(): with open('README.md', encoding='utf-8') as f: content = f.read() return content version_file = 'mmaction/version.py' def get_version(): with open(version_file, 'r') as f: exec(compile(f.read(), version_file, 'exec')) return...
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STTS
STTS-main/VideoSwin/tools/test.py
import argparse import os import os.path as osp import warnings import mmcv import torch from mmcv import Config, DictAction from mmcv.cnn import fuse_conv_bn from mmcv.fileio.io import file_handlers from mmcv.parallel import MMDataParallel, MMDistributedDataParallel from mmcv.runner import get_dist_info, init_dist, l...
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STTS
STTS-main/VideoSwin/tools/__init__.py
from .analysis import * # noqa: F401, F403 from .data import * # noqa: F401, F403 from .deployment import * # noqa: F401, F403 from .misc import * # noqa: F401, F403
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STTS
STTS-main/VideoSwin/tools/train.py
import argparse import copy import os import os.path as osp import time import warnings import mmcv import torch from mmcv import Config, DictAction from mmcv.runner import get_dist_info, init_dist, set_random_seed, load_checkpoint from mmcv.utils import get_git_hash from mmaction import __version__ from mmaction.api...
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STTS
STTS-main/VideoSwin/tools/deployment/publish_model.py
import argparse import subprocess import torch def parse_args(): parser = argparse.ArgumentParser( description='Process a checkpoint to be published') parser.add_argument('in_file', help='input checkpoint filename') parser.add_argument('out_file', help='output checkpoint filename') args = par...
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STTS
STTS-main/VideoSwin/tools/deployment/pytorch2onnx.py
import argparse import mmcv import numpy as np import torch from mmcv.runner import load_checkpoint from mmaction.models import build_model try: import onnx import onnxruntime as rt except ImportError as e: raise ImportError(f'Please install onnx and onnxruntime first. {e}') try: from mmcv.onnx.symb...
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STTS
STTS-main/VideoSwin/tools/misc/clip_feature_extraction.py
import argparse import os import os.path as osp import warnings from datetime import datetime import mmcv import numpy as np import torch import torch.distributed as dist from mmcv import Config, DictAction from mmcv.cnn import fuse_conv_bn from mmcv.fileio.io import file_handlers from mmcv.parallel import MMDataParal...
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STTS
STTS-main/VideoSwin/tools/misc/flow_extraction.py
import argparse import os import os.path as osp import cv2 import numpy as np def flow_to_img(raw_flow, bound=20.): """Convert flow to gray image. Args: raw_flow (np.ndarray[float]): Estimated flow with the shape (w, h). bound (float): Bound for the flow-to-image normalization. Default: 20. ...
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STTS
STTS-main/VideoSwin/tools/misc/bsn_proposal_generation.py
import argparse import os import os.path as osp import mmcv import numpy as np import torch.multiprocessing as mp from mmaction.localization import (generate_bsp_feature, generate_candidate_proposals) def load_video_infos(ann_file): """Load the video annotations. Args: ...
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STTS
STTS-main/VideoSwin/tools/analysis/bench_processing.py
"""This file is for benchmark dataloading process. The command line to run this file is: $ python -m cProfile -o program.prof tools/analysis/bench_processing.py configs/task/method/[config filename] It use cProfile to record cpu running time and output to program.prof To visualize cProfile output program.prof, use Sn...
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STTS
STTS-main/VideoSwin/tools/analysis/eval_metric.py
import argparse import mmcv from mmcv import Config, DictAction from mmaction.datasets import build_dataset def parse_args(): parser = argparse.ArgumentParser(description='Evaluate metric of the ' 'results saved in pkl/yaml/json format') parser.add_argument('config', hel...
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STTS
STTS-main/VideoSwin/tools/analysis/benchmark.py
import argparse import time import torch from mmcv import Config from mmcv.cnn import fuse_conv_bn from mmcv.parallel import MMDataParallel from mmcv.runner.fp16_utils import wrap_fp16_model from mmaction.datasets import build_dataloader, build_dataset from mmaction.models import build_model def parse_args(): p...
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STTS
STTS-main/VideoSwin/tools/analysis/report_accuracy.py
import argparse from mmcv import load from scipy.special import softmax from mmaction.core.evaluation import (get_weighted_score, mean_class_accuracy, top_k_accuracy) def parse_args(): parser = argparse.ArgumentParser(description='Fusing multiple scores') parser.add_arg...
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STTS
STTS-main/VideoSwin/tools/analysis/get_flops.py
import argparse from mmcv import Config from mmaction.models import build_recognizer try: from mmcv.cnn import get_model_complexity_info except ImportError: raise ImportError('Please upgrade mmcv to >0.6.2') def parse_args(): parser = argparse.ArgumentParser(description='Train a recognizer') parser...
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STTS
STTS-main/VideoSwin/tools/analysis/print_config.py
import argparse from mmcv import Config, DictAction def parse_args(): parser = argparse.ArgumentParser(description='Print the whole config') parser.add_argument('config', help='config file path') parser.add_argument( '--options', nargs='+', action=DictAction, help='arguments in dict') args = ...
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STTS
STTS-main/VideoSwin/tools/analysis/analyze_logs.py
import argparse import json from collections import defaultdict import matplotlib.pyplot as plt import numpy as np import seaborn as sns def cal_train_time(log_dicts, args): for i, log_dict in enumerate(log_dicts): print(f'{"-" * 5}Analyze train time of {args.json_logs[i]}{"-" * 5}') all_times = ...
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STTS
STTS-main/VideoSwin/tools/analysis/report_map.py
import argparse import os import os.path as osp import mmcv import numpy as np from mmaction.core import ActivityNetLocalization args = None def cuhk17_top1(): """Assign label for each proposal with the cuhk17 result, which is the #2 entry in http://activity-net.org/challenges/2017/evaluation.html.""" ...
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STTS
STTS-main/VideoSwin/tools/analysis/check_videos.py
import argparse import os import warnings from functools import partial from multiprocessing import Manager, Pool, cpu_count import numpy as np from mmcv import Config, DictAction from tqdm import tqdm from mmaction.datasets import PIPELINES, build_dataset def parse_args(): parser = argparse.ArgumentParser(desc...
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STTS
STTS-main/VideoSwin/tools/data/build_rawframes.py
import argparse import glob import os import os.path as osp import sys import warnings from multiprocessing import Pool import mmcv import numpy as np def extract_frame(vid_item): """Generate optical flow using dense flow. Args: vid_item (list): Video item containing video full path, vid...
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STTS
STTS-main/VideoSwin/tools/data/parse_file_list.py
import csv import fnmatch import glob import json import os import os.path as osp def parse_directory(path, rgb_prefix='img_', flow_x_prefix='flow_x_', flow_y_prefix='flow_y_', level=1): """Parse directories holding extracted frames f...
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STTS
STTS-main/VideoSwin/tools/data/denormalize_proposal_file.py
import argparse import os.path as osp from tools.data.parse_file_list import parse_directory from mmaction.localization import load_localize_proposal_file def process_norm_proposal_file(norm_proposal_file, frame_dict): """Process the normalized proposal file and denormalize it. Args: norm_proposal_...
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STTS
STTS-main/VideoSwin/tools/data/extract_audio.py
import argparse import glob import os import os.path as osp from multiprocessing import Pool import mmcv def extract_audio_wav(line): """Extract the audio wave from video streams using FFMPEG.""" video_id, _ = osp.splitext(osp.basename(line)) video_dir = osp.dirname(line) video_rel_dir = osp.relpath(...
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STTS
STTS-main/VideoSwin/tools/data/anno_txt2json.py
import argparse import mmcv def parse_args(): parser = argparse.ArgumentParser( description='Convert txt annotation list to json') parser.add_argument( 'annofile', type=str, help='the txt annotation file to convert') parser.add_argument( '--format', type=str, defau...
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STTS
STTS-main/VideoSwin/tools/data/build_file_list.py
import argparse import glob import json import os.path as osp import random from mmcv.runner import set_random_seed from tools.data.anno_txt2json import lines2dictlist from tools.data.parse_file_list import (parse_directory, parse_diving48_splits, parse_hmdb51_split, ...
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STTS-main/VideoSwin/tools/data/resize_video.py
import argparse import glob import os import os.path as osp import sys from multiprocessing import Pool def resize_videos(vid_item): """Generate resized video cache. Args: vid_item (list): Video item containing video full path, video relative path. Returns: bool: Whether gene...
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STTS-main/VideoSwin/tools/data/build_videos.py
import argparse import glob import os import os.path as osp import sys from multiprocessing import Pool def encode_video(frame_dir_item): """Encode frames to video using ffmpeg. Args: frame_dir_item (list): Rawframe item containing raw frame directory full path, rawframe directory (short)...
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STTS-main/VideoSwin/tools/data/build_audio_features.py
import argparse import glob import os import os.path as osp import sys from multiprocessing import Pool import mmcv import numpy as np from scipy.io import wavfile try: import librosa import lws except ImportError: print('Please import librosa, lws first.') sys.path.append('..') SILENCE_THRESHOLD = 2 FM...
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STTS-main/VideoSwin/tools/data/gym/download.py
# This scripts is copied from # https://github.com/activitynet/ActivityNet/blob/master/Crawler/Kinetics/download.py # noqa: E501 # The code is licensed under the MIT licence. import argparse import os import ssl import subprocess import mmcv from joblib import Parallel, delayed ssl._create_default_https_context = ss...
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STTS-main/VideoSwin/tools/data/gym/generate_file_list.py
import os import os.path as osp annotation_root = '../../../data/gym/annotations' data_root = '../../../data/gym/subactions' frame_data_root = '../../../data/gym/subaction_frames' videos = os.listdir(data_root) videos = set(videos) train_file_org = osp.join(annotation_root, 'gym99_train_org.txt') val_file_org = osp....
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STTS-main/VideoSwin/tools/data/gym/trim_subaction.py
import os import os.path as osp import subprocess import mmcv data_root = '../../../data/gym' anno_root = f'{data_root}/annotations' event_anno_file = f'{anno_root}/event_annotation.json' event_root = f'{data_root}/events' subaction_root = f'{data_root}/subactions' events = os.listdir(event_root) events = set(event...
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STTS-main/VideoSwin/tools/data/gym/trim_event.py
import os import os.path as osp import subprocess import mmcv data_root = '../../../data/gym' video_root = f'{data_root}/videos' anno_root = f'{data_root}/annotations' anno_file = f'{anno_root}/annotation.json' event_anno_file = f'{anno_root}/event_annotation.json' event_root = f'{data_root}/events' videos = os.lis...
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STTS-main/VideoSwin/tools/data/hvu/parse_tag_list.py
import mmcv tag_list = '../../../data/hvu/annotations/hvu_categories.csv' lines = open(tag_list).readlines() lines = [x.strip().split(',') for x in lines[1:]] tag_categories = {} for line in lines: tag, category = line tag_categories.setdefault(category, []).append(tag) for k in tag_categories: tag_categ...
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STTS-main/VideoSwin/tools/data/hvu/download.py
# ------------------------------------------------------------------------------ # Adapted from https://github.com/activitynet/ActivityNet/ # Original licence: Copyright (c) Microsoft, under the MIT License. # ------------------------------------------------------------------------------ import argparse import glob im...
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STTS-main/VideoSwin/tools/data/hvu/generate_sub_file_list.py
import argparse import os.path as osp import mmcv def main(annotation_file, category): assert category in [ 'action', 'attribute', 'concept', 'event', 'object', 'scene' ] data = mmcv.load(annotation_file) basename = osp.basename(annotation_file) dirname = osp.dirname(annotation_file) ...
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STTS-main/VideoSwin/tools/data/hvu/generate_file_list.py
import argparse import fnmatch import glob import os import os.path as osp import mmcv annotation_root = '../../data/hvu/annotations' tag_file = 'hvu_tags.json' args = None def parse_directory(path, rgb_prefix='img_', flow_x_prefix='flow_x_', flow_y_prefix...
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STTS-main/VideoSwin/tools/data/activitynet/process_annotations.py
"""This file processes the annotation files and generates proper annotation files for localizers.""" import json import numpy as np def load_json(file): with open(file) as json_file: data = json.load(json_file) return data data_file = '../../../data/ActivityNet' info_file = f'{data_file}/video_...
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STTS-main/VideoSwin/tools/data/activitynet/download.py
# This scripts is copied from # https://github.com/activitynet/ActivityNet/blob/master/Crawler/Kinetics/download.py # noqa: E501 # The code is licensed under the MIT licence. import argparse import os import ssl import subprocess import mmcv from joblib import Parallel, delayed ssl._create_default_https_context = ss...
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STTS-main/VideoSwin/tools/data/activitynet/convert_proposal_format.py
"""This file converts the output proposal file of proposal generator (BSN, BMN) into the input proposal file of action classifier (Currently supports SSN and P-GCN, not including TSN, I3D etc.).""" import argparse import mmcv import numpy as np from mmaction.core import pairwise_temporal_iou def load_annotations(an...
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STTS-main/VideoSwin/tools/data/activitynet/generate_rawframes_filelist.py
import json import os import os.path as osp data_file = '../../../data/ActivityNet' video_list = f'{data_file}/video_info_new.csv' anno_file = f'{data_file}/anet_anno_action.json' rawframe_dir = f'{data_file}/rawframes' action_name_list = 'action_name.csv' train_rawframe_dir = rawframe_dir val_rawframe_dir = rawframe...
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STTS-main/VideoSwin/tools/data/activitynet/activitynet_feature_postprocessing.py
import argparse import multiprocessing import os import os.path as osp import numpy as np import scipy.interpolate from mmcv import dump, load args = None def parse_args(): parser = argparse.ArgumentParser(description='ANet Feature Prepare') parser.add_argument('--rgb', default='', help='rgb feature root') ...
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STTS-main/VideoSwin/tools/data/activitynet/tsn_feature_extraction.py
import argparse import os import os.path as osp import pickle import mmcv import numpy as np import torch from mmaction.datasets.pipelines import Compose from mmaction.models import build_model def parse_args(): parser = argparse.ArgumentParser(description='Extract TSN Feature') parser.add_argument('--data-...
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STTS-main/VideoSwin/tools/data/ava/download_videos_parallel.py
import argparse import os.path as osp import subprocess import mmcv from joblib import Parallel, delayed URL_PREFIX = 'https://s3.amazonaws.com/ava-dataset/trainval/' def download_video(video_url, output_dir, num_attempts=5): video_file = osp.basename(video_url) output_file = osp.join(output_dir, video_file...
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STTS-main/VideoSwin/tools/data/kinetics/download.py
# ------------------------------------------------------------------------------ # Adapted from https://github.com/activitynet/ActivityNet/ # Original licence: Copyright (c) Microsoft, under the MIT License. # ------------------------------------------------------------------------------ import argparse import glob imp...
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STTS-main/VideoSwin/tools/data/omnisource/trim_raw_video.py
import os import os.path as osp import sys from subprocess import check_output import mmcv def get_duration(vid_name): command = f'ffprobe -i {vid_name} 2>&1 | grep "Duration"' output = str(check_output(command, shell=True)) output = output.split(',')[0].split('Duration:')[1].strip() h, m, s = output...
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STTS-main/VideoSwin/mmcv_custom/__init__.py
# -*- coding: utf-8 -*-
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STTS-main/VideoSwin/mmcv_custom/runner/checkpoint.py
# Copyright (c) Open-MMLab. All rights reserved. import apex import os.path as osp import time from tempfile import TemporaryDirectory import torch from torch.optim import Optimizer import mmcv from mmcv.parallel import is_module_wrapper from mmcv.runner.checkpoint import weights_to_cpu, get_state_dict def save_chec...
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STTS-main/VideoSwin/mmcv_custom/runner/__init__.py
from .epoch_based_runner import EpochBasedRunnerAmp __all__ = [ 'EpochBasedRunnerAmp' ]
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STTS-main/VideoSwin/mmcv_custom/runner/epoch_based_runner.py
# Copyright (c) Open-MMLab. All rights reserved. import os.path as osp import platform import shutil import time import warnings import torch import mmcv from .checkpoint import save_checkpoint import apex from torch.optim import Optimizer import os class EpochBasedRunnerAmp(mmcv.runner.EpochBasedRunner): def _...
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STTS-main/VideoSwin/mmaction/version.py
# Copyright (c) Open-MMLab. All rights reserved. __version__ = '0.15.0' def parse_version_info(version_str): version_info = [] for x in version_str.split('.'): if x.isdigit(): version_info.append(int(x)) elif x.find('rc') != -1: patch_version = x.split('rc') ...
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STTS-main/VideoSwin/mmaction/__init__.py
import mmcv from mmcv import digit_version from .version import __version__ mmcv_minimum_version = '1.3.1' mmcv_maximum_version = '1.4.0' mmcv_version = digit_version(mmcv.__version__) assert (digit_version(mmcv_minimum_version) <= mmcv_version <= digit_version(mmcv_maximum_version)), \ f'MMCV=={mmcv.__v...
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STTS-main/VideoSwin/mmaction/apis/inference.py
import os import os.path as osp import re from operator import itemgetter import mmcv import torch from mmcv.parallel import collate, scatter from mmcv.runner import load_checkpoint from mmaction.core import OutputHook from mmaction.datasets.pipelines import Compose from mmaction.models import build_recognizer def ...
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STTS-main/VideoSwin/mmaction/apis/test.py
import os.path as osp import pickle import shutil import tempfile # TODO import test functions from mmcv and delete them from mmaction2 import warnings import mmcv import torch import torch.distributed as dist from mmcv.runner import get_dist_info try: from mmcv.engine import (single_gpu_test, multi_gpu_test, ...
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STTS
STTS-main/VideoSwin/mmaction/apis/__init__.py
from .inference import inference_recognizer, init_recognizer from .test import multi_gpu_test, single_gpu_test from .train import train_model __all__ = [ 'train_model', 'init_recognizer', 'inference_recognizer', 'multi_gpu_test', 'single_gpu_test' ]
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STTS-main/VideoSwin/mmaction/apis/train.py
import copy as cp import os.path as osp import torch from mmcv.parallel import MMDataParallel, MMDistributedDataParallel from mmcv.runner import (DistSamplerSeedHook, EpochBasedRunner, OptimizerHook, build_optimizer, get_dist_info) from mmcv.runner.hooks import Fp16OptimizerHook from ..core i...
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STTS-main/VideoSwin/mmaction/core/__init__.py
from .bbox import * # noqa: F401, F403 from .evaluation import * # noqa: F401, F403 from .hooks import * # noqa: F401, F403 from .optimizer import * # noqa: F401, F403 from .runner import * # noqa: F401, F403 from .scheduler import * # noqa: F401, F403
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STTS-main/VideoSwin/mmaction/core/scheduler/lr_updater.py
from mmcv.runner import HOOKS, LrUpdaterHook from mmcv.runner.hooks.lr_updater import annealing_cos @HOOKS.register_module() class TINLrUpdaterHook(LrUpdaterHook): def __init__(self, min_lr, **kwargs): self.min_lr = min_lr super().__init__(**kwargs) def get_warmup_lr(self, cur_iters): ...
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STTS-main/VideoSwin/mmaction/core/scheduler/__init__.py
from .lr_updater import TINLrUpdaterHook __all__ = ['TINLrUpdaterHook']
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