python_code stringlengths 0 992k | repo_name stringlengths 8 46 | file_path stringlengths 5 162 |
|---|---|---|
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
# import alphaction._custom_cuda_ext as _C
class _ROIPool3d(Function):
@staticmethod
def forward(ctx, input, roi, output_size, spatial_scale):
ctx.... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/layers/roi_pool_3d.py |
import torch
from .roi_align_3d import ROIAlign3d
# from .roi_align_3d import roi_align_3d
from .roi_pool_3d import ROIPool3d
from .roi_pool_3d import roi_pool_3d
from .batch_norm import FrozenBatchNorm1d, FrozenBatchNorm2d, FrozenBatchNorm3d
from .sigmoid_focal_loss import SigmoidFocalLoss
from .softmax_focal_loss im... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/layers/__init__.py |
import torch
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
# import alphaction._custom_cuda_ext as _C
class _SigmoidFocalLoss(Function):
@staticmethod
def forward(ctx, logits, targets, gamma, alpha):
ctx.save_for_backward(logits, targ... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/layers/sigmoid_focal_loss.py |
import torch
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
# import alphaction._custom_cuda_ext as _C
from torchvision.ops import roi_align
# class _ROIAlign3d(Function):
# @staticmethod
# def forward(... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/layers/roi_align_3d.py |
import torch
from torch import nn
class _FrozenBatchNorm(nn.Module):
def __init__(self, num_features, eps=1e-5, affine=True, track_running_stats=True):
super(_FrozenBatchNorm, self).__init__()
self.num_features = num_features
self.eps = eps
self.affine = affine
self.track_r... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/layers/batch_norm.py |
from collections import defaultdict
class MemoryPool(object):
def __init__(self):
self.cache = defaultdict(dict)
def update(self, update_info):
for movie_id, feature_per_movie in update_info.items():
self.cache[movie_id].update(feature_per_movie)
def update_list(self, update_i... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/structures/memory_pool.py |
InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/structures/__init__.py | |
# Modified from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/maskrcnn_benchmark/structures/bounding_box.py
import torch
import pdb
# transpose
FLIP_LEFT_RIGHT = 0
FLIP_TOP_BOTTOM = 1
class BoxList(object):
"""
This class represents a set of bounding boxes.
The bounding boxes are repr... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/structures/bounding_box.py |
from .defaults import _C as cfg
| InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/config/__init__.py |
"""Centralized catalog of paths."""
import os
class DatasetCatalog(object):
DATA_DIR = ""
DATASETS = {
"ava_video_train_v2.2": {
"video_root": "/mnt/cache/xingsen/ava_dataset/AVA/clips/trainval/",
"ann_file": "/mnt/lustre/share_data/xingsen/ava_dataset/AVA/annotations/ava_trai... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/config/paths_catalog.py |
from yacs.config import CfgNode as CN
# -----------------------------------------------------------------------------
# Config definition
# -----------------------------------------------------------------------------
_C = CN()
_C.MODEL = CN()
_C.MODEL.WEIGHT = ""
# ------------------------------------------------... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/config/defaults.py |
import bisect
import copy
import torch.utils.data
from alphaction.utils.comm import get_world_size
from alphaction.utils.IA_helper import has_object
import alphaction.config.paths_catalog as paths_catalog
from . import datasets as D
from . import samplers
from .collate_batch import BatchCollator
from .transforms imp... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/build.py |
from .build import make_data_loader
| InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/__init__.py |
import math
def batch_different_videos(videos, size_divisible=0):
'''
:param videos: a list of video tensors
:param size_divisible: output_size(width and height) should be divisble by this param
:return: batched videos as a single tensor
'''
assert isinstance(videos, (tuple, list))
max_siz... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/collate_batch.py |
import bisect
from torch.utils.data.dataset import ConcatDataset as _ConcatDataset
class ConcatDataset(_ConcatDataset):
"""
Same as torch.utils.dataset.dataset.ConcatDataset, but exposes an extra
method for querying the sizes of the image
"""
def get_idxs(self, idx):
dataset_idx = bisect... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/concat_dataset.py |
import os
import torch.utils.data as data
import time
import torch
import numpy as np
from alphaction.structures.bounding_box import BoxList
from collections import defaultdict
from alphaction.utils.video_decode import av_decode_video
import json
# This is used to avoid pytorch issuse #13246
class NpInfoDict(object):... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/ava.py |
from .concat_dataset import ConcatDataset
from .ava import AVAVideoDataset
__all__ = ["ConcatDataset", "AVAVideoDataset"] | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/__init__.py |
from alphaction.dataset import datasets
from .ava import ava_evaluation
def evaluate(dataset, predictions, output_folder, **kwargs):
"""evaluate dataset using different methods based on dataset type.
Args:
dataset: Dataset object
predictions(list[BoxList]): each item in the list represents th... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/__init__.py |
import numpy as np
import tempfile
import os
from pprint import pformat
import csv
import time
from collections import defaultdict
from .pascal_evaluation import object_detection_evaluation, standard_fields
def do_ava_evaluation(dataset, predictions, output_folder, logger):
logger.info("Preparing results for AVA ... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/ava/ava_eval.py |
import logging
from .ava_eval import do_ava_evaluation
def ava_evaluation(dataset, predictions, output_folder, **_):
logger = logging.getLogger("alphaction.inference")
logger.info("performing ava evaluation.")
return do_ava_evaluation(
dataset=dataset,
predictions=predictions,
outp... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/ava/__init__.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... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/ava/pascal_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... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/ava/pascal_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... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/ava/pascal_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... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/ava/pascal_evaluation/np_box_mask_list.py |
InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/ava/pascal_evaluation/__init__.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... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/ava/pascal_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... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/ava/pascal_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... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/ava/pascal_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... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/ava/pascal_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... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/ava/pascal_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... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/ava/pascal_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... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/datasets/evaluation/ava/pascal_evaluation/object_detection_evaluation.py |
from . import video_transforms as T
from . import object_transforms as OT
def build_transforms(cfg, is_train=True):
# build transforms for training of testing
if is_train:
min_size = cfg.INPUT.MIN_SIZE_TRAIN
max_size = cfg.INPUT.MAX_SIZE_TRAIN
color_jitter = cfg.INPUT.COLOR_JITTER
... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/transforms/build.py |
from .build import build_transforms, build_object_transforms | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/transforms/__init__.py |
import torch
import random
import numpy as np
import cv2
cv2.setNumThreads(0)
class Compose(object):
# Compose different kinds of video transforms into one.
def __init__(self, transforms):
self.transforms = transforms
def __call__(self, videos, target):
transform_randoms = {}
for... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/transforms/video_transforms.py |
class Compose(object):
# Class used to compose different kinds of object transforms
def __init__(self, transforms):
self.transforms = transforms
def __call__(self, object_boxes, transform_randoms):
#should reuse the random varaible in video transforms
for t in self.transforms:
... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/transforms/object_transforms.py |
from .distributed import DistributedSampler
from .grouped_batch_sampler import GroupedBatchSampler
from .iteration_based_batch_sampler import IterationBasedBatchSampler
__all__ = ["DistributedSampler", "GroupedBatchSampler", "IterationBasedBatchSampler"]
| InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/samplers/__init__.py |
# Modified based on https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/maskrcnn_benchmark/data/samplers/grouped_batch_sampler.py
import itertools
import torch
from torch.utils.data.sampler import BatchSampler
from torch.utils.data.sampler import Sampler
class GroupedBatchSampler(BatchSampler):
""... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/samplers/grouped_batch_sampler.py |
# Code is copy-pasted exactly as in torch.utils.dataset.distributed.
# FIXME remove this once c10d fixes the bug it has
import math
import torch
import torch.distributed as dist
from torch.utils.data.sampler import Sampler
class DistributedSampler(Sampler):
"""Sampler that restricts dataset loading to a subset of... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/samplers/distributed.py |
# Adopted from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/maskrcnn_benchmark/data/samplers/iteration_based_batch_sampler.py
from torch.utils.data.sampler import BatchSampler
class IterationBasedBatchSampler(BatchSampler):
"""
Wraps a BatchSampler, resampling from it until
a specifi... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/dataset/samplers/iteration_based_batch_sampler.py |
# Adopted from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/maskrcnn_benchmark/utils/metric_logger.py
from collections import defaultdict
from collections import deque
import torch
class SmoothedValue(object):
"""Track a series of values and provide access to smoothed values over a
wind... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/utils/metric_logger.py |
# Modified from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/maskrcnn_benchmark/utils/checkpoint.py
import logging
import os
import torch
from alphaction.utils.model_serialization import load_state_dict
from alphaction.utils.c2_model_loading import load_c2_format
from alphaction.structures.memor... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/utils/checkpoint.py |
# Modified from https://github.com/facebookresearch/detectron2/blob/master/detectron2/utils/comm.py
"""
This file contains primitives for multi-gpu communication.
This is useful when doing distributed training.
"""
import pickle
import torch
import torch.distributed as dist
import functools
def get_world_size():
... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/utils/comm.py |
import logging
import torch
import pickle
from collections import OrderedDict
def _rename_weights(weights, weight_map):
logger = logging.getLogger(__name__)
logger.info("Remapping C2 weights")
max_c2_key_size = max([len(k) for k in weight_map.values()])
new_weights = OrderedDict()
for k in weight_... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/utils/c2_model_loading.py |
# Adopted from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/maskrcnn_benchmark/utils/registry.py
def _register_generic(module_dict, module_name, module):
assert module_name not in module_dict
module_dict[module_name] = module
class Registry(dict):
'''
A helper class for managing... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/utils/registry.py |
import av
import io
import decord
def av_decode_video(video_path):
with av.open(video_path) as container:
frames = []
for frame in container.decode(video=0):
frames.append(frame.to_rgb().to_ndarray())
return frames | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/utils/video_decode.py |
InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/utils/__init__.py | |
# Modified from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/maskrcnn_benchmark/utils/logger.py
import logging
import os
import sys
import time
def setup_logger(name, save_dir, distributed_rank, filename=None):
logger = logging.getLogger(name)
logger.setLevel(logging.DEBUG)
logger.pr... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/utils/logger.py |
# Modified from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/maskrcnn_benchmark/utils/model_serialization.py
from collections import OrderedDict
import logging
import torch
def align_and_update_state_dicts(model_state_dict, loaded_state_dict, no_head):
"""
Strategy: suppose that the mod... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/utils/model_serialization.py |
import itertools
def _block_set(ia_blocks):
if len(ia_blocks) > 0 and isinstance(ia_blocks[0], list):
ia_blocks = list(itertools.chain.from_iterable(ia_blocks))
return ia_blocks
def has_person(ia_config):
ia_blocks = _block_set(ia_config.I_BLOCK_LIST)
return (ia_config.ACTIVE and 'P' in ia_blo... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/utils/IA_helper.py |
import torch
import random
import numpy as np
def set_seed(seed, rank, world_size):
rng = random.Random(seed)
seed_per_rank = [rng.randint(0, 2**32-1) for _ in range(world_size)]
cur_seed = seed_per_rank[rank]
random.seed(cur_seed)
torch.manual_seed(cur_seed)
torch.cuda.manual_seed(cur_seed)
... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/utils/random_seed.py |
import torch
from .lr_scheduler import WarmupMultiStepLR, HalfPeriodCosStepLR
import torch.nn as nn
from alphaction.modeling.roi_heads.action_head.IA_structure import IAStructure
def make_optimizer(cfg, model):
params = []
bn_param_set = set()
transformer_param_set = set()
for name, module in model.... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/solver/build.py |
# Modified from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/maskrcnn_benchmark/solver/lr_scheduler.py
from bisect import bisect_right
import torch
import math
class WarmupMultiStepLR(torch.optim.lr_scheduler._LRScheduler):
def __init__(
self,
optimizer,
milestones,
... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/solver/lr_scheduler.py |
from .build import make_optimizer
from .build import make_lr_scheduler
from .lr_scheduler import WarmupMultiStepLR
| InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/solver/__init__.py |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import torch
import torch.nn as nn
from alphaction.layers import FrozenBatchNorm3d
class NLBlock(nn.Module):
def __init__(self, dim_in, dim_out, dim_inner, nl_cfg, group=False):
super(NLBlock, sel... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/nonlocal_block.py |
import torch.nn as nn
from alphaction.modeling.nonlocal_block import NLBlock
from alphaction.layers import FrozenBatchNorm3d
class Conv3dBN(nn.Module):
def __init__(self, cfg, dim_in, dim_out, kernels, stride, padding, dilation=1, init_weight=None):
super(Conv3dBN, self).__init__()
self.conv = nn.... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/common_blocks.py |
import torch
from torch import nn
from alphaction.layers import ROIAlign3d, ROIPool3d
class Pooler3d(nn.Module):
def __init__(self, output_size, scale, sampling_ratio=None, pooler_type='align3d'):
super(Pooler3d, self).__init__()
if pooler_type == 'align3d':
assert sampling_ratio is n... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/poolers.py |
from alphaction.utils.registry import Registry
BACKBONES = Registry()
ROI_ACTION_FEATURE_EXTRACTORS = Registry()
ROI_ACTION_PREDICTORS = Registry()
INTERACTION_AGGREGATION_STRUCTURES = Registry() | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/registry.py |
InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/__init__.py | |
"""
Miscellaneous utility functions
"""
import torch
from alphaction.structures.bounding_box import BoxList
def cat(tensors, dim=0):
"""
Efficient version of torch.cat that avoids a copy if there is only a single element in a list
"""
assert isinstance(tensors, (list, tuple))
if len(tensors) == 1... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/utils.py |
from .action_detector import build_detection_model | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/detector/__init__.py |
from torch import nn
from ..backbone import build_backbone
from ..roi_heads.roi_heads_3d import build_3d_roi_heads
class ActionDetector(nn.Module):
def __init__(self, cfg):
super(ActionDetector, self).__init__()
self.backbone = build_backbone(cfg)
self.roi_heads = build_3d_roi_heads(cfg, ... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/detector/action_detector.py |
InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/roi_heads/__init__.py | |
import torch
from .action_head.action_head import build_roi_action_head
class Combined3dROIHeads(torch.nn.ModuleDict):
def __init__(self, cfg, heads):
super(Combined3dROIHeads, self).__init__(heads)
self.cfg = cfg.clone()
def forward(self, slow_features, fast_features, boxes, objects=None, e... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/roi_heads/roi_heads_3d.py |
InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/roi_heads/action_head/__init__.py | |
import torch
from torch import nn
from torch.nn import functional as F
from alphaction.modeling import registry
from alphaction.modeling.poolers import make_3d_pooler
from alphaction.modeling.roi_heads.action_head.IA_structure import make_ia_structure
from alphaction.modeling.utils import cat, pad_sequence, prepare_po... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/roi_heads/action_head/roi_action_feature_extractor.py |
import torch
from .roi_action_feature_extractor import make_roi_action_feature_extractor
from .roi_action_predictors import make_roi_action_predictor
from .inference import make_roi_action_post_processor
from .loss import make_roi_action_loss_evaluator
from .metric import make_roi_action_accuracy_evaluator
from alphac... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/roi_heads/action_head/action_head.py |
import torch
from alphaction.modeling.utils import cat
class ActionAccuracyComputation(object):
def __init__(self, num_pose, num_object, num_person):
self.num_pose = num_pose
self.num_object = num_object
self.num_person = num_person
def logic_iou(self, pred, label):
device = p... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/roi_heads/action_head/metric.py |
import torch
from alphaction.layers import SigmoidFocalLoss, SoftmaxFocalLoss
from alphaction.modeling.utils import cat
class ActionLossComputation(object):
def __init__(self, cfg):
self.proposal_per_clip = cfg.MODEL.ROI_ACTION_HEAD.PROPOSAL_PER_CLIP
self.num_pose = cfg.MODEL.ROI_ACTION_HEAD.NUM_P... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/roi_heads/action_head/loss.py |
from torch import nn
from alphaction.modeling import registry
@registry.ROI_ACTION_PREDICTORS.register("FCPredictor")
class FCPredictor(nn.Module):
def __init__(self, config, dim_in):
super(FCPredictor, self).__init__()
num_classes = config.MODEL.ROI_ACTION_HEAD.NUM_CLASSES
dropout_rate ... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/roi_heads/action_head/roi_action_predictors.py |
import torch
from torch import nn
import torch.nn.functional as F
from alphaction.structures.bounding_box import BoxList
class PostProcessor(nn.Module):
def __init__(self, pose_action_num):
super(PostProcessor, self).__init__()
self.pose_action_num = pose_action_num
def forward(self, x, boxe... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/roi_heads/action_head/inference.py |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import math
import torch
import torch.nn as nn
from alphaction.modeling import registry
from alphaction.utils.IA_helper import has_memory, has_person, has_object
class InteractionBlock(nn.Module):
def __i... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/roi_heads/action_head/IA_structure.py |
from alphaction.modeling import registry
from . import slowfast, i3d
@registry.BACKBONES.register("Slowfast-Resnet50")
@registry.BACKBONES.register("Slowfast-Resnet101")
def build_slowfast_resnet_backbone(cfg):
model = slowfast.SlowFast(cfg)
return model
@registry.BACKBONES.register("I3D-Resnet50")
@registry.... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/backbone/backbone.py |
from .backbone import build_backbone | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/backbone/__init__.py |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import torch
import torch.nn as nn
from alphaction.modeling.common_blocks import ResNLBlock
from alphaction.layers import FrozenBatchNorm3d
def get_slow_model_cfg(cfg):
backbone_strs = cfg.MODEL.BACKBONE.... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/backbone/slowfast.py |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import torch.nn as nn
from alphaction.layers import FrozenBatchNorm3d
from alphaction.modeling.common_blocks import ResNLBlock
def get_model_cfg(cfg):
backbone_strs = cfg.MODEL.BACKBONE.CONV_BODY.split('-... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/modeling/backbone/i3d.py |
InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/engine/__init__.py | |
# modified from https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/maskrcnn_benchmark/engine/inference.py
import logging
import os
import torch
from tqdm import tqdm
import time
import datetime
from alphaction.dataset.datasets.evaluation import evaluate
from alphaction.utils.comm import get_rank, is_m... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/engine/inference.py |
import datetime
import logging
import time
import torch
from alphaction.utils.metric_logger import MetricLogger
from alphaction.engine.inference import inference
from alphaction.utils.comm import synchronize, reduce_dict, all_gather
from alphaction.structures.memory_pool import MemoryPool
def do_train(
mode... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/alphaction/engine/trainer.py |
from operator import is_
from alphaction.dataset.transforms import video_transforms as T
# from rand_aug import *
from dataclasses import dataclass
import numpy as np
from data.RandomAugmentBBox import *
import cv2
cv2.setNumThreads(0)
@dataclass
class TransformsCfg:
MIN_SIZE_TRAIN: int = 256
MAX_SIZE_TRAIN... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/data/transforms.py |
"""
Modified from https://github.com/google-research/ssl_detection/blob/master/detection/utils/augmentation.py.
"""
import copy
from unittest import result
import cv2
import mmcv
import numpy as np
from PIL import Image, ImageEnhance, ImageOps
from mmcv.image.colorspace import bgr2rgb, rgb2bgr
from mmdet.core.mask imp... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/data/rand_aug.py |
# Copyright 2020 Google LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/data/RandomAugmentBBox.py |
import numpy as np
import logging
import tempfile
import os
from pprint import pformat
import csv
import time
from collections import defaultdict
from alphaction.dataset.datasets.evaluation.ava.pascal_evaluation import object_detection_evaluation, standard_fields
def do_ava_evaluation(dataset, predictions, output_f... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/data/ava_eval.py |
import os
from venv import main
import torch.utils.data as data
import time
import torch
import numpy as np
import sys
import torch.nn.functional as F
sys.path.append('/mnt/cache/xingsen/xingsen2/VideoMAE_ava')
from alphaction.structures.bounding_box import BoxList
# from transforms import build_transforms
from collect... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/data/ava.py |
InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/data/__init__.py | |
"""
Adapted code from:
@inproceedings{hara3dcnns,
author={Kensho Hara and Hirokatsu Kataoka and Yutaka Satoh},
title={Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
pa... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/data/spatial_transforms.py |
# Copyright 2018 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 applicab... | InternVideo-main | Downstream/Spatial-Temporal-Action-Localization/data/augmentations.py |
# python imports
import argparse
import os
import time
import datetime
from pprint import pprint
# torch imports
import torch
import torch.nn as nn
import torch.utils.data
# for visualization
from torch.utils.tensorboard import SummaryWriter
# our code
from libs.core import load_config
from libs.datasets import make_... | InternVideo-main | Downstream/Temporal-Action-Localization/train_eval.py |
import yaml
DEFAULTS = {
# random seed for reproducibility, a large number is preferred
"init_rand_seed": 1234567891,
# dataset loader, specify the dataset here
"dataset_name": "epic",
"devices": ['cuda:0'], # default: single gpu
"train_split": ('training', ),
"val_split": ('validation', )... | InternVideo-main | Downstream/Temporal-Action-Localization/libs/core/config.py |
from .config import load_default_config, load_config
__all__ = ['load_default_config', 'load_config']
| InternVideo-main | Downstream/Temporal-Action-Localization/libs/core/__init__.py |
import os
import json
import numpy as np
import torch
from torch.utils.data import Dataset
from torch.nn import functional as F
from .datasets import register_dataset
from .data_utils import truncate_feats
import pickle
import io
from petrel_client.client import Client
client = Client()
@register_dataset("thumos")... | InternVideo-main | Downstream/Temporal-Action-Localization/libs/datasets/thumos14.py |
import os
import torch
from .data_utils import trivial_batch_collator, worker_init_reset_seed
datasets = {}
def register_dataset(name):
def decorator(cls):
datasets[name] = cls
return cls
return decorator
def make_dataset(name, is_training, split, **kwargs):
"""
A simple dataset builder
... | InternVideo-main | Downstream/Temporal-Action-Localization/libs/datasets/datasets.py |
from .data_utils import worker_init_reset_seed, truncate_feats
from .datasets import make_dataset, make_data_loader
from . import thumos14, anet # other datasets go here
__all__ = ['worker_init_reset_seed', 'truncate_feats',
'make_dataset', 'make_data_loader']
| InternVideo-main | Downstream/Temporal-Action-Localization/libs/datasets/__init__.py |
import os
import copy
import random
import numpy as np
import random
import torch
def trivial_batch_collator(batch):
"""
A batch collator that does nothing
"""
return batch
def worker_init_reset_seed(worker_id):
"""
Reset random seed for each worker
"""
seed = torch.initial_se... | InternVideo-main | Downstream/Temporal-Action-Localization/libs/datasets/data_utils.py |
from linecache import updatecache
import os
import json
import h5py
import numpy as np
import torch
from torch.utils.data import Dataset
from torch.nn import functional as F
from .datasets import register_dataset
from .data_utils import truncate_feats
from ..utils import remove_duplicate_annotations
import pickle
i... | InternVideo-main | Downstream/Temporal-Action-Localization/libs/datasets/anet.py |
# Modified from official EPIC-Kitchens action detection evaluation code
# see https://github.com/epic-kitchens/C2-Action-Detection/blob/master/EvaluationCode/evaluate_detection_json_ek100.py
import os
import json
import pandas as pd
import numpy as np
from joblib import Parallel, delayed
from typing import List
from ty... | InternVideo-main | Downstream/Temporal-Action-Localization/libs/utils/metrics.py |
import os
import shutil
import time
import pickle
import numpy as np
import random
from copy import deepcopy
import torch
import torch.optim as optim
import torch.backends.cudnn as cudnn
from .lr_schedulers import LinearWarmupMultiStepLR, LinearWarmupCosineAnnealingLR
from .postprocessing import postprocess_results
... | InternVideo-main | Downstream/Temporal-Action-Localization/libs/utils/train_utils.py |
import math
import warnings
from collections import Counter
from bisect import bisect_right
import torch
from torch.optim.lr_scheduler import _LRScheduler
class LinearWarmupCosineAnnealingLR(_LRScheduler):
"""
Sets the learning rate of each parameter group to follow a linear warmup schedule
between warmu... | InternVideo-main | Downstream/Temporal-Action-Localization/libs/utils/lr_schedulers.py |
# Functions for 1D NMS, modified from:
# https://github.com/open-mmlab/mmcv/blob/master/mmcv/ops/nms.py
import torch
import nms_1d_cpu
class NMSop(torch.autograd.Function):
@staticmethod
def forward(
ctx, segs, scores, cls_idxs,
iou_threshold, min_score, max_num
):
# vanilla nms w... | InternVideo-main | Downstream/Temporal-Action-Localization/libs/utils/nms.py |
from .nms import batched_nms
from .metrics import ANETdetection, remove_duplicate_annotations
from .train_utils import (make_optimizer, make_scheduler, save_checkpoint,
AverageMeter, train_one_epoch, valid_one_epoch,
fix_random_seed, ModelEma)
from .postprocessing imp... | InternVideo-main | Downstream/Temporal-Action-Localization/libs/utils/__init__.py |
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