python_code stringlengths 0 4.04M | repo_name stringlengths 8 58 | file_path stringlengths 5 147 |
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# Copyright (c) Facebook, Inc. and its affiliates.
import argparse
import numpy as np
import os
import torch
from torch import nn
from torch.autograd import Variable
import torchvision
import utils.modelZoo as modelZoo
from utils.load_utils import *
DATA_PATHS = {
#'video_data/Oliver/train/':1,
#'vide... | body2hands-main | train_gan.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import argparse
import os
import json
import numpy as np
import torch
import torchvision
from torch import nn
from torch.autograd import Variable
import utils.modelZoo as modelZoo
from utils.load_utils import *
def main(args):
## variable initializations
devi... | body2hands-main | sample.py |
import tensorflow as tf
import os
import sys
from nets.CPM import CPM
from data.DomeReader import DomeReader
from data.TsimonDBReader import TsimonDBReader
from data.RHDReader import RHDReader
from data.STBReader import STBReader
from data.MultiDataset import combineMultiDataset
from data.GAneratedReader import GAnera... | body2hands-main | visualization/POF/training_PAF_hand.py |
import os
import numpy as np
import numpy.linalg as nl
import json
import pickle
import argparse
map_body25_to_body19 = list(range(8)) + list(range(9, 25)) # total of 24
parser = argparse.ArgumentParser()
parser.add_argument('--seqName', '-n', type=str)
parser.add_argument('--rootDir', '-r', type=str)
parser.add_arg... | body2hands-main | visualization/POF/collect_openpose.py |
import tensorflow as tf
import os
import sys
from nets.CPM import CPM
from nets.Hourglass import Hourglass
from data.DomeReader import DomeReader
from data.HumanReader import HumanReader
from data.MultiDataset import combineMultiDataset
from data.COCOReader import COCOReader
import pickle
import utils.general
import ... | body2hands-main | visualization/POF/training_e2e_PAF.py |
from __future__ import print_function, unicode_literals
import tensorflow as tf
import numpy as np
import numpy.linalg as nl
import matplotlib.pyplot as plt
import matplotlib.patches
from mpl_toolkits.mplot3d import Axes3D
import argparse
import cv2
import os
from time import time
import json
from nets.CPM import CPM
... | body2hands-main | visualization/POF/save_total_sequence.py |
import tensorflow as tf
import pickle
import os
from utils.ops import NetworkOps as ops
class handSegNet:
def __init__(self):
pass
def init_sess(self, sess):
file_name = './weights/handsegnet-rhd.pickle'
exclude_var_list = []
assert os.path.exists(file_name), "File not found."... | body2hands-main | visualization/POF/utils/handSegNet.py |
import tensorflow as tf
import numpy as np
import numpy.linalg as nl
import utils.general
import skimage.feature
import json
import os
PAF_type = 0
allPAFConnection = [[np.array([[1, 8], [8, 9], [9, 10], [1, 11], [11, 12], [12, 13], [1, 2], [2, 3], [3, 4], [2, 16], [1, 5], [5, 6], [6, 7], [5, 17], [1, 0], [0, 14], [0,... | body2hands-main | visualization/POF/utils/PAF.py |
import numpy as np
def transReProjectionLoss(t, X0, K, uv):
assert t.shape == (3,)
assert len(X0.shape) == 2 and X0.shape[1] == 3
assert K.shape == (3, 3)
assert len(uv.shape) == 2 and uv.shape[1] == 2
X = X0 + t[np.newaxis, :]
x = X.dot(K.T)
x /= x[:, 2][:, np.newaxis]
return np.sum... | body2hands-main | visualization/POF/utils/optimization.py |
import tensorflow as tf
from tensorflow.python import pywrap_tensorflow
def load_weights_from_snapshot(session, checkpoint_path, discard_list=None, rename_dict=None):
""" Loads weights from a snapshot except the ones indicated with discard_list. Others are possibly renamed. """
reader = pywrap_tensorf... | body2hands-main | visualization/POF/utils/load_ckpt.py |
import tensorflow as tf
import json
import numpy as np
class AdamModel(object):
num_shape_coeff = 30
num_vertices = 18540
num_joints = 62
def __init__(self):
# read in model file
model_file = 'utils/adam_v1_plus2.json'
with open(model_file) as f:
model_data = json... | body2hands-main | visualization/POF/utils/AdamModel.py |
import tensorflow as tf
import math
import numpy as np
class NetworkOps(object):
""" Operations that are frequently used within networks. """
neg_slope_of_relu = 0.01
@classmethod
def leaky_relu(cls, tensor, name='relu'):
out_tensor = tf.maximum(tensor, cls.neg_slope_of_relu * tensor, name=na... | body2hands-main | visualization/POF/utils/ops.py |
from utils.AdamModel import AdamModel
from utils.PAF import PAFConnection
import tensorflow as tf
import numpy as np
import json
if __name__ == '__main__':
adam = AdamModel()
adam_joints = adam.reconstruct()
sess = tf.Session()
V_vec, joints_v = sess.run([adam.mean_shape, adam_joints])
sess.close()... | body2hands-main | visualization/POF/utils/default_PAF_length.py |
import numpy as np
def calc_auc(x, y):
""" Given x and y values it calculates the approx. integral and normalizes it: area under curve"""
integral = np.trapz(y, x)
norm = np.trapz(np.ones_like(y), x)
return integral / norm
class EvalUtil:
""" Util class for evaluation networks.
"""
def _... | body2hands-main | visualization/POF/utils/EvalUtil.py |
# Don't use anaconda for this
import ctypes
import os
from PIL import Image, ImageOps
import matplotlib.pyplot as plt
import numpy as np
class wrapper_hand_model(object):
def __init__(self, lib_file='./utils/libPythonWrapper.so', model_file='./utils/hand2_l_all_uv.json'):
self.lib = ctypes.cdll.LoadLibrar... | body2hands-main | visualization/POF/utils/wrapper_hand_model.py |
import numpy as np
from math import factorial
def savitzky_golay(y, window_size, order, deriv=0, rate=1):
r"""Smooth (and optionally differentiate) data with a Savitzky-Golay filter.
The Savitzky-Golay filter removes high frequency noise from data.
It has the advantage of preserving the original shape and... | body2hands-main | visualization/POF/utils/smoothing.py |
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.widgets import Slider
import utils.general
class vis_heatmap3d(object):
def __init__(self, fig, ax, heatmap, keypoints=None, type_str=None):
assert len(heatmap.shape) == 4
self.fig = fig
... | body2hands-main | visualization/POF/utils/vis_heatmap3d.py |
import tensorflow as tf
def average_gradients(tower_grads):
average_grads = []
for grad_and_vars in zip(*tower_grads):
# Note that each grad_and_vars looks like the following:
# ((grad0_gpu0, var0_gpu0), ... , (grad0_gpuN, var0_gpuN))
grads = []
for g, _ in grad_and_vars:
... | body2hands-main | visualization/POF/utils/multigpu.py |
import ctypes
from PIL import Image, ImageOps
import numpy as np
class meshWrapper(object):
def __init__(self, lib_file='./utils/libPythonWrapper.so'):
self.lib = ctypes.cdll.LoadLibrary(lib_file)
# extern "C" void load_totalmodel(char* obj_file, char* model_file, char* pca_file);
self.li... | body2hands-main | visualization/POF/utils/meshWrapper.py |
import tensorflow as tf
import numpy as np
import numpy.linalg as nl
import cv2
# in A4 order (SMC)
tbody_connMat = np.array([0, 1, 0, 3, 3, 4, 4, 5, 0, 9, 9, 10, 10, 11, 0, 2, 2, 6, 6, 7, 7, 8, 2, 12, 12, 13, 13, 14, 1, 15, 15, 16, 1, 17, 17, 18, 0, 19, 0, 20, 20, 12, 20, 6])
thand_connMat = np.array([0, 1, 1, 2, 2, ... | body2hands-main | visualization/POF/utils/general.py |
import numpy as np
import numpy.linalg as nl
from utils.general import connMat
a4_to_main = {
'body': np.array([1, 0, 9, 10, 11, 3, 4, 5, 12, 13, 14, 6, 7, 8, 17, 15, 18, 16, 19, 20], dtype=np.int64), # convert to order of openpose
'1_body': np.array([1, 0, 9, 10, 11, 3, 4, 5, 12, 13, 14, 6, 7, 8, 17, 15, 18,... | body2hands-main | visualization/POF/utils/keypoint_conversion.py |
import tensorflow as tf
from utils.ops import NetworkOps
import numpy as np
ops = NetworkOps
class CPM(object):
# The original CPM: set input image to right hand, BGR channel order (OpenCV), image scale to x / 256.0 - 0.5, output channel number to 22 (the last one for background)
def __init__(self, crop_siz... | body2hands-main | visualization/POF/nets/CPM.py |
import tensorflow as tf
from data.BaseReader import BaseReader
import numpy as np
class TempConstReader(BaseReader):
crop_scale_noise_sigma = 0.1
crop_offset_noise_sigma = 0.1
def __init__(self, objtype=0, shuffle=False, batch_size=1, crop_noise=False):
super(TempConstReader, self).__init__(objty... | body2hands-main | visualization/POF/data/TempConstReader.py |
# Run this script with OpenCV2
import cv2
import numpy as np
import os
import json
source_dir = '/media/posefs3b/Users/gines/mpii_mask'
target_dir = '/media/posefs3b/Users/donglaix/mpii_mask'
if __name__ == '__main__':
path_to_db = './MPII_collected.json'
with open(path_to_db) as f:
db_data = json.loa... | body2hands-main | visualization/POF/data/process_MPII_mask.py |
import tensorflow as tf
import numpy as np
import utils.general
class BaseReader(object):
# BaseReader is a virual base class to be inherited by other data readers which provide data by calling register_tensor
crop_size_zoom = 1.5
crop_size_zoom_2d = 1.8
crop_size = 368
grid_size = crop_size // 8... | body2hands-main | visualization/POF/data/BaseReader.py |
import tensorflow as tf
from data.BaseReader import BaseReader
import numpy as np
import h5py
from utils.keypoint_conversion import human36m_to_main, mpi3d_to_main, SMPL_to_main
import pickle
import os
class HumanReader(BaseReader):
def __init__(self, name='Human3.6M', mode='training', objtype=0, shuffle=True, b... | body2hands-main | visualization/POF/data/HumanReader.py |
import tensorflow as tf
from data.BaseReader import BaseReader
import numpy as np
class Base2DReader(BaseReader):
# inherit from BaseReader, implement different 2D cropping (cropping from 2D)
def __init__(self, objtype=0, shuffle=True, batch_size=1, crop_noise=False):
super(Base2DReader, self).__init... | body2hands-main | visualization/POF/data/Base2DReader.py |
import tensorflow as tf
from data.TempConstReader import TempConstReader
import numpy as np
import numpy.linalg as nl
import pickle
from utils.keypoint_conversion import a4_to_main as order_dict
import json
import os
class DomeReaderTempConst(TempConstReader):
def __init__(self, mode='training', objtype=0, shuff... | body2hands-main | visualization/POF/data/DomeReaderTempConst.py |
import os
import numpy as np
import numpy.linalg as nl
import json
import pickle
map_body25_to_body19 = list(range(8)) + list(range(9, 25)) # total of 24
seqName = 'Dexter_Grasp2'
# root = '/home/donglaix/Documents/Experiments/{}'.format(seqName)
root = '/media/posefs1b/Users/donglaix/siggasia018/{}/'.format(seqName... | body2hands-main | visualization/POF/data/collect_openpose.py |
import tensorflow as tf
class MultiDataset(object):
# A class to combine multi dataset input
def __init__(self, db_list):
assert type(db_list) == list and len(db_list) >= 1
self.db_list = db_list
def get(self, name_wanted):
data_list = []
for i, db in enumerate(self.db_li... | body2hands-main | visualization/POF/data/MultiDataset.py |
import tensorflow as tf
import os
import numpy as np
from data.BaseReader import BaseReader
import pickle
from data.collect_stb import PATH_TO_DATASET, K, Rl, Rr, tl, tr, TRAIN_SEQS, TEST_SEQS
from utils.keypoint_conversion import STB_to_main
class STBReader(BaseReader):
def __init__(self, mode='training', objtyp... | body2hands-main | visualization/POF/data/STBReader.py |
import tensorflow as tf
from data.BaseReader import BaseReader
import numpy as np
import numpy.linalg as nl
import pickle
from utils.keypoint_conversion import a4_to_main as order_dict
import json
import os
class DomeReader(BaseReader):
def __init__(self, mode='training', objtype=0, shuffle=False, batch_size=1, ... | body2hands-main | visualization/POF/data/DomeReader.py |
import tensorflow as tf
import os
import numpy as np
import json
from data.Base2DReader import Base2DReader
from utils.keypoint_conversion import COCO_to_main, MPII_to_main
class COCOReader(Base2DReader):
def __init__(self, name='COCO', mode='training', objtype=0, shuffle=True, batch_size=1, crop_noise=False):
... | body2hands-main | visualization/POF/data/COCOReader.py |
import pickle
from scipy.io import loadmat
import os
import numpy as np
PATH_TO_DATASET = '/media/posefs0c/Users/donglaix/Experiments/StereoHandTracking/'
TEST_SEQS = ['B1Counting', 'B1Random']
TRAIN_SEQS = ['B2Counting', 'B2Random', 'B3Counting', 'B3Random', 'B4Counting', 'B4Random', 'B5Counting', 'B5Random', 'B6Coun... | body2hands-main | visualization/POF/data/collect_stb.py |
import tensorflow as tf
from data.Base2DReader import Base2DReader
import os
import pickle
import numpy as np
from utils.keypoint_conversion import GAnerated_to_main as order_dict
class GAneratedReader(Base2DReader):
def __init__(self, mode='training', objtype=1, shuffle=False, batch_size=1, crop_noise=False):
... | body2hands-main | visualization/POF/data/GAneratedReader.py |
import pickle
import os
import numpy as np
from utils.general import plot2d_cv2
import cv2
map_index = np.array([0, 4, 3, 2, 1, 8, 7, 6, 5, 12, 11, 10, 9, 16, 15, 14, 13, 20, 19, 18, 17], dtype=int)
def project(joints, K, R=None, t=None, distCoef=None):
""" Perform Projection.
joints: N * 3
"""
x... | body2hands-main | visualization/POF/data/collect_crop_hand.py |
import tensorflow as tf
import numpy as np
import json
from data.Base2DReader import Base2DReader
import os
from utils.keypoint_conversion import tsimon_to_main as order_dict
class TsimonDBReader(Base2DReader):
def __init__(self, mode='training', objtype=1, shuffle=False, batch_size=1, crop_noise=False):
... | body2hands-main | visualization/POF/data/TsimonDBReader.py |
import tensorflow as tf
import pickle
from data.BaseReader import BaseReader
import os
import numpy as np
class RHDReader(BaseReader):
def __init__(self, mode='training', objtype=1, shuffle=False, batch_size=1, crop_noise=False):
assert objtype == 1
super(RHDReader, self).__init__(objtype, shuffle... | body2hands-main | visualization/POF/data/RHDReader.py |
import os
import pickle
import json
import numpy as np
def load_calib_file(calib_file):
assert os.path.isfile(calib_file)
with open(calib_file) as f:
calib = json.load(f)
for key in calib:
if type(calib[key]) == list:
calib[key] = np.array(calib[key])
return calib
"""
###... | body2hands-main | visualization/POF/data/collect_a4.py |
import tensorflow as tf
from data.BaseReader import BaseReader
import numpy as np
import pickle
from utils.keypoint_conversion import a4_to_main as order_dict
import json
import os
class OpenposeReader(BaseReader):
def __init__(self, seqName, mode='evaluation', objtype=0, shuffle=False, batch_size=1, crop_noise=... | body2hands-main | visualization/POF/data/OpenposeReader.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import os
import sys
import numpy as np
import scipy.io as io
rng = np.random.RandomState(23456)
import torch
import torchvision
from torch import nn
from torch.autograd import Variable
from torch.utils.data import DataLoader
from torchvision.utils import save_image
... | body2hands-main | utils/modelZoo.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import json
import numpy as np
import os, sys
import scipy
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d, Axes3D
from scipy.spatial.transform import Rotation as R
from shutil import copyfile
from PIL import Image,ImageDraw
from torchvision i... | body2hands-main | utils/load_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
import argparse
import os
import json
import numpy as np
import torch
import torchvision
from torch import nn
from torch.autograd import Variable
import pickle
import utils.modelZoo as modelZoo
from utils.load_utils import *
ARMS_ONLY = [13,14,16,17,18,19] #arms for ... | body2hands-main | smplx_plugin/demo.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#%%
import json
import time
try:
from eval_server_common import connect_to_redis
except ImportError:
print("HINT:... | codraw-models-master | eval_run_bots.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#%%
import numpy as np
from pathlib import Path
import torch
import torch.cuda
import torch.nn as nn
import torch.nn.func... | codraw-models-master | baseline4_models.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
"""
An event-based view of the CoDraw dataset
"""
#%%
import numpy as np
from pathlib import Path
import json
from enum i... | codraw-models-master | codraw_data.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
"""
Multi-headed attention implementation
"""
#%%
import numpy as np
import torch
import torch.cuda
import torch.nn as n... | codraw-models-master | attention.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#%%
import numpy as np
from pathlib import Path
import heapq
import torch
import torch.cuda
import torch.nn as nn
import ... | codraw-models-master | baseline2_models.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from interactivity import INTERACTIVE, try_magic, try_cd
try_cd('~/dev/drawmodel/nkcodraw')
#%%
import numpy as np
from p... | codraw-models-master | baseline4_eval.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from interactivity import INTERACTIVE, try_magic, try_cd
try_cd('~/dev/drawmodel/nkcodraw')
#%%
assert __name__ == "__mai... | codraw-models-master | baseline1_train.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
def scene_similarity_orig(pred, target):
"""
DEPRECATED: use scene_similarity instead!
Thi... | codraw-models-master | abs_metric.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
try:
from IPython.display import display
except ImportError:
assert not INTERACTIVE
def display(*args, **kwargs... | codraw-models-master | episode.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import redis
REDIS_HOST = 'localhost'
REDIS_PORT = 6379
REDIS_PASSWORD = 'YOUR PASSWORD HERE'
REDIS_CONNECTION = None
de... | codraw-models-master | example.eval_server_common.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
__all__ = ['cpu', 'cuda_if_available', 'logsumexp', 'torch_load']
import torch
# %%
cpu = torch.device('cpu')
if torch.... | codraw-models-master | nkfb_util.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#%%
import numpy as np
from pathlib import Path
import torch
import torch.cuda
import torch.nn as nn
import torch.nn.func... | codraw-models-master | baseline3_models.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
from pathlib import Path
import editdistance
from collections import Counter
import torch
import torch.... | codraw-models-master | datagen.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#%%
def load_models(*partitions):
if not partitions:
partitions = (1, 2, 3, 4)
models = {}
if 1 in p... | codraw-models-master | saved_models.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
"""
Provides the Packer class, which is useful for managing a hierarchy where each
batch element has a variable number of c... | codraw-models-master | packer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
from pathlib import Path
import editdistance
import torch
import torch.cuda
import torch.nn as nn
impor... | codraw-models-master | model.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from interactivity import INTERACTIVE, try_magic, try_cd
try_cd('~/dev/drawmodel/nkcodraw')
#%%
import json
import numpy a... | codraw-models-master | eval_transcripts.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from interactivity import INTERACTIVE, try_magic, try_cd
try_cd('~/dev/drawmodel/nkcodraw')
#%%
import numpy as np
from p... | codraw-models-master | baseline2_eval.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from pathlib import Path
from IPython.display import SVG, display
from PIL import Image
from binascii import b2a_base64
PN... | codraw-models-master | abs_render.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from interactivity import INTERACTIVE, try_magic, try_cd
try_cd('~/dev/drawmodel/nkcodraw')
#%%
assert __name__ == "__mai... | codraw-models-master | baseline2_train.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from interactivity import INTERACTIVE, try_magic, try_cd
try_cd('~/dev/drawmodel/nkcodraw')
#%%
assert __name__ == "__mai... | codraw-models-master | baseline3_train.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from interactivity import INTERACTIVE, try_magic, try_cd
try_cd('~/dev/drawmodel/nkcodraw')
#%%
import numpy as np
from p... | codraw-models-master | eval_automatic.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from interactivity import INTERACTIVE, try_magic, try_cd
try_cd('~/dev/drawmodel/nkcodraw')
#%%
import numpy as np
from p... | codraw-models-master | baseline3_eval.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
"""
Abstract Scene (abs) utilities copied from the original CoDraw codebase
"""
import math
import torch
from torch.autogr... | codraw-models-master | abs_util_orig.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from interactivity import INTERACTIVE, try_magic, try_cd
try_cd('~/dev/drawmodel/nkcodraw')
#%%
import numpy as np
from p... | codraw-models-master | baseline1_eval.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
try:
get_ipython()
INTERACTIVE=True
except:
INTERACTIVE=False
def try_magic(*args, **kwargs):
if not INTER... | codraw-models-master | interactivity.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
"""
Scene-level nearest-neighbor teller
"""
from interactivity import INTERACTIVE, try_magic, try_cd
try_cd('~/dev/drawmod... | codraw-models-master | exp28_scenenn.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#%%
import numpy as np
from pathlib import Path
import editdistance
import torch
import torch.cuda
import torch.nn as nn
... | codraw-models-master | baseline1_models.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from interactivity import INTERACTIVE, try_magic, try_cd
try_cd('~/dev/drawmodel/nkcodraw')
#%%
assert __name__ == "__mai... | codraw-models-master | baseline4_train.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import ast
from itertools import chain
import logging
import math
import os
import sys
import json
import hashlib
import ed... | av_hubert-main | avhubert/infer_s2s.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from argparse import Namespace
import contextlib
import copy
import math
import numpy as np
import torch
import torch.nn as... | av_hubert-main | avhubert/decoder.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import logging
import os, glob
import sys
from typing import Dict, List, Optional, Tuple
import numpy as np
from dataclas... | av_hubert-main | avhubert/hubert_pretraining.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from .hubert import * # noqa
from .hubert_asr import * # noqa
from .hubert_dataset import *
from .hubert_pretraining import *
from .hubert_c... | av_hubert-main | avhubert/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import math
from typing import Dict, List, Optional
import sys
import torch
import torch.nn as nn
from fairseq import sear... | av_hubert-main | avhubert/sequence_generator.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import math
import re
from dataclasses import dataclass, field
from typing import List, Optional
import torch
import torch... | av_hubert-main | avhubert/hubert_criterion.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import logging
import math
import torch.nn as nn
import pdb
logger = logging.getLogger(__name__)
def conv3x3(in_planes, ... | av_hubert-main | avhubert/resnet.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import sys,logging
import contextlib
import tempfile
from argparse import Namespace
from typing import Any, Optional
impor... | av_hubert-main | avhubert/hubert_asr.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import cv2
import torch
import random
import numpy as np
from typing import Dict, List, Optional, Tuple
def load_video(pat... | av_hubert-main | avhubert/utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import itertools
import logging
import os
import sys
import time
from typing import Any, List, Optional, Union
import nump... | av_hubert-main | avhubert/hubert_dataset.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import os,sys
import logging
from typing import Dict, List, Optional, Tuple
import numpy as np
import torch
import torch.... | av_hubert-main | avhubert/hubert.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import sys
import argparse
import torch
from fairseq.data import Dictionary, encoders
def add_task_state(ckpt_path):
s... | av_hubert-main | avhubert/misc/fix_state.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import logging
import os
import sys
import numpy as np
import joblib
import torch
import tqdm
logging.basicConfig(
f... | av_hubert-main | avhubert/clustering/dump_km_label.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import logging
import math
import os
import sys
import fairseq
import soundfile as sf
import torch
import torch.nn.functio... | av_hubert-main | avhubert/clustering/dump_hubert_feature.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import os, subprocess
import submitit
import argparse
from argparse import Namespace
def dump_av_hubert(*args, **kwargs):
... | av_hubert-main | avhubert/clustering/submit_cluster.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import logging
import os
import sys
import numpy as np
from sklearn.cluster import MiniBatchKMeans
import joblib
logging... | av_hubert-main | avhubert/clustering/learn_kmeans.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import logging
import math
import os
import sys
import soundfile as sf
import torch
import torchaudio
import tqdm
from npy... | av_hubert-main | avhubert/clustering/dump_mfcc_feature.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import os
import glob
import shutil
import subprocess
from tqdm import tqdm
from pathlib import Path
from gen_subword impor... | av_hubert-main | avhubert/preparation/lrs3_manifest.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import os
import numpy as np
from scipy.io import wavfile
from tqdm import tqdm
def mix_audio(wav_fns):
wav_data = [wa... | av_hubert-main | avhubert/preparation/lrs3_noise.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import os, sys, glob, subprocess, json, math
import numpy as np
from scipy.io import wavfile
from os.path import basename, ... | av_hubert-main | avhubert/preparation/vox_prepare.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import cv2, math, os
import submitit
import tempfile
import shutil
from tqdm import tqdm
from scipy.io import wavfile
def ... | av_hubert-main | avhubert/preparation/count_frames_slurm.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import sys, os, glob, subprocess, shutil, math
from datetime import timedelta
import tempfile
from collections import Order... | av_hubert-main | avhubert/preparation/lrs3_prepare.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import sys,os,pickle,math
import cv2,dlib,time
import numpy as np
from tqdm import tqdm
def load_video(path):
videogen... | av_hubert-main | avhubert/preparation/detect_landmark.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import argparse
from tempfile import NamedTemporaryFile
import csv
from pathlib import Path
import zipfile
from functools i... | av_hubert-main | avhubert/preparation/gen_subword.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
## Based on: https://github.com/mpc001/Lipreading_using_Temporal_Convolutional_Networks/blob/master/preprocessing/crop_mout... | av_hubert-main | avhubert/preparation/align_mouth.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import math
import tempfile
import shutil
import submitit
import os, sys, subprocess, glob, re
import numpy as np
from coll... | av_hubert-main | avhubert/preparation/musan_prepare.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import math, time
import os, sys, subprocess, glob, re
import numpy as np
from collections import defaultdict
from scipy.io... | av_hubert-main | avhubert/preparation/noise_manifest.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import cv2, math, os
import tempfile
import shutil
from tqdm import tqdm
from scipy.io import wavfile
def count_frames(fid... | av_hubert-main | avhubert/preparation/count_frames.py |
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