repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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DeepPersonality | DeepPersonality-main/dpcv/exps_first_stage/03_audiovisual_residual_networks.py | import torch.nn as nn
import torch.optim as optim
from dpcv.engine.bi_modal_trainer import BiModalTrainer
from dpcv.tools.common import setup_seed, setup_config
from dpcv.tools.logger import make_logger
from dpcv.modeling.networks.audio_visual_residual import get_audiovisual_resnet_model
from dpcv.config.audiovisual_re... | 1,439 | 34.121951 | 101 | py |
DeepPersonality | DeepPersonality-main/dpcv/exps_first_stage/10_swin_transformer_on_personality.py | import torch.optim as optim
import torch.nn as nn
from dpcv.config.swin_transformer_cfg import cfg
from dpcv.modeling.networks.swin_transformer import get_swin_transformer_model
from dpcv.tools.common import setup_seed, setup_config
from dpcv.tools.logger import make_logger
from dpcv.tools.common import parse_args
from... | 1,363 | 33.1 | 101 | py |
DeepPersonality | DeepPersonality-main/dpcv/exps_first_stage/11_3D_resnet_on_personality.py | import torch.nn as nn
import torch.optim as optim
from dpcv.config.resnet_3d_cfg import cfg
from dpcv.modeling.networks.resnet_3d import get_3d_resnet_model
from dpcv.tools.common import setup_seed, setup_config
from dpcv.tools.logger import make_logger
from dpcv.tools.common import parse_args
from dpcv.evaluation.summ... | 1,339 | 32.5 | 101 | py |
DeepPersonality | DeepPersonality-main/dpcv/exps_first_stage/02_bi-modal-LSTM_nn.py | import torch.nn as nn
import os
import torch.optim as optim
from dpcv.config.bi_modal_lstm_cfg import cfg
from dpcv.engine.bi_modal_trainer import BimodalLSTMTrain, ImgModalLSTMTrain, AudModalLSTMTrain
from dpcv.tools.common import setup_seed, setup_config
from dpcv.tools.logger import make_logger
from dpcv.modeling.ne... | 1,773 | 34.48 | 101 | py |
DeepPersonality | DeepPersonality-main/dpcv/exps_first_stage/14_video_action_transformer_on_personality.py | import torch.nn as nn
import torch.optim as optim
from dpcv.config.vat_cfg import cfg
from dpcv.modeling.networks.video_action_transformer import get_vat_model
from dpcv.tools.common import setup_seed, setup_config
from dpcv.tools.logger import make_logger
from dpcv.tools.common import parse_args
from dpcv.evaluation.s... | 1,324 | 32.125 | 101 | py |
DeepPersonality | DeepPersonality-main/dpcv/exps_first_stage/06_interpreting_cnn_models.py | import torch
import torch.nn as nn
import torch.optim as optim
from dpcv.config.interpret_dan_cfg import cfg
from dpcv.engine.bi_modal_trainer import ImageModalTrainer
from dpcv.modeling.networks.interpret_dan import get_interpret_dan_model
from dpcv.tools.common import setup_seed, setup_config
from dpcv.tools.logger i... | 3,142 | 31.402062 | 101 | py |
DeepPersonality | DeepPersonality-main/dpcv/exps_first_stage/12_slow_fast_on_personality.py | import torch.nn as nn
import torch.optim as optim
from dpcv.config.slow_fast_cfg import cfg
from dpcv.modeling.networks.slow_fast import get_slow_fast_model
from dpcv.tools.common import setup_seed, setup_config
from dpcv.tools.logger import make_logger
from dpcv.tools.common import parse_args
from dpcv.evaluation.summ... | 1,331 | 32.3 | 101 | py |
DeepPersonality | DeepPersonality-main/dpcv/exps_first_stage/15_key_dynamic_image.py | from engine.excitation_core import contrastive_excitation_backprop
import torchvision
from PIL import Image
from dpcv.tools.common import get_device
from dpcv.modeling.networks.excitation_bp_rnn import AlexNetLSTM
from dpcv.tools.draw import plot_example
def get_example_data(shape=224):
"""Get example data to dem... | 2,298 | 28.474359 | 78 | py |
DeepPersonality | DeepPersonality-main/dpcv/engine/excitation_core.py |
__all__ = [
"contrastive_excitation_backprop",
"eltwise_sum",
"excitation_backprop",
"ExcitationBackpropContext",
]
import torch
import torch.nn as nn
from torch.autograd import Function
from dpcv.tools.excitation_bp import Patch, Probe
from dpcv.tools.excitation_bp import get_backward_gradient, get_... | 20,385 | 37.609848 | 101 | py |
DeepPersonality | DeepPersonality-main/dpcv/engine/bi_modal_trainer.py | import torch
from tqdm import tqdm
import numpy as np
import math
import os
from .build import TRAINER_REGISTRY
from torch.utils.tensorboard import SummaryWriter
import time
@TRAINER_REGISTRY.register()
class BiModalTrainer(object):
"""base trainer for bi-modal input"""
def __init__(self, cfg, collector, logg... | 26,435 | 40.566038 | 126 | py |
DeepPersonality | DeepPersonality-main/dpcv/engine/crnet_trainer.py | import torch
from tqdm import tqdm
from dpcv.engine.bi_modal_trainer import BiModalTrainer
import numpy as np
import math
import os
from .build import TRAINER_REGISTRY
class CRNetTrainer(BiModalTrainer):
def train(self, data_loader, model, loss_f, optimizer, epoch_idx):
model.train()
if model.tr... | 18,256 | 43.420925 | 116 | py |
DeepPersonality | DeepPersonality-main/dpcv/engine/bi_modal_lstm_train.py | import torch
from dpcv.engine.bi_modal_trainer import BiModalTrainer
# class BiModalTrainer_(object):
# def __init__(self, collector):
# self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
# self.clt = collector
#
# def train(self, data_loader, model, loss_f, optimizer, ... | 3,497 | 41.144578 | 116 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/video_frame_data.py | import random
import torch
from torch.utils.data import DataLoader
from PIL import Image
import numpy as np
import glob
from dpcv.data.datasets.bi_modal_data import VideoData
from dpcv.data.transforms.transform import set_transform_op
from dpcv.data.transforms.build import build_transform_spatial
from .build import DAT... | 6,427 | 30.9801 | 110 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/second_stage_dataset.py | import torch
from torch.utils.data import Dataset
from dpcv.data.datasets.build import DATA_LOADER_REGISTRY
from torch.utils.data import DataLoader
import glob
import os
from tqdm import tqdm
import numpy as np
from math import ceil
class SecondStageData(Dataset):
def __init__(self, data_dir, data_type="pred", m... | 10,829 | 34.048544 | 120 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/cr_data.py | import torch
import os
import glob
from torch.utils.data import DataLoader
from PIL import Image
import random
import numpy as np
from pathlib import Path
from dpcv.data.datasets.bi_modal_data import VideoData
from .build import DATA_LOADER_REGISTRY
from dpcv.data.transforms.transform import set_crnet_transform, crnet_... | 11,162 | 38.168421 | 113 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/ture_personality_data.py | import os
import torch
from torch.utils.data.dataset import Dataset
from torch.utils.data import DataLoader
import os.path as opt
import glob
import numpy as np
import json
import random
from pathlib import Path
from PIL import Image
from PIL import ImageFile
ImageFile.LOAD_TRUNCATED_IMAGES = True
import torchaudio
fro... | 28,793 | 35.12798 | 119 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/vat_data.py | import torch
from torch.utils.data import DataLoader
from dpcv.data.transforms.transform import set_vat_transform_op
from dpcv.data.datasets.video_segment_data import VideoFrameSegmentData
from dpcv.data.datasets.tpn_data import TPNData as VATData
from dpcv.data.datasets.tpn_data import TPNTruePerData as VATTruePerData... | 6,490 | 31.949239 | 119 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/slow_fast_data_true_personality.py | from dpcv.data.datasets.video_segment_data import TruePersonalityVideoFrameSegmentData
import torch
from torch.utils.data import DataLoader
from dpcv.data.datasets.bi_modal_data import VideoData
from dpcv.data.transforms.transform import set_transform_op
from dpcv.data.transforms.build import build_transform_spatial
fr... | 2,616 | 33.893333 | 120 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/feature_extract_true_personality_dataset.py | from .ture_personality_data import Chalearn21FrameData, Chalearn21PersemonData
from dpcv.data.transforms.build import build_transform_spatial
import glob
import torch
import os.path as opt
from pathlib import Path
import numpy as np
import random
from PIL import Image
from PIL import ImageFile
ImageFile.LOAD_TRUNCATED_... | 8,737 | 34.376518 | 99 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/audio_data.py | import os
import numpy as np
from dpcv.data.datasets.bi_modal_data import VideoData
from dpcv.data.datasets.cr_data import CRNetData
from torch.utils.data import DataLoader
from dpcv.data.datasets.build import DATA_LOADER_REGISTRY
import torch
@DATA_LOADER_REGISTRY.register()
class AudioData(VideoData):
def __ini... | 7,905 | 28.610487 | 101 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/tpn_data.py | import torch
from torch.utils.data import DataLoader
from dpcv.data.transforms.transform import set_tpn_transform_op
from dpcv.data.datasets.video_segment_data import VideoFrameSegmentData
from dpcv.data.transforms.temporal_transforms import TemporalRandomCrop, TemporalDownsample, TemporalEvenCropDownsample
from dpcv.d... | 8,114 | 31.46 | 119 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/temporal_data.py | """
TODO: merge temporal data to bi_modal_data
"""
import torch
import os
import glob
from dpcv.data.datasets.bi_modal_data import VideoData
from torch.utils.data import DataLoader
from PIL import Image
from pathlib import Path
import random
import numpy as np
from dpcv.data.transforms.transform import face_image_trans... | 5,639 | 32.372781 | 109 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/pers_emo_data.py | import glob
import random
import os
from PIL import Image
from pathlib import Path
import torch
import numpy as np
from torch.utils.data import DataLoader
from dpcv.data.datasets.bi_modal_data import VideoData
from dpcv.data.transforms.build import build_transform_spatial
from dpcv.data.transforms.transform import set_... | 10,331 | 36.846154 | 115 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/interpretability_audio_data.py | import os
from dpcv.data.datasets.bi_modal_data import VideoData
from .build import DATA_LOADER_REGISTRY
import torch
import torchaudio
from torch.utils.data import DataLoader
def aud_transform():
return torchaudio.transforms.Resample(44100, 4000)
def norm(aud_ten):
mean = aud_ten.mean()
std = aud_ten.s... | 4,665 | 32.328571 | 97 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/audio_visual_data.py | import os
import torch
import glob
from torch.utils.data import DataLoader
from torch.utils.data import Dataset
from PIL import Image
import random
import pickle
import numpy as np
from dpcv.data.datasets.bi_modal_data import VideoData
from dpcv.data.transforms.transform import set_audio_visual_transform
from dpcv.data... | 8,335 | 34.47234 | 119 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/video_segment_data.py | import torch
from torch.utils.data import DataLoader
import glob
import numpy as np
import os
from pathlib import Path
from dpcv.data.datasets.bi_modal_data import VideoData
from dpcv.data.transforms.transform import set_transform_op
from dpcv.data.transforms.build import build_transform_spatial
from .build import DATA... | 12,338 | 33.563025 | 120 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/bi_modal_data.py | import glob
import torch
import numpy as np
from PIL import Image
from torch.utils.data import Dataset
import pickle
import os
from random import shuffle
class VideoData(Dataset):
"""base class for bi-modal input data"""
def __init__(self, data_root, img_dir, label_file, audio_dir=None, parse_img_dir=True, pa... | 3,143 | 35.988235 | 112 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/multi_modal_pred.py | import torch
import glob
import os
from torch.utils.data import DataLoader
from pathlib import Path
from .build import DATA_LOADER_REGISTRY
class MultiModalData:
def __init__(self, data_root, split, mode, session, spectrum_channel=15):
assert session in ["none", "talk", "animal", "lego", "ghost"], \
... | 3,424 | 30.422018 | 87 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/datasets/slow_fast_data.py | import torch
from torch.utils.data import DataLoader
from dpcv.data.transforms.transform import set_transform_op
from dpcv.data.datasets.video_segment_data import VideoFrameSegmentData
from dpcv.data.transforms.temporal_transforms import TemporalRandomCrop, TemporalDownsample, TemporalTwoEndsCrop
from dpcv.data.transfo... | 6,596 | 30.869565 | 112 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/utils/feature_extractor.py | import torch
import os
from pathlib import Path
from tqdm import tqdm
import numpy as np
from PIL import Image
import glob
from torchvggish import vggish, vggish_input
from dpcv.data.transforms.transform import set_transform_op
from dpcv.data.datasets.bi_modal_data import VideoData
from dpcv.modeling.networks.multi_mod... | 4,866 | 36.438462 | 103 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/utils/feature_extractor_tp.py | import os
from tqdm import tqdm
import torch
import numpy as np
from torchvggish import vggish, vggish_input
from dpcv.modeling.networks.multi_modal_pred_net import resnet101_visual_feature_extractor
from dpcv.data.datasets.ture_personality_data import Chalearn21FrameData, Chalearn21AudioDataPath
class TPExtractVisua... | 4,514 | 44.15 | 113 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/transforms/transform.py | """
transform operation for different networks
for vgg face mean = (131.0912, 103.8827, 91.4953) no std
"""
from .build import TRANSFORM_REGISTRY
def set_transform_op():
import torchvision.transforms as transforms
norm_mean = [0.485, 0.456, 0.406] # statistics from imagenet dataset which contains about 120 m... | 4,902 | 32.353741 | 115 | py |
DeepPersonality | DeepPersonality-main/dpcv/data/transforms/spatial_transforms.py | """
code modified form https://github.com/kenshohara/3D-ResNets-PyTorch.git
"""
import random
from torchvision.transforms import transforms
from torchvision.transforms import functional as F
from PIL import Image
class Compose(transforms.Compose):
def randomize_parameters(self):
for t in self.transforms:... | 5,649 | 25.036866 | 95 | py |
DeepPersonality | DeepPersonality-main/dpcv/exps_second_stage/featrue_process.py | import os
import torch
from tqdm import tqdm
import glob
import numpy as np
from scipy import signal
import pickle
def gen_statistic_data(data_path, save_to, method=None):
data = torch.load(data_path)
statistic_data_ls = []
for sample in data["video_frames_pred"]:
statistic_data_ls.append(method(s... | 4,742 | 33.875 | 99 | py |
DeepPersonality | DeepPersonality-main/dpcv/exps_second_stage/train_net.py | import argparse
import os
import torch
import torch.nn as nn
from torch.utils.data import Dataset, DataLoader
import torch.optim as optim
from trainer import SpectrumTrainer
from trainer import MLPTrainer
from dpcv.modeling.networks.statistic_model import StatisticMLP
from dpcv.data.datasets.second_stage_dataset import... | 3,219 | 41.368421 | 112 | py |
DeepPersonality | DeepPersonality-main/dpcv/exps_second_stage/trainer.py | import torch
import os
import torch.nn as nn
from mlflow import log_metric, log_param, log_params
class MLPTrainer:
def __init__(self, max_epo, output_dir):
self.output_dir = output_dir
if not os.path.exists(output_dir):
os.makedirs(output_dir)
self.max_epo = max_epo
s... | 3,387 | 35.042553 | 103 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/solver/lr_schedule.py | import torch.optim as optim
from .build import SOLVER_REGISTRY
@SOLVER_REGISTRY.register()
def multi_step_scale(cfg, optimizer):
return optim.lr_scheduler.MultiStepLR(optimizer, gamma=cfg.SOLVER.FACTOR, milestones=cfg.SOLVER.MILESTONE)
@SOLVER_REGISTRY.register()
def cosine_annealing(cfg, optimizer):
return... | 714 | 28.791667 | 113 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/solver/optimize.py | import torch.optim as optim
from .build import SOLVER_REGISTRY
@SOLVER_REGISTRY.register()
def sgd(cfg, model):
return optim.SGD(
model.parameters(),
lr=cfg.SOLVER.LR_INIT,
momentum=cfg.SOLVER.MOMENTUM,
weight_decay=cfg.SOLVER.WEIGHT_DECAY
)
@SOLVER_REGISTRY.register()
def cr... | 827 | 26.6 | 117 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/slow_fast.py | """
code modified form https://github.com/facebookresearch/SlowFast.git
"""
import torch
import torch.nn as nn
from dpcv.modeling.module import weight_init_helper as init_helper
from functools import partial
from dpcv.modeling.module import stem_helper, resnet_helper
from .build import NETWORK_REGISTRY
from easydict im... | 24,983 | 36.797277 | 106 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/sphereface_net.py | """
code modified from https://github.com/clcarwin/sphereface_pytorch.git
"""
import torch
import torch.nn as nn
from torch.autograd import Variable
import torch.nn.functional as F
from torch.nn import Parameter
import math
from dpcv.modeling.module.weight_init_helper import initialize_weights
from .build import NETWOR... | 5,292 | 33.594771 | 93 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/statistic_model.py | import torch
import torch.nn as nn
from .build import NETWORK_REGISTRY
class StatisticMLP(nn.Module):
def __init__(self, hidden_units=256):
super(StatisticMLP, self).__init__()
# log_param("hidden_units", hidden_units)
self.input_layer = nn.Linear(12 * 5, hidden_units)
self.relu_1 ... | 2,188 | 33.203125 | 88 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/dan.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from .build import NETWORK_REGISTRY
from dpcv.modeling.module.weight_init_helper import initialize_weights
# import torch.utils.model_zoo as model_zoo
backbone = {
'VGG11': [64, 'M', 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512, 'M'],
'VGG1... | 6,604 | 35.694444 | 120 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/swin_transformer.py | # --------------------------------------------------------
# Swin Transformer
# Copyright (c) 2021 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ze Liu
#
# code modified from https://github.com/microsoft/Swin-Transformer.git
# Note that: added sigmoid function for model output
# sinc... | 29,160 | 39.277624 | 119 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/se_net.py | import torch
import torch.nn as nn
from torch.hub import load_state_dict_from_url
from dpcv.modeling.module.resnet_tv import ResNet
from dpcv.modeling.module.se_resnet import SEBottleneck
from .build import NETWORK_REGISTRY
@NETWORK_REGISTRY.register()
def se_resnet50(cfg, num_classes=1000, pretrained=False):
"""... | 2,880 | 45.467742 | 115 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/bi_modal_lstm.py | import torch
import torch.nn as nn
from dpcv.modeling.module.weight_init_helper import initialize_weights
from .build import NETWORK_REGISTRY
class BiModelLSTM(nn.Module):
def __init__(self, init_weights=True, true_personality=False):
super(BiModelLSTM, self).__init__()
self.audio_branch = nn.Line... | 6,000 | 36.273292 | 89 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/audio_visual_residual.py | import torch
import torch.nn as nn
from dpcv.modeling.module.bi_modal_resnet_module import AudioVisualResNet, AudInitStage
from dpcv.modeling.module.bi_modal_resnet_module import VisInitStage, BiModalBasicBlock
from dpcv.modeling.module.bi_modal_resnet_module import aud_conv1x9, aud_conv1x1, vis_conv3x3, vis_conv1x1
fr... | 4,542 | 31.683453 | 106 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/multi_modal_pred_net.py | import torch
import torch.nn as nn
from dpcv.modeling.module.resnet_tv import Bottleneck, BasicBlock, conv1x1, conv3x3
from dpcv.modeling.module.resnet_tv import model_zoo, model_urls
from .build import NETWORK_REGISTRY
class ResNetFeatureExtractor(nn.Module):
"""
Note: that class is not a formal resnet but w... | 6,631 | 34.848649 | 106 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/spectrum_model.py | import torch.cuda
import torch.nn as nn
from dpcv.modeling.networks.build import NETWORK_REGISTRY
from dpcv import device
from dpcv.modeling.module.weight_init_helper import initialize_weights
class SpectrumConv1D(nn.Module):
def __init__(self, channel=80, hidden_units=[128, 512, 2048]):
super(SpectrumCo... | 16,069 | 34.870536 | 119 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/interpret_dan.py | import torch
import torch.nn as nn
from dpcv.modeling.networks.dan import make_layers, backbone
from dpcv.modeling.networks.build import NETWORK_REGISTRY
from dpcv.modeling.module.weight_init_helper import initialize_weights
# import torch.utils.model_zoo as model_zoo
class InterpretDAN(nn.Module):
def __init__(... | 3,343 | 38.341176 | 120 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/audio_interpretability_net.py | import torch
import torch.nn as nn
from dpcv.modeling.module.weight_init_helper import initialize_weights
from .build import NETWORK_REGISTRY
class AudioInterpretNet(nn.Module):
def __init__(self, init_weights=True):
super().__init__()
self.conv_block_1 = nn.Sequential(
nn.Conv1d(1, 6... | 1,740 | 26.634921 | 81 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/excitation_bp_rnn.py | import torch
import torch.nn as nn
from torch.autograd import Variable
from torchvision.models.utils import load_state_dict_from_url
model_urls = {
'alexnet': 'https://download.pytorch.org/models/alexnet-owt-4df8aa71.pth',
}
class MultiLSTMCellRelu(nn.Module):
def __init__(self, input_size, hidden_size, nlay... | 5,010 | 33.088435 | 92 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/TSN2D.py | from dpcv.modeling.module.tpn.base import BaseRecognizer
from dpcv.modeling.module.tpn import resnet_mm, cls_head_module, simple_consensus, simple_spatial_module, tpn
from .build import NETWORK_REGISTRY
import torch
from torch.autograd import Variable
args = {
# 'type': 'TSN2D',
'backbone': {
# 'type':... | 8,989 | 30.766784 | 119 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/resnet_3d.py | """
code modified from https://github.com/kenshohara/3D-ResNets-PyTorch.git
"""
from functools import partial
import torch
import torch.nn as nn
import torch.nn.functional as F
from .build import NETWORK_REGISTRY
from dpcv.modeling.module.weight_init_helper import initialize_weights
def get_inplanes():
return [6... | 7,256 | 27.912351 | 100 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/cr_net.py | import torch
import torch.nn as nn
from dpcv.modeling.module.bi_modal_resnet_module import AudioVisualResNet, AudInitStage
from dpcv.modeling.module.bi_modal_resnet_module import BiModalBasicBlock, VisInitStage
from dpcv.modeling.module.bi_modal_resnet_module import aud_conv1x9, aud_conv1x1, vis_conv3x3, vis_conv1x1
fr... | 13,169 | 40.677215 | 117 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/TSN3D.py | from modeling.module.tpn.tpn import BaseRecognizer
from modeling import builder
import torch
class TSN3D(BaseRecognizer):
def __init__(self,
backbone,
necks=None,
spatial_temporal_module=None,
segmental_consensus=None,
fcn_test... | 4,712 | 30.42 | 118 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/video_action_transformer.py | """
code modified from https://github.com/ppriyank/Video-Action-Transformer-Network-Pytorch-.git
"""
import torch
import torch.nn.functional as F
from torch import nn
import math
import torchvision
from torch.autograd import Variable
from dpcv.modeling.module.weight_init_helper import initialize_weights
from .build imp... | 8,339 | 32.629032 | 114 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/hr_net_cls.py | # ------------------------------------------------------------------------------
# code modified form https://github.com/HRNet/HRNet-Image-Classification
# ------------------------------------------------------------------------------
from easydict import EasyDict
import os
import logging
import torch
import torch.nn a... | 21,618 | 37.196113 | 114 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/networks/single_modal_video_analysis_conv3d.py | import torch
import torch.nn as nn
class SequenceBasedModel(nn.Module):
def __init__(self, ):
super().__init__()
self.block_1 = nn.Sequential(
nn.Conv3d(in_channels=3, out_channels=64, kernel_size=(3, 5, 5)),
nn.BatchNorm3d(100),
nn.ReLU(),
nn.MaxPoo... | 1,519 | 29.4 | 80 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/operators.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
"""Custom operators."""
import torch
import torch.nn as nn
class Swish(nn.Module):
"""Swish activation function: x * sigmoid(x)."""
def __init__(self):
super(Swish, self).__init__()
def forward(self,... | 2,552 | 29.759036 | 86 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/resnet_tv.py | import torch.nn as nn
import torch.utils.model_zoo as model_zoo
from dpcv.modeling.module.weight_init_helper import initialize_weights
import torch
__all__ = ['ResNet', 'resnet18', 'resnet34', 'resnet50', 'resnet101',
'resnet152']
model_urls = {
'resnet18': 'https://download.pytorch.org/models/resnet... | 8,374 | 30.844106 | 106 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/vgg_tv.py | import torch
import torch.nn as nn
import torch.utils.model_zoo as model_zoo
__all__ = [
'VGG', 'vgg11', 'vgg11_bn', 'vgg13', 'vgg13_bn', 'vgg16', 'vgg16_bn',
'vgg19_bn', 'vgg19',
]
model_urls = {
'vgg11': 'https://download.pytorch.org/models/vgg11-bbd30ac9.pth',
'vgg13': 'https://download.pytorch.o... | 6,791 | 31.037736 | 113 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/bi_modal_resnet_module.py | # import torch
import torch.nn as nn
# import torch.utils.model_zoo as model_zoo
# consider add pre-train weight
# model_urls = {'resnet18': 'https://download.pytorch.org/models/resnet18-5c106cde.pth'}
def vis_conv3x3(in_planes, out_planes, stride=1):
"""3x3 convolution with padding"""
return nn.Conv2d(in_pla... | 5,952 | 35.975155 | 117 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/nonlocal_helper.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
"""Non-local helper"""
import torch
import torch.nn as nn
class Nonlocal(nn.Module):
"""
Builds Non-local Neural Networks as a generic family of building
blocks for capturing long-range dependencies. Non-local... | 5,418 | 35.369128 | 80 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/stem_helper.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
"""ResNe(X)t 3D stem helper."""
import torch.nn as nn
def get_stem_func(name):
"""
Retrieves the stem module by name.
"""
trans_funcs = {"x3d_stem": X3DStem, "basic_stem": ResNetBasicStem}
assert (
... | 10,775 | 32.362229 | 102 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/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
def c2_xavier_fill(module: nn.Module) -> None:
"""
Initialize `module.weight` using the "XavierFill" implemented in Caffe2.
Also initializ... | 3,741 | 34.980769 | 82 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/se_resnet.py | import torch
import torch.nn as nn
from torch.hub import load_state_dict_from_url
from dpcv.modeling.module.resnet_tv import ResNet
class SELayer(nn.Module):
def __init__(self, channel, reduction=16):
super(SELayer, self).__init__()
self.avg_pool = nn.AdaptiveAvgPool2d(1) # squeeze
sel... | 5,970 | 30.098958 | 115 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/resnet_helper.py | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
"""Video models."""
import torch
import torch.nn as nn
from dpcv.tools.common import drop_path
from dpcv.modeling.module.nonlocal_helper import Nonlocal
from dpcv.modeling.module.operators import SE, Swish
def get_trans_... | 24,800 | 33.161157 | 83 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/tpn/base.py | import logging
from abc import ABCMeta, abstractmethod
import torch.nn as nn
class BaseRecognizer(nn.Module):
"""Base class for recognizers"""
__metaclass__ = ABCMeta
def __init__(self):
super(BaseRecognizer, self).__init__()
@property
def with_tenon_list(self):
return hasattr(... | 1,158 | 26.595238 | 76 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/tpn/simple_spatial_module.py | import torch.nn as nn
class SimpleSpatialModule(nn.Module):
def __init__(self, spatial_type='avg', spatial_size=7):
super(SimpleSpatialModule, self).__init__()
assert spatial_type in ['avg']
self.spatial_type = spatial_type
self.spatial_size = spatial_size if not isinstance(spati... | 586 | 26.952381 | 111 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/tpn/cls_head_module.py | import torch
import torch.nn as nn
import torch.nn.functional as F
class ClsHead(nn.Module):
"""Simplest classification head"""
def __init__(self,
with_avg_pool=True,
temporal_feature_size=1,
spatial_feature_size=7,
dropout_ratio=0.8,
... | 2,900 | 33.535714 | 120 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/tpn/tpn.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv import Config
import numpy as np
def xavier_init(module, gain=1, bias=0, distribution='normal'):
assert distribution in ['uniform', 'normal']
if hasattr(module, 'weight') and module.weight is not None:
if distribution == 'uni... | 12,418 | 34.584527 | 123 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/tpn/resnet_mm.py | import logging
import torch.nn as nn
import torch.utils.checkpoint as cp
from dpcv.checkpoint.load import load_checkpoint
import torch
def constant_init(module, val, bias=0):
if hasattr(module, 'weight') and module.weight is not None:
nn.init.constant_(module.weight, val)
if hasattr(module, 'bias') an... | 12,608 | 33.263587 | 114 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/module/tpn/simple_consensus.py | import torch
import torch.nn as nn
class _SimpleConsensus(torch.autograd.Function):
"""Simplest segmental consensus module"""
@staticmethod
def forward(ctx, x, dim, consensus_type):
ctx.save_for_backward(x, dim, consensus_type)
if consensus_type == 'avg':
output = x.mean(dim=d... | 1,088 | 26.225 | 75 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/loss/pers_emo_loss.py | import torch
import torch.nn.functional as F
from .build import LOSS_FUNC_REGISTRY
def per_emo_loss(p_score, p_label, e_score, e_label, p_co, e_co, x_ep, use_adv=False):
p_mark = torch.cat([torch.ones((p_co.shape[0], 1)), torch.zeros((p_co.shape[0], 1))], 1).cuda()
e_mark = torch.cat([torch.zeros((e_co.shape[... | 1,984 | 43.111111 | 110 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/loss/common.py | import torch.nn as nn
from .build import LOSS_FUNC_REGISTRY
@LOSS_FUNC_REGISTRY.register()
def mean_square_error():
return nn.MSELoss()
@LOSS_FUNC_REGISTRY.register()
def l1_loss():
return nn.L1Loss()
@LOSS_FUNC_REGISTRY.register()
def smooth_l1_loss():
return nn.SmoothL1Loss() | 296 | 16.470588 | 37 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/loss/label_smooth.py | import numpy as np
import torch
import torch.nn.functional as F
import torch.nn as nn
class LabelSmoothLoss(nn.Module):
"""
@author: https://github.com/TingsongYu
"""
def __init__(self, smoothing=0.0):
super(LabelSmoothLoss, self).__init__()
self.smoothing = smoothing
def forward(... | 979 | 28.69697 | 86 | py |
DeepPersonality | DeepPersonality-main/dpcv/modeling/loss/cr_loss.py | import torch
import torch.nn as nn
from .build import LOSS_FUNC_REGISTRY
def one_hot_CELoss(pred, label):
bs = label.size(0)
log_prob = torch.log_softmax(pred, dim=1)
loss = -torch.sum(log_prob * label) / bs
return loss
class BellLoss:
def __init__(self, gama=300, theta=9):
self.gama = t... | 1,447 | 25.814815 | 80 | py |
DeepPersonality | DeepPersonality-main/script/run_exp.py | #! /usr/bin/env python
import sys
import os
current_path = os.path.dirname(os.path.abspath(__file__))
work_path = os.path.join(current_path, "../")
sys.path.append(work_path)
from dpcv.tools.common import parse_args
from dpcv.config.default_config_opt import cfg, cfg_from_file, cfg_from_list
# from torch.utils.tensor... | 1,100 | 21.02 | 76 | py |
DeepPersonality | DeepPersonality-main/script/cmp_multi_modal_post_fusion.py | import torch
import os
import numpy as np
from dpcv.evaluation.metrics import compute_pcc, compute_ccc
import logging
import argparse
class CmpPostFusion:
def __init__(self, visual_data_path, audio_data_path, label_data_path, addition_data_path=None):
logger.info(f" ================ {os.path.dirname(visua... | 2,942 | 34.890244 | 105 | py |
simpa | simpa-master/simpa_tests/automatic_tests/TestProcessing.py | """
SPDX-FileCopyrightText: 2021 Computer Assisted Medical Interventions Group, DKFZ
SPDX-FileCopyrightText: 2021 VISION Lab, Cancer Research UK Cambridge Institute (CRUK CI)
SPDX-License-Identifier: MIT
"""
from simpa.core.reconstruction_module.reconstruction_utils import apply_b_mode, get_apodization_factor, \
r... | 4,734 | 50.467391 | 119 | py |
simpa | simpa-master/simpa_tests/manual_tests/DelayMultiplyAndSumReconstruction.py | """
SPDX-FileCopyrightText: 2021 Computer Assisted Medical Interventions Group, DKFZ
SPDX-FileCopyrightText: 2021 VISION Lab, Cancer Research UK Cambridge Institute (CRUK CI)
SPDX-License-Identifier: MIT
"""
from simpa.utils import Tags
from simpa.utils.dict_path_manager import generate_dict_path
from simpa.io_handlin... | 3,414 | 49.220588 | 134 | py |
simpa | simpa-master/simpa_tests/manual_tests/DelayAndSumReconstruction.py | """
SPDX-FileCopyrightText: 2021 Computer Assisted Medical Interventions Group, DKFZ
SPDX-FileCopyrightText: 2021 VISION Lab, Cancer Research UK Cambridge Institute (CRUK CI)
SPDX-License-Identifier: MIT
"""
from simpa.utils import Tags
from simpa.utils.dict_path_manager import generate_dict_path
from simpa.io_handl... | 3,482 | 47.375 | 118 | py |
simpa | simpa-master/simpa_tests/manual_tests/SignedDelayMultiplyAndSumReconstruction.py | """
SPDX-FileCopyrightText: 2021 Computer Assisted Medical Interventions Group, DKFZ
SPDX-FileCopyrightText: 2021 VISION Lab, Cancer Research UK Cambridge Institute (CRUK CI)
SPDX-License-Identifier: MIT
"""
from simpa.utils import Tags
from simpa.utils.dict_path_manager import generate_dict_path
from simpa.io_handlin... | 3,681 | 51.6 | 118 | py |
simpa | simpa-master/simpa/__init__.py | """
SPDX-FileCopyrightText: 2021 Computer Assisted Medical Interventions Group, DKFZ
SPDX-FileCopyrightText: 2021 VISION Lab, Cancer Research UK Cambridge Institute (CRUK CI)
SPDX-License-Identifier: MIT
"""
from .core.reconstruction_module.reconstruction_module_delay_and_sum_adapter import reconstruct_delay_and_sum_p... | 612 | 67.111111 | 149 | py |
simpa | simpa-master/simpa/core/reconstruction_module/reconstruction_utils.py | """
SPDX-FileCopyrightText: 2021 Computer Assisted Medical Interventions Group, DKFZ
SPDX-FileCopyrightText: 2021 VISION Lab, Cancer Research UK Cambridge Institute (CRUK CI)
SPDX-License-Identifier: MIT
"""
from simpa.utils import Tags
import torch
import torch.fft
import numpy as np
from scipy.signal import hilbert
... | 7,142 | 47.924658 | 115 | py |
simpa | simpa-master/simpa/core/reconstruction_module/reconstruction_module_delay_multiply_and_sum_adapter.py | """
SPDX-FileCopyrightText: 2021 Computer Assisted Medical Interventions Group, DKFZ
SPDX-FileCopyrightText: 2021 VISION Lab, Cancer Research UK Cambridge Institute (CRUK CI)
SPDX-License-Identifier: MIT
"""
from simpa.utils import Tags
from simpa.core.reconstruction_module import ReconstructionAdapterBase
from simpa.... | 13,987 | 58.021097 | 137 | py |
simpa | simpa-master/simpa/core/reconstruction_module/reconstruction_module_delay_and_sum_adapter.py | """
SPDX-FileCopyrightText: 2021 Computer Assisted Medical Interventions Group, DKFZ
SPDX-FileCopyrightText: 2021 VISION Lab, Cancer Research UK Cambridge Institute (CRUK CI)
SPDX-License-Identifier: MIT
"""
from simpa.utils import Tags
from simpa.core.reconstruction_module import ReconstructionAdapterBase
from simpa.... | 13,489 | 56.649573 | 137 | py |
simpa | simpa-master/simpa/core/reconstruction_module/reconstruction_module_signed_delay_multiply_and_sum_adapter.py | """
SPDX-FileCopyrightText: 2021 Computer Assisted Medical Interventions Group, DKFZ
SPDX-FileCopyrightText: 2021 VISION Lab, Cancer Research UK Cambridge Institute (CRUK CI)
SPDX-License-Identifier: MIT
"""
from simpa.utils import Tags
from simpa.core.reconstruction_module import ReconstructionAdapterBase
from simpa.... | 14,009 | 56.892562 | 125 | py |
simpa | simpa-master/simpa/utils/tags.py | """
SPDX-FileCopyrightText: 2021 Computer Assisted Medical Interventions Group, DKFZ
SPDX-FileCopyrightText: 2021 VISION Lab, Cancer Research UK Cambridge Institute (CRUK CI)
SPDX-License-Identifier: MIT
"""
import numpy as np
class Tags:
"""
This class contains all 'Tags' for the use in the settings diction... | 43,421 | 32.171887 | 125 | py |
RandStainNA | RandStainNA-master/main.py | import os
from randstainna import RandStainNA
import cv2
if __name__ == "__main__":
"""
Usage1: Demo(for visualization)
"""
# # Setting: is_train = False
# randstainna = RandStainNA(
# yaml_file = './randstainna/CRC_LAB_randomTrue_n0.yaml',
# std_hyper = 0.0,
# distribution... | 1,455 | 26.471698 | 79 | py |
RandStainNA | RandStainNA-master/stain_augmentation.py | import PIL.Image as Image
import os
from torchvision import transforms as transforms
img_path_list = [
"./visualization/origin/TUM-AEPINLNQ.png",
"./visualization/origin/TUM-DFGFFNEY.png",
"./visualization/origin/TUM-EWFNFSQL.png",
"./visualization/origin/TUM-TCGA-CVATFAAT.png",
]
save_dir_path = "./v... | 733 | 30.913043 | 77 | py |
RandStainNA | RandStainNA-master/stain_normalization.py | import PIL.Image as Image
import os
from torchvision import transforms as transforms
import cv2
import numpy as np
from skimage import color
def quick_loop(image, image_avg, image_std, temp_avg, temp_std, isHed=False):
image = (image - np.array(image_avg)) * (
np.array(temp_std) / np.array(image_std)
... | 3,843 | 31.854701 | 83 | py |
RandStainNA | RandStainNA-master/classification/inference.py | #!/usr/bin/env python3
"""PyTorch Inference Script
An example inference script that outputs top-k class ids for images in a folder into a csv.
Hacked together by / Copyright 2020 Ross Wightman (https://github.com/rwightman)
"""
import os
import time
import argparse
import logging
import numpy as np
import torch
from... | 5,235 | 39.90625 | 137 | py |
RandStainNA | RandStainNA-master/classification/benchmark.py | #!/usr/bin/env python3
""" Model Benchmark Script
An inference and train step benchmark script for timm models.
Hacked together by Ross Wightman (https://github.com/rwightman)
"""
import argparse
import os
import csv
import json
import time
import logging
import torch
import torch.nn as nn
import torch.nn.parallel
fr... | 24,750 | 39.978477 | 137 | py |
RandStainNA | RandStainNA-master/classification/setup.py | """ Setup
"""
from setuptools import setup, find_packages
from codecs import open
from os import path
here = path.abspath(path.dirname(__file__))
# Get the long description from the README file
with open(path.join(here, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
exec(open('timm/version.py'... | 1,772 | 35.183673 | 78 | py |
RandStainNA | RandStainNA-master/classification/hubconf.py | dependencies = ['torch']
from timm.models import registry
globals().update(registry._model_entrypoints)
| 105 | 20.2 | 45 | py |
RandStainNA | RandStainNA-master/classification/validate.py | #!/usr/bin/env python3
""" ImageNet Validation Script
This is intended to be a lean and easily modifiable ImageNet validation script for evaluating pretrained
models or training checkpoints against ImageNet or similarly organized image datasets. It prioritizes
canonical PyTorch, standard Python style, and good perform... | 15,574 | 42.997175 | 137 | py |
RandStainNA | RandStainNA-master/classification/clean_checkpoint.py | #!/usr/bin/env python3
""" Checkpoint Cleaning Script
Takes training checkpoints with GPU tensors, optimizer state, extra dict keys, etc.
and outputs a CPU tensor checkpoint with only the `state_dict` along with SHA256
calculation for model zoo compatibility.
Hacked together by / Copyright 2020 Ross Wightman (https:... | 3,229 | 38.876543 | 102 | py |
RandStainNA | RandStainNA-master/classification/avg_checkpoints.py | #!/usr/bin/env python3
""" Checkpoint Averaging Script
This script averages all model weights for checkpoints in specified path that match
the specified filter wildcard. All checkpoints must be from the exact same model.
For any hope of decent results, the checkpoints should be from the same or child
(via resumes) tr... | 4,772 | 38.122951 | 107 | py |
RandStainNA | RandStainNA-master/classification/train_origin.py | #!/usr/bin/env python3
""" ImageNet Training Script
This is intended to be a lean and easily modifiable ImageNet training script that reproduces ImageNet
training results with some of the latest networks and training techniques. It favours canonical PyTorch
and standard Python style over trying to be able to 'do it al... | 40,586 | 47.607186 | 137 | py |
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