python_code stringlengths 0 992k | repo_name stringlengths 8 46 | file_path stringlengths 5 162 |
|---|---|---|
from .base import BaseLocalizer
from .bmn import BMN
from .bsn import PEM, TEM
from .ssn import SSN
__all__ = ['PEM', 'TEM', 'BMN', 'SSN', 'BaseLocalizer']
| InternVideo-main | Downstream/Open-Set-Action-Recognition/mmaction/models/localizers/__init__.py |
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from ...localization import temporal_iop
from ..builder import build_loss
from ..registry import LOCALIZERS
from .base import BaseLocalizer
from .utils import post_processing
@LOCALIZERS.register_module()
class TEM(BaseLocalizer):
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/mmaction/models/localizers/bsn.py |
from abc import ABCMeta, abstractmethod
from collections import OrderedDict
import torch
import torch.distributed as dist
import torch.nn as nn
from .. import builder
class BaseLocalizer(nn.Module, metaclass=ABCMeta):
"""Base class for localizers.
All localizers should subclass it. All subclass should over... | InternVideo-main | Downstream/Open-Set-Action-Recognition/mmaction/models/localizers/base.py |
from .post_processing import post_processing
__all__ = ['post_processing']
| InternVideo-main | Downstream/Open-Set-Action-Recognition/mmaction/models/localizers/utils/__init__.py |
from mmaction.localization import soft_nms
def post_processing(result, video_info, soft_nms_alpha, soft_nms_low_threshold,
soft_nms_high_threshold, post_process_top_k,
feature_extraction_interval):
"""Post process for temporal proposals generation.
Args:
result... | InternVideo-main | Downstream/Open-Set-Action-Recognition/mmaction/models/localizers/utils/post_processing.py |
from .bsn_utils import generate_bsp_feature, generate_candidate_proposals
from .proposal_utils import soft_nms, temporal_iop, temporal_iou
from .ssn_utils import (eval_ap, load_localize_proposal_file,
perform_regression, temporal_nms)
__all__ = [
'generate_candidate_proposals', 'generate_bs... | InternVideo-main | Downstream/Open-Set-Action-Recognition/mmaction/localization/__init__.py |
import os.path as osp
import numpy as np
from .proposal_utils import temporal_iop, temporal_iou
def generate_candidate_proposals(video_list,
video_infos,
tem_results_dir,
temporal_scale,
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/mmaction/localization/bsn_utils.py |
import numpy as np
def temporal_iou(proposal_min, proposal_max, gt_min, gt_max):
"""Compute IoU score between a groundtruth bbox and the proposals.
Args:
proposal_min (list[float]): List of temporal anchor min.
proposal_max (list[float]): List of temporal anchor max.
gt_min (float): G... | InternVideo-main | Downstream/Open-Set-Action-Recognition/mmaction/localization/proposal_utils.py |
from itertools import groupby
import numpy as np
from ..core import average_precision_at_temporal_iou
from . import temporal_iou
def load_localize_proposal_file(filename):
"""Load the proposal file and split it into many parts which contain one
video's information separately.
Args:
filename(str... | InternVideo-main | Downstream/Open-Set-Action-Recognition/mmaction/localization/ssn_utils.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/pytorch2onnx.py |
InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/__init__.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.
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/flow_extraction.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/test.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/publish_model.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:
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/bsn_proposal_generation.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 init_dist, set_random_seed
from mmcv.utils import get_git_hash
from mmaction import __version__
from mmaction.apis import train_model
from mmacti... | InternVideo-main | Downstream/Open-Set-Action-Recognition/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 init_dist, set_random_seed
from mmcv.utils import get_git_hash
import numpy as np
from mmaction import __version__
from mmaction.apis import trai... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/hypertune.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/analysis/eval_metric.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/analysis/benchmark.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 = ... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/analysis/print_config.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/analysis/report_accuracy.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/analysis/bench_processing.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/analysis/get_flops.py |
import argparse
import os
import os.path as osp
import mmcv
import numpy as np
from mmaction.core import ActivityNetDetection
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."""
if ... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/analysis/report_map.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 = ... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/analysis/analyze_logs.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(... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/extract_audio.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/anno_txt2json.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_hmdb51_split,
parse_jester_splits,
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/build_file_list.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/build_rawframes.py |
import os, argparse
import cv2
from tqdm import tqdm
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Check the data')
parser.add_argument('video_path', type=str, help='The video path')
parser.add_argument('dataset_list', type=str, help='The list file of dataset.')
parser.add_a... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/data_check.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)... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/build_videos.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/parse_file_list.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_... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/denormalize_proposal_file.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/build_audio_features.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/resize_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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/omnisource/trim_raw_video.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')
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/activitynet/activitynet_feature_postprocessing.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 os
import ssl
import subprocess
import mmcv
from joblib import Parallel, delayed
ssl._create_default_https_context = ssl._create_unveri... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/activitynet/download.py |
import os
import os.path as osp
import mmcv
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'
def generate_rawframes_filelist():
anet_annotations = m... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/activitynet/generate_rawframes_filelist.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/activitynet/convert_proposal_format.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-... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/activitynet/tsn_feature_extraction.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_... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/activitynet/process_annotations.py |
# ------------------------------------------------------------------------------
# Adapted from https://github.com/activitynet/ActivityNet/
# Original licence: Copyright (c) Microsoft, under the MIT License.
# ------------------------------------------------------------------------------
import argparse
import glob
imp... | InternVideo-main | Downstream/Open-Set-Action-Recognition/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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/kinetics/download_subset.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/ava/download_videos_parallel.py |
# ------------------------------------------------------------------------------
# Adapted from https://github.com/activitynet/ActivityNet/
# Original licence: Copyright (c) Microsoft, under the MIT License.
# ------------------------------------------------------------------------------
import argparse
import glob
im... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/hvu/download.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/hvu/parse_tag_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)
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/hvu/generate_sub_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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/hvu/generate_file_list.py |
import os, argparse
from sklearn.utils import shuffle
def parse_args():
parser = argparse.ArgumentParser(description='Build file list')
parser.add_argument('dataset', type=str, choices=['mimetics10', 'mimetics'], help='dataset to be built file list')
parser.add_argument('src_folder', type=str, help='root... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/mimetics/build_file_list.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
import youtube_dl
import glob
ssl._cre... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/gym/download_ytdl.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/gym/download.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/gym/trim_subaction.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... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/gym/trim_event.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.... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/gym/generate_file_list.py |
import os
from tqdm import tqdm
def fix_listfile(file_split, phase):
assert os.path.exists(file_split), 'File does not exist! %s'%(file_split)
filename = file_split.split('/')[-1]
file_split_new = os.path.join(dataset_path, 'temp_' + filename)
with open(file_split_new, 'w') as fw:
with open(fi... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tools/data/mit/fix_video_filelist.py |
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.lines import Line2D
def draw_curves():
fig = plt.figure(figsize=(8,5))
plt.rcParams["font.family"] = "Arial"
fontsize = 15
markersize = 80
# I3D
I3D_DNN_HMDB = [94.69, 75.07] # (closed-set ACC, open-set AUC)
I3D_DNN_MiT =... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/draw_performance_gain.py |
import numpy as np
import argparse
import os
import matplotlib.pyplot as plt
# from mmaction.core.evaluation import confusion_matrix
from mpl_toolkits.axes_grid1 import make_axes_locatable
import matplotlib.ticker as ticker
from matplotlib.colors import LogNorm
def confusion_maxtrix(ind_labels, ind_results, ind_uncer... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/draw_confusion_matrix.py |
import argparse
import os
import os.path as osp
import torch
import mmcv
from mmaction.apis import init_recognizer
from mmcv.parallel import collate, scatter
from operator import itemgetter
from mmaction.datasets.pipelines import Compose
from mmaction.datasets import build_dataloader, build_dataset
from mmcv.parallel i... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/ood_detection.py |
import argparse
import os
import torch
import mmcv
from mmaction.apis import init_recognizer
from mmaction.datasets import build_dataloader, build_dataset
from mmaction.core.evaluation import top_k_accuracy
from mmcv.parallel import MMDataParallel
import numpy as np
import torch.multiprocessing
torch.multiprocessing.se... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/eval_debias.py |
import argparse, os, sys
import torch
import mmcv
import numpy as np
import torch.nn.functional as F
from mmcv.parallel import collate, scatter
from mmaction.datasets.pipelines import Compose
from mmaction.apis import init_recognizer
from mmaction.datasets import build_dataloader, build_dataset
from mmcv.parallel impor... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/baseline_openmax.py |
import argparse
import os
import os.path as osp
import torch
import mmcv
from mmaction.apis import init_recognizer
from mmcv.parallel import collate, scatter
from operator import itemgetter
from mmaction.datasets.pipelines import Compose
from mmaction.datasets import build_dataloader, build_dataset
from mmcv.parallel i... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/get_threshold_dist.py |
import argparse
import os
import os.path as osp
import torch
import mmcv
from mmaction.apis import init_recognizer
from mmcv.parallel import collate, scatter
from operator import itemgetter
from mmaction.datasets.pipelines import Compose
from mmaction.datasets import build_dataloader, build_dataset
from mmcv.parallel i... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/get_threshold.py |
import argparse, os, sys
import torch
import mmcv
import numpy as np
import torch.nn.functional as F
from mmcv.parallel import collate, scatter
from mmaction.datasets.pipelines import Compose
from mmaction.apis import init_recognizer
from mmaction.datasets import build_dataloader, build_dataset
from mmcv.parallel impor... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/baseline_softmax.py |
import argparse
import os
import os.path as osp
import torch
import mmcv
from mmaction.apis import init_recognizer
from mmcv.parallel import collate, scatter
from mmaction.datasets.pipelines import Compose
from mmaction.datasets import build_dataloader, build_dataset
from mmcv.parallel import MMDataParallel
import nump... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/baseline_rpl.py |
import os
import argparse
from matplotlib.pyplot import axis
import numpy as np
from sklearn.metrics import roc_auc_score, accuracy_score, precision_recall_curve, auc, roc_curve
from terminaltables import AsciiTable
def parse_args():
'''Command instruction:
source activate mmaction
python experimen... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/compare_openness_new.py |
import argparse
import os
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
def parse_args():
parser = argparse.ArgumentParser(description='Draw histogram')
parser.add_argument('--uncertainty', default='EDL', choices=['BALD', 'Entropy', 'EDL'], help='the uncertainty estimat... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/draw_ood_hist.py |
import argparse
import os
import os.path as osp
import torch
import mmcv
from mmcv import Config, DictAction
from mmaction.apis import init_recognizer
from mmcv.parallel import collate, scatter
from operator import itemgetter
from mmaction.datasets.pipelines import Compose
from mmaction.datasets import build_dataloader... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/ood_detection_dist.py |
import os
import numpy as np
import matplotlib.pyplot as plt
def plot_by_uncertainty(result_file, uncertainty='EDL', auc=80, fontsize=16, result_prefix=''):
assert os.path.exists(result_file), 'result file not exists! %s'%(result_file)
results = np.load(result_file, allow_pickle=True)
# ind_confidences = ... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/draw_fig7cd.py |
import os
import argparse
import numpy as np
from sklearn.metrics import f1_score, roc_auc_score, accuracy_score
import matplotlib.pyplot as plt
def parse_args():
'''Command instruction:
source activate mmaction
python experiments/compare_openness.py --ind_ncls 101 --ood_ncls 51
'''
parser ... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/compare_openness.py |
import argparse
import os
import torch
from mmaction.apis import init_recognizer
from mmcv.parallel import collate, scatter
from mmaction.datasets.pipelines import Compose
import numpy as np
from tqdm import tqdm
def parse_args():
parser = argparse.ArgumentParser(description='MMAction2 test')
# model config
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/demo.py |
import argparse, os
import numpy as np
import matplotlib.pyplot as plt
def eval_calibration(predictions, confidences, labels, M=15):
"""
M: number of bins for confidence scores
"""
num_Bm = np.zeros((M,), dtype=np.int32)
accs = np.zeros((M,), dtype=np.float32)
confs = np.zeros((M,), dtype=np.f... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/evaluate_calibration.py |
import argparse
import os
import torch
from mmcv.parallel import collate, scatter
from mmaction.datasets.pipelines import Compose
from mmaction.apis import init_recognizer
from sklearn.manifold import TSNE
import numpy as np
import matplotlib.pyplot as plt
from tqdm import tqdm
def parse_args():
parser = argparse... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/analyze_features.py |
import os, argparse
import numpy as np
import matplotlib.pyplot as plt
from sklearn.metrics import f1_score
def softmax_curvepoints(result_file, thresh, ood_ncls, num_rand):
assert os.path.exists(result_file), "File not found! Run baseline_i3d_softmax.py first!"
# load the testing results
results = np.loa... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/draw_openness_curves.py |
from distutils.core import setup
from distutils.extension import Extension
from Cython.Distutils import build_ext
from Cython.Build import cythonize
import sys
import numpy
#ext_modules = [Extension("libmr", ["libmr.pyx", "MetaRecognition.cpp"])]
setup(
ext_modules = cythonize(Extension('libmr',
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/libMR/setup.py |
import os, sys
import scipy as sp
import libmr
def main():
posscores = sp.asarray([0.245 , 0.2632, 0.3233, 0.3573, 0.4014, 0.4055, 0.4212, 0.5677])
test_distances = sp.asarray([ 0.05, 0.1 , 0.25, 0.4 , 0.75, 1. , 1.5 , 2.])
mr = libmr.MR()
# since higher is worse and we want to fit the ... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/libMR/estimate_wscores.py |
import scipy as sp
import sys, os
try:
import libmr
print("Imported libmr succesfully")
except ImportError:
print("Cannot import libmr")
sys.exit()
import pickle
svm_data = {}
svm_data["labels"] = [1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1 , -1, -1, -1, -1, -1,
1, 1, 1, 1,... | InternVideo-main | Downstream/Open-Set-Action-Recognition/experiments/libMR/test_libmr.py |
import os.path as osp
import random
import numpy as np
import pytest
from numpy.testing import assert_array_almost_equal, assert_array_equal
from mmaction.core import (ActivityNetDetection,
average_recall_at_avg_proposals, confusion_matrix,
get_weighted_score, mea... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_accuracy.py |
import os.path as osp
import numpy as np
import pytest
from numpy.testing import assert_array_almost_equal, assert_array_equal
from mmaction.localization import (generate_bsp_feature,
generate_candidate_proposals, soft_nms,
temporal_iop, temporal_i... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_localization_utils.py |
import numpy as np
import pytest
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv import ConfigDict
from numpy.testing import assert_array_almost_equal
from torch.autograd import Variable
from mmaction.models import (BCELossWithLogits, BinaryLogisticRegressionLoss,
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_loss.py |
import os.path as osp
import mmcv
import numpy as np
import pytest
import torch
from mmaction.models import build_recognizer
from mmaction.utils.gradcam_utils import GradCAM
def _get_cfg(fname):
"""Grab configs necessary to create a recognizer.
These are deep copied to allow for safe modification of parame... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_gradcam.py |
import copy
import numpy as np
import pytest
import torch
import torch.nn as nn
from mmcv.utils import _BatchNorm
from mmaction.models import (C3D, X3D, ResNet, ResNet2Plus1d, ResNet3d,
ResNet3dCSN, ResNet3dSlowFast, ResNet3dSlowOnly,
ResNetAudio, ResNetTIN, R... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_models/test_backbone.py |
import mmcv
import pytest
import torch
import torch.nn as nn
from mmaction.apis import inference_recognizer, init_recognizer
video_config_file = 'configs/recognition/tsn/tsn_r50_video_inference_1x1x3_100e_kinetics400_rgb.py' # noqa: E501
frame_config_file = 'configs/recognition/tsn/tsn_r50_inference_1x1x3_100e_kinet... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_models/test_inference.py |
import os.path as osp
import mmcv
import numpy as np
import pytest
import torch
import torch.nn.functional as F
from mmaction.models import BaseRecognizer, build_recognizer
class ExampleRecognizer(BaseRecognizer):
def __init__(self, train_cfg, test_cfg):
super(BaseRecognizer, self).__init__()
#... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_models/test_recognizers.py |
import pytest
import torch
from mmaction.models import Conv2plus1d, ConvAudio
def test_conv2plus1d():
with pytest.raises(AssertionError):
# Length of kernel size, stride and padding must be the same
Conv2plus1d(3, 8, (2, 2))
conv_2plus1d = Conv2plus1d(3, 8, 2)
conv_2plus1d.init_weights()... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_models/test_common_modules.py |
import torch
import torch.nn as nn
from mmaction.models import (AudioTSNHead, BaseHead, I3DHead, SlowFastHead,
TPNHead, TSMHead, TSNHead, X3DHead)
class ExampleHead(BaseHead):
# use a ExampleHead to success BaseHead
def init_weights(self):
pass
def forward(self, x):
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_models/test_head.py |
import copy
import mmcv
import numpy as np
import pytest
import torch
from mmaction.models import build_localizer
from mmaction.models.localizers.utils import post_processing
def test_tem():
model_cfg = dict(
type='TEM',
temporal_dim=100,
boundary_ratio=0.1,
tem_feat_dim=400,
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_models/test_localizers.py |
import copy
import numpy as np
import pytest
import torch
from mmaction.models import TPN
def test_tpn():
"""Test TPN backbone."""
tpn_cfg = dict(
in_channels=(1024, 2048),
out_channels=1024,
spatial_modulation_cfg=dict(
in_channels=(1024, 2048), out_channels=2048),
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_models/test_neck.py |
import numpy as np
import pytest
from mmaction.datasets.pipelines import Compose, ImageToTensor
def check_keys_equal(result_keys, target_keys):
"""Check if all elements in target_keys is in result_keys."""
return set(target_keys) == set(result_keys)
def test_compose():
with pytest.raises(TypeError):
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_data/test_compose.py |
import copy
import os.path as osp
import mmcv
import numpy as np
import pytest
import torch
from numpy.testing import assert_array_almost_equal, assert_array_equal
# yapf: disable
from mmaction.datasets.pipelines import (AudioDecode, AudioDecodeInit,
AudioFeatureSelector, Deco... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_data/test_loading.py |
import numpy as np
import pytest
import torch
from mmcv.parallel import DataContainer as DC
from mmaction.datasets.pipelines import (Collect, FormatAudioShape,
FormatShape, ImageToTensor,
ToDataContainer, ToTensor, Transpose)
def check... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_data/test_formating.py |
import os
import os.path as osp
import tempfile
import mmcv
import numpy as np
import pytest
from mmcv import ConfigDict
from numpy.testing import assert_array_almost_equal, assert_array_equal
from mmaction.datasets import (ActivityNetDataset, AudioDataset,
AudioFeatureDataset, AudioVis... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_data/test_dataset.py |
import os.path as osp
import mmcv
import numpy as np
from numpy.testing import assert_array_equal
from mmaction.datasets import AVADataset
def check_keys_contain(result_keys, target_keys):
"""Check if all elements in target_keys is in result_keys."""
return set(target_keys).issubset(set(result_keys))
clas... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_data/test_ava_dataset.py |
import copy
import mmcv
import numpy as np
import pytest
from numpy.testing import assert_array_almost_equal, assert_array_equal
# yapf: disable
from mmaction.datasets.pipelines import (AudioAmplify, CenterCrop, ColorJitter,
EntityBoxClip, EntityBoxCrop,
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_data/test_augmentations.py |
import os.path as osp
import tempfile
import unittest.mock as mock
from unittest.mock import MagicMock, patch
import mmcv
import pytest
import torch
import torch.nn as nn
from mmcv.runner import EpochBasedRunner, build_optimizer
from mmcv.utils import get_logger
from torch.utils.data import DataLoader, Dataset
from m... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_runtime/test_eval_hook.py |
import torch
import torch.nn as nn
from mmcv.runner import build_optimizer_constructor
class SubModel(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Conv2d(2, 2, kernel_size=1, groups=2)
self.gn = nn.GroupNorm(2, 2)
self.fc = nn.Linear(2, 2)
self.param1... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_runtime/test_optimizer.py |
import tempfile
import pytest
import torch
import torch.nn as nn
from mmcv import Config
from torch.utils.data import Dataset
from mmaction.apis import train_model
from mmaction.datasets.registry import DATASETS
@DATASETS.register_module()
class ExampleDataset(Dataset):
def __init__(self, test_mode=False):
... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_runtime/test_train.py |
import sys
from unittest.mock import MagicMock, Mock, patch
import pytest
import torch
import torch.nn as nn
from torch.utils.data import DataLoader, Dataset
from mmaction.apis.test import (collect_results_cpu, multi_gpu_test,
single_gpu_test)
class OldStyleModel(nn.Module):
def... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_runtime/test_apis_test.py |
import logging
import shutil
import sys
import tempfile
from unittest.mock import MagicMock, call
import torch
import torch.nn as nn
from mmcv.runner import IterTimerHook, PaviLoggerHook, build_runner
from torch.utils.data import DataLoader
def test_tin_lr_updater_hook():
sys.modules['pavi'] = MagicMock()
lo... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_runtime/test_lr.py |
import os.path as osp
import tempfile
import torch.nn as nn
from tools.pytorch2onnx import _convert_batchnorm, pytorch2onnx
class TestModel(nn.Module):
def __init__(self):
super().__init__()
self.conv = nn.Conv3d(1, 2, 1)
self.bn = nn.SyncBatchNorm(2)
def forward(self, x):
r... | InternVideo-main | Downstream/Open-Set-Action-Recognition/tests/test_runtime/test_onnx.py |
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