python_code stringlengths 0 679k | repo_name stringlengths 9 41 | file_path stringlengths 6 149 |
|---|---|---|
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | modulus/launch/logging/launch.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | modulus/launch/logging/utils.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | test/utils/test_checkpoint.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | test/ci_tests/header_check.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | docs/conf.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/dlwp/era5_hdf5.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/dlwp/train_dlwp.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/dlwp/cube_sphere_plotter_no_subplots.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/dlwp/data_curation/data_download_simple.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/dlwp/data_curation/post_processing.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/graphcast/train_utils.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/graphcast/constants.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/graphcast/__init__.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/graphcast/train_graphcast.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/graphcast/train_base.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/graphcast/validation.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/graphcast/loss/__init__.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/graphcast/loss/utils.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/fcn_sfno/ensembler.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/fcn_sfno/models.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/fcn_sfno/inferencer.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/fcn_sfno/visualize.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/fcn_sfno/train.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/fcn_sfno/trainer.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/fcn_sfno/helpers.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/weather/fcn_afno/train_era5.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/gray_scott_rnn/gray_scott_rnn.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/navier_stokes_rnn/navier_stokes_rnn.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/ahmed_body_mgn/constants.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/ahmed_body_mgn/utils.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/ahmed_body_mgn/train.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/ahmed_body_mgn/inference.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/darcy_fno/validator.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/darcy_fno/train_fno_darcy.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/darcy_nested_fnos/train_nested_darcy.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/darcy_nested_fnos/generate_nested_darcy.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/darcy_nested_fnos/evaluate_nested_darcy.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/darcy_nested_fnos/utils.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/vortex_shedding_mgn/constants.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/vortex_shedding_mgn/train.py |
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | modulus-launch-main | examples/cfd/vortex_shedding_mgn/inference.py |
### Copyright (C) 2017 NVIDIA Corporation. All rights reserved.
### Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
import time
import os
import numpy as np
from collections import OrderedDict
from torch.autograd import Variable
from options.test_options import... | vid2vid-master | test.py |
### Copyright (C) 2017 NVIDIA Corporation. All rights reserved.
### Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
import time
import os
import torch
from subprocess import call
from options.train_options import TrainOptions
from data.data_loader import Creat... | vid2vid-master | train.py |
from .base_options import BaseOptions
class TestOptions(BaseOptions):
def initialize(self):
BaseOptions.initialize(self)
self.parser.add_argument('--ntest', type=int, default=float("inf"), help='# of test examples.')
self.parser.add_argument('--results_dir', type=str, default='./results/',... | vid2vid-master | options/test_options.py |
from .base_options import BaseOptions
class TrainOptions(BaseOptions):
def initialize(self):
BaseOptions.initialize(self)
self.parser.add_argument('--display_freq', type=int, default=100, help='frequency of showing training results on screen')
self.parser.add_argument('--print_freq', type=... | vid2vid-master | options/train_options.py |
vid2vid-master | options/__init__.py | |
import argparse
import os
from util import util
import torch
class BaseOptions():
def __init__(self):
self.parser = argparse.ArgumentParser()
self.initialized = False
def initialize(self):
self.parser.add_argument('--dataroot', type=str, default='datasets/Cityscapes/') ... | vid2vid-master | options/base_options.py |
import random
import numpy as np
import torch
from torch.autograd import Variable
class ImagePool():
def __init__(self, pool_size):
self.pool_size = pool_size
if self.pool_size > 0:
self.num_imgs = 0
self.images = []
def query(self, images):
if self.pool_size == ... | vid2vid-master | util/image_pool.py |
from __future__ import print_function
import torch
import numpy as np
from PIL import Image
import inspect, re
import numpy as np
import os
import collections
from PIL import Image
import cv2
from collections import OrderedDict
def save_all_tensors(opt, real_A, fake_B, fake_B_first, fake_B_raw, real_B, flow_ref, conf_... | vid2vid-master | util/util.py |
import dominate
from dominate.tags import *
import os
class HTML:
def __init__(self, web_dir, title, reflesh=0):
self.title = title
self.web_dir = web_dir
self.img_dir = os.path.join(self.web_dir, 'images')
if not os.path.exists(self.web_dir):
os.makedirs(self.web_dir)
... | vid2vid-master | util/html.py |
vid2vid-master | util/__init__.py | |
### Copyright (C) 2017 NVIDIA Corporation. All rights reserved.
### Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
import numpy as np
import os
import time
from . import util
from . import html
import scipy.misc
try:
from StringIO import StringIO # Pytho... | vid2vid-master | util/visualizer.py |
### Copyright (C) 2017 NVIDIA Corporation. All rights reserved.
### Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
import numpy as np
import math
import torch
import torch.nn.functional as F
import os
import sys
from collections import OrderedDict
from torch.a... | vid2vid-master | models/vid2vid_model_G.py |
### Copyright (C) 2017 NVIDIA Corporation. All rights reserved.
### Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
import os
import torch
import torch.nn as nn
import numpy as np
import fractions
def lcm(a,b): return abs(a * b)/fractions.gcd(a,b) if a and b el... | vid2vid-master | models/models.py |
import numpy as np
import torch
import sys
from .base_model import BaseModel
class FlowNet(BaseModel):
def name(self):
return 'FlowNet'
def initialize(self, opt):
BaseModel.initialize(self, opt)
# flownet 2
from .flownet2_pytorch import models as flownet2_models
... | vid2vid-master | models/flownet.py |
vid2vid-master | models/__init__.py | |
import os, sys
import numpy as np
import torch
from .networks import get_grid
class BaseModel(torch.nn.Module):
def name(self):
return 'BaseModel'
def initialize(self, opt):
self.opt = opt
self.gpu_ids = opt.gpu_ids
self.isTrain = opt.isTrain
self.Tensor = torch.cuda.Fl... | vid2vid-master | models/base_model.py |
### Copyright (C) 2017 NVIDIA Corporation. All rights reserved.
### Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
import torch
import torch.nn as nn
from torch.nn import init
import functools
from torch.autograd import Variable
import numpy as np
import torch... | vid2vid-master | models/networks.py |
### Copyright (C) 2017 NVIDIA Corporation. All rights reserved.
### Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
import numpy as np
import torch
import os
import sys
from collections import OrderedDict
from torch.autograd import Variable
import util.util as ... | vid2vid-master | models/vid2vid_model_D.py |
import torch
import torch.nn as nn
from torch.nn import init
import math
import numpy as np
from .networks.resample2d_package.resample2d import Resample2d
from .networks.channelnorm_package.channelnorm import ChannelNorm
from .networks import FlowNetC
from .networks import FlowNetS
from .networks import FlowNetSD
fr... | vid2vid-master | models/flownet2_pytorch/models.py |
#!/usr/bin/env python2.7
import caffe
from caffe.proto import caffe_pb2
import sys, os
import torch
import torch.nn as nn
import argparse, tempfile
import numpy as np
parser = argparse.ArgumentParser()
parser.add_argument('caffe_model', help='input model in hdf5 or caffemodel format')
parser.add_argument('prototxt_... | vid2vid-master | models/flownet2_pytorch/convert.py |
import torch
import torch.utils.data as data
import os, math, random
from os.path import *
import numpy as np
from glob import glob
import utils.frame_utils as frame_utils
from scipy.misc import imread, imresize
class StaticRandomCrop(object):
def __init__(self, image_size, crop_size):
self.th, self.tw ... | vid2vid-master | models/flownet2_pytorch/datasets.py |
vid2vid-master | models/flownet2_pytorch/__init__.py | |
'''
Portions of this code copyright 2017, Clement Pinard
'''
# freda (todo) : adversarial loss
import torch
import torch.nn as nn
import math
def EPE(input_flow, target_flow):
return torch.norm(target_flow-input_flow,p=2,dim=1).mean()
class L1(nn.Module):
def __init__(self):
super(L1, self).__init_... | vid2vid-master | models/flownet2_pytorch/losses.py |
#!/usr/bin/env python
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
from torch.autograd import Variable
from tensorboardX import SummaryWriter
import argparse, os, sys, subprocess
import setproctitle, colorama
import numpy as np
from tqdm import tqdm
from glob import glob
from os.path imp... | vid2vid-master | models/flownet2_pytorch/main.py |
import numpy as np
TAG_CHAR = np.array([202021.25], np.float32)
def readFlow(fn):
""" Read .flo file in Middlebury format"""
# Code adapted from:
# http://stackoverflow.com/questions/28013200/reading-middlebury-flow-files-with-python-bytes-array-numpy
# WARNING: this will work on little-endian archit... | vid2vid-master | models/flownet2_pytorch/utils/flow_utils.py |
# freda (todo) :
import os, time, sys, math
import subprocess, shutil
from os.path import *
import numpy as np
from inspect import isclass
from pytz import timezone
from datetime import datetime
import inspect
import torch
def datestr():
pacific = timezone('US/Pacific')
now = datetime.now(pacific)
return... | vid2vid-master | models/flownet2_pytorch/utils/tools.py |
vid2vid-master | models/flownet2_pytorch/utils/__init__.py | |
import torch
import torch.nn as nn
import numpy as np
def parse_flownetc(modules, weights, biases):
keys = [
'conv1',
'conv2',
'conv3',
'conv_redir',
'conv3_1',
'conv4',
'conv4_1',
'conv5',
'conv5_1',
'conv6',
'conv6_1',
'deconv5',
'deconv4',
'deconv3',
... | vid2vid-master | models/flownet2_pytorch/utils/param_utils.py |
import numpy as np
from os.path import *
from scipy.misc import imread
from . import flow_utils
def read_gen(file_name):
ext = splitext(file_name)[-1]
if ext == '.png' or ext == '.jpeg' or ext == '.ppm' or ext == '.jpg':
im = imread(file_name)
if im.shape[2] > 3:
return im[:,:,:3]
... | vid2vid-master | models/flownet2_pytorch/utils/frame_utils.py |
'''
Portions of this code copyright 2017, Clement Pinard
'''
import torch
import torch.nn as nn
from torch.nn import init
import math
import numpy as np
from .submodules import *
'Parameter count : 38,676,504 '
class FlowNetS(nn.Module):
def __init__(self, args, input_channels = 12, batchNorm=True):
sup... | vid2vid-master | models/flownet2_pytorch/networks/FlowNetS.py |
import torch
import torch.nn as nn
from torch.nn import init
import math
import numpy as np
from .submodules import *
'Parameter count = 581,226'
class FlowNetFusion(nn.Module):
def __init__(self,args, batchNorm=True):
super(FlowNetFusion,self).__init__()
self.batchNorm = batchNorm
self.... | vid2vid-master | models/flownet2_pytorch/networks/FlowNetFusion.py |
# freda (todo) :
import torch.nn as nn
import torch
import numpy as np
def conv(batchNorm, in_planes, out_planes, kernel_size=3, stride=1):
if batchNorm:
return nn.Sequential(
nn.Conv2d(in_planes, out_planes, kernel_size=kernel_size, stride=stride, padding=(kernel_size-1)//2, bias=False),
... | vid2vid-master | models/flownet2_pytorch/networks/submodules.py |
vid2vid-master | models/flownet2_pytorch/networks/__init__.py | |
import torch
import torch.nn as nn
from torch.nn import init
import math
import numpy as np
from .correlation_package.correlation import Correlation
from .submodules import *
'Parameter count , 39,175,298 '
class FlowNetC(nn.Module):
def __init__(self, args, batchNorm=True, div_flow = 20):
super(FlowNet... | vid2vid-master | models/flownet2_pytorch/networks/FlowNetC.py |
import torch
import torch.nn as nn
from torch.nn import init
import math
import numpy as np
from .submodules import *
'Parameter count = 45,371,666'
class FlowNetSD(nn.Module):
def __init__(self, args, batchNorm=True):
super(FlowNetSD,self).__init__()
self.batchNorm = batchNorm
self.conv... | vid2vid-master | models/flownet2_pytorch/networks/FlowNetSD.py |
from torch.autograd import Function, Variable
from torch.nn.modules.module import Module
import channelnorm_cuda
class ChannelNormFunction(Function):
@staticmethod
def forward(ctx, input1, norm_deg=2):
assert input1.is_contiguous()
b, _, h, w = input1.size()
output = input1.new(b, 1, h... | vid2vid-master | models/flownet2_pytorch/networks/channelnorm_package/channelnorm.py |
vid2vid-master | models/flownet2_pytorch/networks/channelnorm_package/__init__.py | |
#!/usr/bin/env python3
import os
import torch
from setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
cxx_args = ['-std=c++11']
nvcc_args = [
'-gencode', 'arch=compute_52,code=sm_52',
'-gencode', 'arch=compute_60,code=sm_60',
'-gencode', 'arch=compute_61,code=sm_6... | vid2vid-master | models/flownet2_pytorch/networks/channelnorm_package/setup.py |
vid2vid-master | models/flownet2_pytorch/networks/correlation_package/__init__.py | |
#!/usr/bin/env python3
import os
import torch
from setuptools import setup, find_packages
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
cxx_args = ['-std=c++11']
nvcc_args = [
'-gencode', 'arch=compute_50,code=sm_50',
'-gencode', 'arch=compute_52,code=sm_52',
'-gencode', 'arch=compu... | vid2vid-master | models/flownet2_pytorch/networks/correlation_package/setup.py |
import torch
from torch.nn.modules.module import Module
from torch.autograd import Function
import correlation_cuda
class CorrelationFunction(Function):
def __init__(self, pad_size=3, kernel_size=3, max_displacement=20, stride1=1, stride2=2, corr_multiply=1):
super(CorrelationFunction, self).__init__()
... | vid2vid-master | models/flownet2_pytorch/networks/correlation_package/correlation.py |
from torch.nn.modules.module import Module
from torch.autograd import Function, Variable
import resample2d_cuda
class Resample2dFunction(Function):
@staticmethod
def forward(ctx, input1, input2, kernel_size=1):
assert input1.is_contiguous()
assert input2.is_contiguous()
ctx.save_for_b... | vid2vid-master | models/flownet2_pytorch/networks/resample2d_package/resample2d.py |
vid2vid-master | models/flownet2_pytorch/networks/resample2d_package/__init__.py | |
#!/usr/bin/env python3
import os
import torch
from setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
cxx_args = ['-std=c++11']
nvcc_args = [
'-gencode', 'arch=compute_50,code=sm_50',
'-gencode', 'arch=compute_52,code=sm_52',
'-gencode', 'arch=compute_60,code=sm_6... | vid2vid-master | models/flownet2_pytorch/networks/resample2d_package/setup.py |
import os
from download_gdrive import *
file_id = '1E8re-b6csNuo-abg1vJKCDjCzlIam50F'
chpt_path = './models/flownet2_pytorch/'
destination = os.path.join(chpt_path, 'FlowNet2_checkpoint.pth.tar')
download_file_from_google_drive(file_id, destination) | vid2vid-master | scripts/download_models_flownet2.py |
import os
from download_gdrive import *
file_id = '1rPcbnanuApZeo2uc7h55OneBkbcFCnnf'
chpt_path = './datasets/'
if not os.path.isdir(chpt_path):
os.makedirs(chpt_path)
destination = os.path.join(chpt_path, 'datasets.zip')
download_file_from_google_drive(file_id, destination)
unzip_file(destination, chpt_path) | vid2vid-master | scripts/download_datasets.py |
# Download code taken from Code taken from https://stackoverflow.com questions/25010369/wget-curl-large-file-from-google-drive/39225039#39225039
import requests, zipfile, os
def download_file_from_google_drive(id, destination):
URL = "https://docs.google.com/uc?export=download"
session = requests.Session()
... | vid2vid-master | scripts/download_gdrive.py |
import os
from download_gdrive import *
import torch
"""if torch.__version__ == '0.4.1':
file_id = '1gKwE1Ad41TwtAzwDcN3dYa_S6DcVyiSl'
file_name = 'flownet2_pytorch_041.zip'
else:
file_id = '1F2h_6e8gyTqxnbmFFW72zsxx_JX0dKFo'
file_name = 'flownet2_pytorch_040.zip'"""
chpt_path = './models/'
if not os.path.isdir(... | vid2vid-master | scripts/download_flownet2.py |
import os
from download_gdrive import *
file_id = '10LvNw-2lrh-6sPGkWbQDfHspkqz5AKxb'
chpt_path = './checkpoints/'
if not os.path.isdir(chpt_path):
os.makedirs(chpt_path)
destination = os.path.join(chpt_path, 'models_face.zip')
download_file_from_google_drive(file_id, destination)
unzip_file(destination, chpt_path) | vid2vid-master | scripts/face/download_models.py |
# Download code taken from Code taken from https://stackoverflow.com questions/25010369/wget-curl-large-file-from-google-drive/39225039#39225039
import requests, zipfile, os
def download_file_from_google_drive(id, destination):
URL = "https://docs.google.com/uc?export=download"
session = requests.Session()
... | vid2vid-master | scripts/face/download_gdrive.py |
import os
from download_gdrive import *
file_id = '1QoE1p3QikxNVbbTBWWRDtIspg-RcLE8y'
chpt_path = './checkpoints/'
if not os.path.isdir(chpt_path):
os.makedirs(chpt_path)
destination = os.path.join(chpt_path, 'models_g1.zip')
download_file_from_google_drive(file_id, destination)
unzip_file(destination, chpt_path)
| vid2vid-master | scripts/street/download_models_g1.py |
import os
from download_gdrive import *
file_id = '1MKtImgtnGC28EPU7Nh9DfFpHW6okNVkl'
chpt_path = './checkpoints/'
if not os.path.isdir(chpt_path):
os.makedirs(chpt_path)
destination = os.path.join(chpt_path, 'models.zip')
download_file_from_google_drive(file_id, destination)
unzip_file(destination, chpt_path) | vid2vid-master | scripts/street/download_models.py |
# Download code taken from Code taken from https://stackoverflow.com questions/25010369/wget-curl-large-file-from-google-drive/39225039#39225039
import requests, zipfile, os
def download_file_from_google_drive(id, destination):
URL = "https://docs.google.com/uc?export=download"
session = requests.Session()
... | vid2vid-master | scripts/street/download_gdrive.py |
from util.util import add_dummy_to_tensor
import torch.utils.data as data
import torch
from PIL import Image
import torchvision.transforms as transforms
import numpy as np
import random
class BaseDataset(data.Dataset):
def __init__(self):
super(BaseDataset, self).__init__()
def name(self):
ret... | vid2vid-master | data/base_dataset.py |
import os.path
import torchvision.transforms as transforms
import torch
from PIL import Image
import numpy as np
import cv2
from skimage import feature
from data.base_dataset import BaseDataset, get_img_params, get_transform, get_video_params, concat_frame
from data.image_folder import make_grouped_dataset, check_path... | vid2vid-master | data/face_dataset.py |
def CreateDataLoader(opt):
from data.custom_dataset_data_loader import CustomDatasetDataLoader
data_loader = CustomDatasetDataLoader()
print(data_loader.name())
data_loader.initialize(opt)
return data_loader
| vid2vid-master | data/data_loader.py |
import os.path
from PIL import Image
import numpy as np
import json
import glob
from scipy.optimize import curve_fit
import warnings
def func(x, a, b, c):
return a * x**2 + b * x + c
def linear(x, a, b):
return a * x + b
def setColor(im, yy, xx, color):
if len(im.shape) == 3:
if (im[yy, xx] =... | vid2vid-master | data/keypoint2img.py |
class BaseDataLoader():
def __init__(self):
pass
def initialize(self, opt):
self.opt = opt
pass
def load_data():
return None
| vid2vid-master | data/base_data_loader.py |
vid2vid-master | data/__init__.py |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.