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
value |
|---|---|---|---|---|---|---|
AdaInt | AdaInt-main/tests/test_models/test_backbones/test_encoder_decoders/test_encoder_decoder.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmedit.models.backbones import SimpleEncoderDecoder
def assert_dict_keys_equal(dictionary, target_keys):
"""Check if the keys of the dictionary is equal to the target key set."""
assert isinstance(dictionary, dict)
asser... | 3,362 | 35.956044 | 79 | py |
AdaInt | AdaInt-main/tests/test_models/test_backbones/test_encoder_decoders/test_encoders.py | # Copyright (c) OpenMMLab. All rights reserved.
from collections.abc import Iterable
import numpy as np
import pytest
import torch
from mmcv.utils.parrots_wrapper import _BatchNorm
from mmedit.models.backbones import (VGG16, DepthwiseIndexBlock,
FBAResnetDilated, HolisticIndexBloc... | 24,631 | 38.22293 | 79 | py |
AdaInt | AdaInt-main/tests/test_models/test_backbones/test_encoder_decoders/test_pconv_encdec.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmcv.utils.parrots_wrapper import _BatchNorm
from mmedit.models.backbones import PConvEncoder, PConvEncoderDecoder
def test_pconv_encdec():
pconv_enc_cfg = dict(type='PConvEncoder')
pconv_dec_cfg = dict(type='PConvDecoder')
... | 1,280 | 31.025 | 72 | py |
AdaInt | AdaInt-main/tests/test_models/test_backbones/test_encoder_decoders/test_deepfill_encdec.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmedit.models.backbones import DeepFillEncoderDecoder, GLEncoderDecoder
from mmedit.models.components import DeepFillRefiner
def test_deepfill_encdec():
encdec = DeepFillEncoderDecoder()
assert isinstance(encdec.stage1, GLEncoderDecoder)
a... | 961 | 37.48 | 76 | py |
AdaInt | AdaInt-main/tests/test_models/test_extractors/test_feedback_hour_glass.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmedit.models import build_component
from mmedit.models.extractors import Hourglass
from mmedit.models.extractors.feedback_hour_glass import (
ResBlock, reduce_to_five_heatmaps)
def test_res_block():
res_block = ResBlock(16, 32)... | 2,154 | 30.231884 | 68 | py |
AdaInt | AdaInt-main/tests/test_models/test_extractors/test_lte.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmedit.models import build_component
def test_lte():
model_cfg = dict(
type='LTE',
requires_grad=False,
pixel_range=1.,
pretrained=None,
load_pretrained_vgg=False)
lte = build_component(mo... | 863 | 24.411765 | 47 | py |
AdaInt | AdaInt-main/tests/test_models/test_synthesizers/test_cyclegan.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
from unittest.mock import patch
import mmcv
import pytest
import torch
from mmcv.parallel import DataContainer as DC
from mmcv.runner import obj_from_dict
from mmedit.models import build_model
from mmedit.models.backbones import ResnetGenerator
from mmedit.m... | 23,294 | 40.747312 | 78 | py |
AdaInt | AdaInt-main/tests/test_models/test_restorers/test_basicvsr_model.py | # Copyright (c) OpenMMLab. All rights reserved.
import tempfile
import mmcv
import pytest
import torch
from mmcv.runner import obj_from_dict
from mmedit.models import build_model
from mmedit.models.backbones.sr_backbones import BasicVSRNet
from mmedit.models.losses import MSELoss
def test_basicvsr_model():
mod... | 5,163 | 32.973684 | 79 | py |
AdaInt | AdaInt-main/tests/test_models/test_restorers/test_tdan.py | # Copyright (c) OpenMMLab. All rights reserved.
import tempfile
import mmcv
import pytest
import torch
from mmcv.runner import obj_from_dict
from mmedit.models import build_model
from mmedit.models.backbones import TDANNet
from mmedit.models.losses import MSELoss
def test_tdan_model():
model_cfg = dict(
... | 5,090 | 34.110345 | 77 | py |
AdaInt | AdaInt-main/tests/test_models/test_restorers/test_real_esrgan.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest.mock import patch
import pytest
import torch
from mmcv.runner import obj_from_dict
from mmedit.models import build_model
from mmedit.models.backbones import MSRResNet
from mmedit.models.components import ModifiedVGG
from mmedit.models.losses import GANLoss... | 10,264 | 38.480769 | 79 | py |
AdaInt | AdaInt-main/tests/test_models/test_restorers/test_glean.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import pytest
import torch
from mmedit.models import build_model
def test_glean():
model_cfg = dict(
type='GLEAN',
generator=dict(
type='GLEANStyleGANv2',
in_size=16,
out_size=64,
style_ch... | 2,269 | 30.971831 | 78 | py |
AdaInt | AdaInt-main/tests/test_models/test_restorers/test_liif.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
import torch.nn as nn
from mmcv.runner import obj_from_dict
from mmcv.utils.config import Config
from mmedit.models import build_model
from mmedit.models.registry import COMPONENTS
@COMPONENTS.register_module()
class BP(nn.Module):
"... | 4,114 | 33.579832 | 77 | py |
AdaInt | AdaInt-main/tests/test_models/test_restorers/test_dic_model.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmcv.runner import obj_from_dict
from mmcv.utils.config import Config
from mmedit.models.builder import build_model
def test_dic_model():
pretrained = 'https://download.openmmlab.com/mmediting/' + \
'restor... | 4,844 | 39.375 | 77 | py |
AdaInt | AdaInt-main/tests/test_models/test_restorers/test_ttsr.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmcv.runner import obj_from_dict
from mmcv.utils.config import Config
from mmedit.models import build_backbone, build_model
from mmedit.models.backbones.sr_backbones.ttsr_net import (CSFI2, CSFI3, SFE,
... | 7,308 | 33.63981 | 77 | py |
AdaInt | AdaInt-main/tests/test_models/test_restorers/test_esrgan.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest.mock import patch
import torch
from mmcv.runner import obj_from_dict
from mmedit.models import build_model
from mmedit.models.backbones import MSRResNet
from mmedit.models.components import ModifiedVGG
from mmedit.models.losses import GANLoss, L1Loss
def... | 7,807 | 39.666667 | 79 | py |
AdaInt | AdaInt-main/tests/test_models/test_restorers/test_edvr_model.py | # Copyright (c) OpenMMLab. All rights reserved.
import tempfile
import mmcv
import pytest
import torch
from mmcv.runner import obj_from_dict
from mmedit.models import build_model
from mmedit.models.backbones import EDVRNet
from mmedit.models.losses import L1Loss
def test_edvr_model():
model_cfg = dict(
... | 6,625 | 35.406593 | 77 | py |
AdaInt | AdaInt-main/tests/test_models/test_restorers/test_srgan.py | # Copyright (c) OpenMMLab. All rights reserved.
from unittest.mock import patch
import pytest
import torch
from mmcv.runner import obj_from_dict
from mmedit.models import build_model
from mmedit.models.backbones import MSRResNet
from mmedit.models.components import ModifiedVGG
from mmedit.models.losses import GANLoss... | 9,665 | 39.107884 | 79 | py |
AdaInt | AdaInt-main/tests/test_models/test_restorers/test_basic_restorer.py | # Copyright (c) OpenMMLab. All rights reserved.
import tempfile
import mmcv
import pytest
import torch
from mmcv.runner import obj_from_dict
from mmedit.models import build_model
from mmedit.models.backbones import MSRResNet
from mmedit.models.losses import L1Loss
def test_basic_restorer():
model_cfg = dict(
... | 6,208 | 35.309942 | 77 | py |
AdaInt | AdaInt-main/tests/test_models/test_mattors/test_mattors.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
from unittest.mock import patch
import mmcv
import numpy as np
import pytest
import torch
from mmedit.models import BaseMattor, build_model
def _get_model_cfg(fname):
"""
Grab configs necessary to create a model. These are deep copied to ... | 14,057 | 37.620879 | 79 | py |
AdaInt | AdaInt-main/tests/test_models/test_losses/test_losses.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
from unittest.mock import patch
import numpy.testing as npt
import pytest
import torch
from mmedit.models import (CharbonnierCompLoss, CharbonnierLoss, DiscShiftLoss,
GANLoss, GradientLoss, GradientPenaltyLoss,
... | 16,288 | 34.105603 | 79 | py |
AdaInt | AdaInt-main/tests/test_models/test_losses/test_feature_loss.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmedit.models.losses import LightCNNFeatureLoss
def test_light_cnn_feature_loss():
pretrained = 'https://download.openmmlab.com/mmediting/' + \
'restorers/dic/light_cnn_feature.pth'
pred = torch.rand((3, 3, 128, 128))
... | 1,600 | 28.648148 | 78 | py |
AdaInt | AdaInt-main/tests/test_models/test_common/test_common_module.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
import torch.nn as nn
from mmedit.models.common import (ASPP, DepthwiseSeparableConvModule,
GCAModule, LinearModule, MaskConvModule,
PartialConv2d, SimpleGatedConvModule)
def... | 10,851 | 31.984802 | 79 | py |
AdaInt | AdaInt-main/tests/test_models/test_common/test_img_normalize.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmedit.models.common import ImgNormalize
def test_normalize_layer():
rgb_mean = (1, 2, 3)
rgb_std = (1, 0.5, 0.25)
layer = ImgNormalize(1, rgb_mean, rgb_std)
x = torch.randn((2, 3, 64, 64))
y = layer(x)
x = x.permute((1, 0, 2, ... | 695 | 29.26087 | 69 | py |
AdaInt | AdaInt-main/tests/test_models/test_common/test_flow_warp.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmedit.models import flow_warp
def tensor_shift(x, shift=(1, 1), fill_val=0):
"""Shift tensor for testing flow_warp.
Args:
x (Tensor): the input tensor. The shape is (b, c, h, w].
shift (tuple): shift pixel.
... | 1,471 | 26.773585 | 76 | py |
AdaInt | AdaInt-main/tests/test_models/test_common/test_model_utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import pytest
import torch
import torch.nn as nn
from mmedit.models.common import (GANImageBuffer, extract_around_bbox,
extract_bbox_patch, generation_init_weights,
set_re... | 5,756 | 38.979167 | 78 | py |
AdaInt | AdaInt-main/tests/test_models/test_transformer/test_search_transformer.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmedit.models.builder import build_component
def test_search_transformer():
model_cfg = dict(type='SearchTransformer')
model = build_component(model_cfg)
lr_pad_level3 = torch.randn((2, 32, 32, 32))
ref_pad_level3 = torch.randn((2, 32... | 806 | 31.28 | 61 | py |
AdaInt | AdaInt-main/tests/test_models/test_components/test_stylegan2.py | # Copyright (c) OpenMMLab. All rights reserved.
from copy import deepcopy
import pytest
import torch
import torch.nn as nn
from mmedit.models.components.stylegan2.common import get_module_device
from mmedit.models.components.stylegan2.generator_discriminator import (
StyleGAN2Discriminator, StyleGANv2Generator)
f... | 8,432 | 30.466418 | 79 | py |
AdaInt | AdaInt-main/tests/test_models/test_components/test_refiners/test_mlp_refiner.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmedit.models.builder import build_component
def test_mlp_refiner():
model_cfg = dict(
type='MLPRefiner', in_dim=8, out_dim=3, hidden_list=[8, 8, 8, 8])
mlp = build_component(model_cfg)
# test attributes
... | 971 | 26.771429 | 73 | py |
AdaInt | AdaInt-main/tests/test_models/test_components/test_refiners/test_matting_refiners.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmedit.models import PlainRefiner
def assert_dict_keys_equal(dictionary, target_keys):
"""Check if the keys of the dictionary is equal to the target key set."""
assert isinstance(dictionary, dict)
assert set(dictionary.k... | 2,239 | 34.555556 | 79 | py |
AdaInt | AdaInt-main/tests/test_models/test_components/test_refiners/test_deepfill_refiner.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmedit.models import (ContextualAttentionNeck, DeepFillDecoder,
DeepFillEncoder, DeepFillRefiner, GLDilationNeck)
def test_deepfill_refiner():
refiner = DeepFillRefiner()
x = torch.rand((2, 5, 256, 256))
mask = ... | 1,564 | 37.170732 | 76 | py |
AdaInt | AdaInt-main/tests/test_models/test_components/test_discriminators/test_light_cnn.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmedit.models.builder import build_component
from mmedit.models.components.discriminators.light_cnn import MaxFeature
def test_max_feature():
# cpu
conv2d = MaxFeature(16, 16, filter_type='conv2d')
x1 = torch.rand(3, 16, 16, ... | 1,475 | 27.384615 | 72 | py |
AdaInt | AdaInt-main/tests/test_models/test_components/test_discriminators/test_discriminators.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import pytest
import torch
from mmedit.models import build_component
def test_ttsr_dict():
cfg = dict(type='TTSRDiscriminator', in_channels=3, in_size=160)
net = build_component(cfg)
net.init_weights(pretrained=None)
# cp... | 2,904 | 25.898148 | 68 | py |
AdaInt | AdaInt-main/tests/test_models/test_components/test_discriminators/test_deepfill_disc.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmedit.models.components import (DeepFillv1Discriminators,
MultiLayerDiscriminator)
def test_deepfillv1_disc():
model_config = dict(
global_disc_cfg=dict(
type='MultiLayerDisc... | 1,862 | 34.826923 | 68 | py |
AdaInt | AdaInt-main/tests/test_models/test_components/test_discriminators/test_multi_layer_disc.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
import torch.nn as nn
from mmedit.models.components import MultiLayerDiscriminator
def test_multi_layer_disc():
with pytest.raises(AssertionError):
# fc_in_channels must be greater than 0
multi_disc = MultiLayerDiscriminat... | 3,133 | 34.613636 | 71 | py |
AdaInt | AdaInt-main/tests/test_models/test_inpaintors/test_deepfill_inpaintor.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import os
import tempfile
import pytest
import torch
from mmcv import Config
from mmedit.core import build_optimizers
from mmedit.models import DeepFillv1Inpaintor
def test_two_stage_inpaintor():
model = dict(
disc_input_with_mask=True,
... | 12,857 | 38.441718 | 79 | py |
AdaInt | AdaInt-main/tests/test_models/test_inpaintors/test_gl_inpaintor.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmcv import Config
from mmedit.models import build_model
def test_gl_inpaintor():
cfg = Config.fromfile('tests/data/inpaintor_config/gl_test.py')
gl = build_model(cfg.model, train_cfg=cfg.train_cfg, test_cfg=cfg.test_cfg)
assert gl.__cla... | 2,138 | 37.196429 | 79 | py |
AdaInt | AdaInt-main/tests/test_models/test_inpaintors/test_pconv_inpaintor.py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import tempfile
from unittest.mock import patch
import pytest
import torch
from mmcv import Config
from mmedit.models import build_model
from mmedit.models.losses import PerceptualVGG
@patch.object(PerceptualVGG, 'init_weights')
def test_pconv_inpaintor(init... | 3,937 | 36.865385 | 74 | py |
AdaInt | AdaInt-main/tests/test_models/test_inpaintors/test_two_stage_inpaintor.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import os
import tempfile
import pytest
import torch
from mmcv import Config
from mmedit.core import build_optimizers
from mmedit.models import TwoStageInpaintor
def test_two_stage_inpaintor():
model = dict(
disc_input_with_mask=True,
e... | 14,419 | 38.184783 | 79 | py |
AdaInt | AdaInt-main/tests/test_models/test_inpaintors/test_one_stage_inpaintor.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import os
import tempfile
from unittest.mock import patch
import pytest
import torch
from mmcv import Config
from mmedit.models import build_model
from mmedit.models.backbones import GLEncoderDecoder
def test_one_stage_inpaintor():
cfg = Config.fromfil... | 6,045 | 39.306667 | 79 | py |
AdaInt | AdaInt-main/tests/test_data/test_datasets/test_repeat_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
from torch.utils.data import Dataset
from mmedit.datasets import RepeatDataset
def test_repeat_dataset():
class ToyDataset(Dataset):
def __init__(self):
super().__init__()
self.members = [1, 2, 3, 4, 5]
def __len__(self):
... | 623 | 23 | 50 | py |
AdaInt | AdaInt-main/tests/test_data/test_pipelines/test_formating.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmedit.datasets.pipelines import (Collect, FormatTrimap, GetMaskedImage,
ImageToTensor, ToTensor)
from mmedit.datasets.pipelines.formating import FramesToTensor
def check_keys_con... | 7,142 | 36.793651 | 78 | py |
AdaInt | AdaInt-main/tests/test_data/test_pipelines/test_generate_assistant.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmedit.datasets.pipelines import (GenerateCoordinateAndCell,
GenerateHeatmap)
def test_generate_heatmap():
inputs = dict(landmark=[(1, 2), (3, 4)])
generate_heatmap = GenerateHeatmap('landmark', 4, 16)
... | 2,102 | 39.442308 | 77 | py |
AdaInt | AdaInt-main/tests/test_data/test_pipelines/test_pipeline_utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmedit.datasets.pipelines.utils import (adjust_gamma, dtype_range,
make_coord)
def test_adjust_gamma():
"""Test Gamma Correction
Adpted from
# https://github.co... | 3,075 | 36.512195 | 149 | py |
AdaInt | AdaInt-main/tests/test_data/test_pipelines/test_augmentation.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import pytest
import torch
from mmedit.datasets.pipelines import (BinarizeImage, CopyValues, Flip,
GenerateFrameIndices,
GenerateFrameIndiceswithPadding,
... | 31,370 | 41.50813 | 79 | py |
AdaInt | AdaInt-main/tests/test_utils/test_tensor2img.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from torchvision.utils import make_grid
from mmedit.core import tensor2img
def test_tensor2img():
tensor_4d_1 = torch.FloatTensor(2, 3, 4, 4).uniform_(0, 1)
tensor_4d_2 = torch.FloatTensor(1, 3, 4, 4).uniform_(0, 1)... | 3,609 | 41.97619 | 77 | py |
AdaInt | AdaInt-main/tests/test_utils/test_pix2pix.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
from unittest.mock import patch
import mmcv
import pytest
import torch
from mmcv.parallel import DataContainer as DC
from mmcv.runner import obj_from_dict
from mmedit.models import build_model
from mmedit.models.backbones import UnetGenerator
from mmedit.mod... | 16,144 | 38.864198 | 79 | py |
AdaInt | AdaInt-main/tests/test_utils/test_onnx_wraper.py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import mmcv
import numpy as np
import pytest
import torch
from packaging import version
from mmedit.models import build_model
@pytest.mark.skipif(torch.__version__ == 'parrots', reason='skip parrots.')
@pytest.mark.skipif(
version.parse(torch.__version__... | 5,041 | 31.320513 | 79 | py |
AdaInt | AdaInt-main/adaint/model.py | import numbers
import os.path as osp
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision
import mmcv
from mmcv.runner import auto_fp16
from mmedit.models.base import BaseModel
from mmedit.models.registry import MODELS
from mmedit.models.builder import build_loss
from mmedit.core imp... | 17,975 | 35.987654 | 103 | py |
AdaInt | AdaInt-main/adaint/demo.py | import os
import argparse
import mmcv
import torch
from mmcv.parallel import collate, scatter
from mmedit.apis import init_model
from mmedit.core import tensor2img
from mmedit.datasets.pipelines import Compose
def enhancement_inference(model, img):
r"""Inference image with the model.
Args:
model (nn... | 2,448 | 31.653333 | 79 | py |
AdaInt | AdaInt-main/adaint/transforms.py | import random
import numpy as np
from PIL import Image
from torch.nn.modules.utils import _pair
from torchvision.transforms import ColorJitter
from mmedit.datasets.registry import PIPELINES
@PIPELINES.register_module()
class RandomRatioCrop(object):
r"""Random crop the image.
Args:
keys (Sequence[st... | 5,694 | 36.715232 | 111 | py |
AdaInt | AdaInt-main/adaint/ailut_transform/setup.py | import os
import os.path as osp
from setuptools import setup, find_packages
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
def get_version(version_file):
with open(version_file, 'r') as f:
exec(compile(f.read(), version_file, 'exec'))
return locals()['__version__']
os.chdir(osp.... | 1,466 | 30.891304 | 67 | py |
AdaInt | AdaInt-main/adaint/ailut_transform/ailut/pyinterfaces.py | from typing import Tuple
import torch
from torch.cuda.amp import custom_fwd, custom_bwd
from ._ext import (
lut_cforward, lut_cbackward,
ailut_cforward, ailut_cbackward
)
class LUTTransformFunction(torch.autograd.Function):
@staticmethod
@custom_fwd(cast_inputs=torch.float32)
def forward(ctx,
... | 3,728 | 29.072581 | 89 | py |
AdaInt | AdaInt-main/mmedit/apis/test.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import pickle
import shutil
import tempfile
import mmcv
import torch
import torch.distributed as dist
from mmcv.runner import get_dist_info
def single_gpu_test(model,
data_loader,
save_image=False,
... | 7,852 | 32.417021 | 79 | py |
AdaInt | AdaInt-main/mmedit/apis/restoration_face_inference.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmcv.parallel import collate, scatter
from mmedit.datasets.pipelines import Compose
try:
from facexlib.utils.face_restoration_helper import FaceRestoreHelper
has_facexlib = True
except ImportError:
has_facexlib = False
... | 3,069 | 33.494382 | 77 | py |
AdaInt | AdaInt-main/mmedit/apis/generation_inference.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmcv.parallel import collate, scatter
from mmedit.core import tensor2img
from mmedit.datasets.pipelines import Compose
def generation_inference(model, img, img_unpaired=None):
"""Inference image with the model.
Args:
... | 2,229 | 34.967742 | 74 | py |
AdaInt | AdaInt-main/mmedit/apis/inpainting_inference.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmcv.parallel import collate, scatter
from mmedit.datasets.pipelines import Compose
def inpainting_inference(model, masked_img, mask):
"""Inference image with the model.
Args:
model (nn.Module): The loaded model.
masked_img (s... | 1,546 | 29.94 | 70 | py |
AdaInt | AdaInt-main/mmedit/apis/restoration_inference.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmcv.parallel import collate, scatter
from mmedit.datasets.pipelines import Compose
def restoration_inference(model, img):
"""Inference image with the model.
Args:
model (nn.Module): The loaded model.
img (str): File path of i... | 1,434 | 32.372093 | 72 | py |
AdaInt | AdaInt-main/mmedit/apis/matting_inference.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import torch
from mmcv.parallel import collate, scatter
from mmcv.runner import load_checkpoint
from mmedit.datasets.pipelines import Compose
from mmedit.models import build_model
def init_model(config, checkpoint=None, device='cuda:0'):
"""Initialize a... | 2,659 | 33.545455 | 79 | py |
AdaInt | AdaInt-main/mmedit/apis/train.py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import os.path as osp
import random
import warnings
import mmcv
import numpy as np
import torch
from mmcv.parallel import MMDataParallel
from mmcv.runner import HOOKS, IterBasedRunner
from mmcv.utils import build_from_cfg
from mmedit.core import DistEvalIterHo... | 11,841 | 34.776435 | 79 | py |
AdaInt | AdaInt-main/mmedit/apis/restoration_video_inference.py | # Copyright (c) OpenMMLab. All rights reserved.
import glob
import torch
from mmcv.parallel import collate, scatter
from mmedit.datasets.pipelines import Compose
def pad_sequence(data, window_size):
padding = window_size // 2
data = torch.cat([
data[:, 1 + padding:1 + 2 * padding].flip(1), data,
... | 2,942 | 32.443182 | 78 | py |
AdaInt | AdaInt-main/mmedit/core/distributed_wrapper.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.parallel import MODULE_WRAPPERS, MMDistributedDataParallel
from mmcv.parallel.scatter_gather import scatter_kwargs
from torch.cuda._utils import _get_device_index
@MODULE_WRAPPERS.register_module()
class DistributedDataParall... | 5,720 | 39.864286 | 79 | py |
AdaInt | AdaInt-main/mmedit/core/misc.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import numpy as np
import torch
from torchvision.utils import make_grid
def tensor2img(tensor, out_type=np.uint8, min_max=(0, 1)):
"""Convert torch Tensors into image numpy arrays.
After clamping to (min, max), image values will be normalized to [0... | 2,898 | 37.653333 | 79 | py |
AdaInt | AdaInt-main/mmedit/core/evaluation/eval_hooks.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
from mmcv.runner import Hook
from torch.utils.data import DataLoader
class EvalIterHook(Hook):
"""Non-Distributed evaluation hook for iteration-based runner.
This hook will regularly perform evaluation in a given interval when
perform... | 3,766 | 33.87963 | 75 | py |
AdaInt | AdaInt-main/mmedit/core/export/wrappers.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import warnings
import numpy as np
import onnxruntime as ort
import torch
from torch import nn
from mmedit.models import BaseMattor, BasicRestorer, build_model
def inference_with_session(sess, io_binding, output_names, input_tensor):
device_t... | 4,767 | 34.318519 | 79 | py |
AdaInt | AdaInt-main/mmedit/core/hooks/visualization.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import mmcv
import torch
from mmcv.runner import HOOKS, Hook
from mmcv.runner.dist_utils import master_only
from torchvision.utils import save_image
@HOOKS.register_module()
class VisualizationHook(Hook):
"""Visualization hook.
In this ho... | 3,050 | 34.894118 | 79 | py |
AdaInt | AdaInt-main/mmedit/core/hooks/ema.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
from copy import deepcopy
from functools import partial
import mmcv
import torch
from mmcv.parallel import is_module_wrapper
from mmcv.runner import HOOKS, Hook
@HOOKS.register_module()
class ExponentialMovingAverageHook(Hook):
"""Exponential Moving... | 4,719 | 40.403509 | 79 | py |
AdaInt | AdaInt-main/mmedit/core/optimizer/builder.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmcv.runner import build_optimizer
def build_optimizers(model, cfgs):
"""Build multiple optimizers from configs.
If `cfgs` contains several dicts for optimizers, then a dict for each
constructed optimizers will be returned.
If `cfgs` only contains ... | 1,679 | 27.474576 | 78 | py |
AdaInt | AdaInt-main/mmedit/models/base.py | # Copyright (c) OpenMMLab. All rights reserved.
from abc import ABCMeta, abstractmethod
from collections import OrderedDict
import torch
import torch.nn as nn
class BaseModel(nn.Module, metaclass=ABCMeta):
"""Base model.
All models should subclass it.
All subclass should overwrite:
``init_weigh... | 2,948 | 26.820755 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/builder.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from mmcv import build_from_cfg
from .registry import BACKBONES, COMPONENTS, LOSSES, MODELS
def build(cfg, registry, default_args=None):
"""Build module function.
Args:
cfg (dict): Configuration for building modules.
regis... | 1,482 | 23.311475 | 75 | py |
AdaInt | AdaInt-main/mmedit/models/restorers/basicvsr.py | # Copyright (c) OpenMMLab. All rights reserved.
import numbers
import os.path as osp
import mmcv
import numpy as np
import torch
from mmedit.core import tensor2img
from ..registry import MODELS
from .basic_restorer import BasicRestorer
@MODELS.register_module()
class BasicVSR(BasicRestorer):
"""BasicVSR model f... | 7,576 | 35.781553 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/restorers/liif.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import numbers
import os.path as osp
import mmcv
import torch
from mmedit.core import tensor2img
from ..registry import MODELS
from .basic_restorer import BasicRestorer
@MODELS.register_module()
class LIIF(BasicRestorer):
"""LIIF model for single image... | 6,371 | 31.845361 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/restorers/dic.py | # Copyright (c) OpenMMLab. All rights reserved.
import numbers
import os.path as osp
import mmcv
import torch
from mmedit.core import tensor2img
from mmedit.models.common import ImgNormalize
from ..builder import build_backbone, build_component, build_loss
from ..common import set_requires_grad
from ..registry import... | 9,366 | 34.34717 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/restorers/ttsr.py | # Copyright (c) OpenMMLab. All rights reserved.
import numbers
import os.path as osp
import mmcv
import torch
from mmedit.core import tensor2img
from ..builder import build_backbone, build_component, build_loss
from ..common import set_requires_grad
from ..registry import MODELS
from .basic_restorer import BasicResto... | 11,581 | 36.003195 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/restorers/real_esrgan.py | import numbers
import os.path as osp
from copy import deepcopy
import mmcv
import torch
from mmcv.parallel import is_module_wrapper
from mmedit.core import tensor2img
from ..common import set_requires_grad
from ..registry import MODELS
from .srgan import SRGAN
@MODELS.register_module()
class RealESRGAN(SRGAN):
... | 8,849 | 36.820513 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/restorers/esrgan.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from ..common import set_requires_grad
from ..registry import MODELS
from .srgan import SRGAN
@MODELS.register_module()
class ESRGAN(SRGAN):
"""Enhanced SRGAN model for single image super-resolution.
Ref:
ESRGAN: Enhanced Super-Resolution Gene... | 4,694 | 35.395349 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/extractors/lte.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.runner import load_checkpoint
from torchvision import models
from mmedit.models.common import ImgNormalize
from mmedit.models.registry import COMPONENTS
from mmedit.utils import get_root_logger
@COMPONENTS.register_module()
... | 3,781 | 33.697248 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/extractors/feedback_hour_glass.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmedit.models.registry import COMPONENTS
class ResBlock(nn.Module):
"""ResBlock for Hourglass.
It has a style of:
::
---Conv-ReLU-Conv-Conv-+-
|_________Conv________|
or
---Conv-R... | 7,183 | 32.7277 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/common/flow_warp.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn.functional as F
def flow_warp(x,
flow,
interpolation='bilinear',
padding_mode='zeros',
align_corners=True):
"""Warp an image or a feature map with optical flow.
Args:
x... | 1,781 | 36.125 | 78 | py |
AdaInt | AdaInt-main/mmedit/models/common/aspp.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmcv.cnn import ConvModule
from torch import nn
from torch.nn import functional as F
from .separable_conv_module import DepthwiseSeparableConvModule
class ASPPPooling(nn.Sequential):
def __init__(self, in_channels, out_channels, conv_cfg, norm_cf... | 3,861 | 29.650794 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/common/sr_backbone_utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from mmcv.cnn import constant_init, kaiming_init
from mmcv.utils.parrots_wrapper import _BatchNorm
def default_init_weights(module, scale=1):
"""Initialize network weights.
Args:
modules (nn.Module): Modules to be initialized.
... | 2,919 | 28.795918 | 78 | py |
AdaInt | AdaInt-main/mmedit/models/common/model_utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
def set_requires_grad(nets, requires_grad=False):
"""Set requires_grad for all the networks.
Args:
nets (nn.Module | list[nn.Module]): A list of networks or a single
network.
requires_grad (bool): Whet... | 4,502 | 31.868613 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/common/separable_conv_module.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from mmcv.cnn import ConvModule
class DepthwiseSeparableConvModule(nn.Module):
"""Depthwise separable convolution module.
See https://arxiv.org/pdf/1704.04861.pdf for details.
This module can replace a ConvModule with the conv block r... | 3,907 | 38.877551 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/common/linear_module.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from mmcv.cnn import build_activation_layer, kaiming_init
class LinearModule(nn.Module):
"""A linear block that contains linear/norm/activation layers.
For low level vision, we add spectral norm and padding layer.
Args:
in_fea... | 3,211 | 34.688889 | 78 | py |
AdaInt | AdaInt-main/mmedit/models/common/contextual_attention.py | # Copyright (c) OpenMMLab. All rights reserved.
from functools import partial
import torch
import torch.nn as nn
import torch.nn.functional as F
class ContextualAttentionModule(nn.Module):
"""Contexture attention module.
The details of this module can be found in:
Generative Image Inpainting with Contex... | 15,214 | 39.039474 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/common/gated_conv_module.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, build_activation_layer
class SimpleGatedConvModule(nn.Module):
"""Simple Gated Convolutional Module.
This module is a simple gated convolutional module. The detailed formula
is... | 2,423 | 32.205479 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/common/conv.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmcv.cnn import CONV_LAYERS
from torch import nn
CONV_LAYERS.register_module('Deconv', module=nn.ConvTranspose2d)
# TODO: octave conv
| 188 | 26 | 64 | py |
AdaInt | AdaInt-main/mmedit/models/common/gca_module.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, constant_init, xavier_init
from torch.nn import functional as F
class GCAModule(nn.Module):
"""Guided Contextual Attention Module.
From https://arxiv.org/pdf/2001.04069.pdf.
Based on https:... | 14,808 | 40.250696 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/common/generation_model_utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, kaiming_init, normal_init, xavier_init
from torch.nn import init
def generation_init_weights(module, init_type='normal', init_gain=0.02):
"""Default initialization of network weig... | 10,699 | 34.430464 | 78 | py |
AdaInt | AdaInt-main/mmedit/models/common/upsample.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
import torch.nn.functional as F
from .sr_backbone_utils import default_init_weights
class PixelShufflePack(nn.Module):
""" Pixel Shuffle upsample layer.
Args:
in_channels (int): Number of input channels.
out_channels (int)... | 1,517 | 28.192308 | 76 | py |
AdaInt | AdaInt-main/mmedit/models/common/img_normalize.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
class ImgNormalize(nn.Conv2d):
"""Normalize images with the given mean and std value.
Based on Conv2d layer, can work in GPU.
Args:
pixel_range (float): Pixel range of feature.
img_mean (Tuple[float]): Ima... | 1,063 | 31.242424 | 68 | py |
AdaInt | AdaInt-main/mmedit/models/common/mask_conv_module.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmcv.cnn import ConvModule
class MaskConvModule(ConvModule):
"""Mask convolution module.
This is a simple wrapper for mask convolution like: 'partial conv'.
Convolutions in this module always need a mask as extra input.
Args:
in_channels (... | 3,649 | 40.011236 | 78 | py |
AdaInt | AdaInt-main/mmedit/models/common/partial_conv.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import CONV_LAYERS
@CONV_LAYERS.register_module(name='PConv')
class PartialConv2d(nn.Conv2d):
"""Implementation for partial convolution.
Image Inpainting for Irr... | 3,609 | 34.048544 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/inpaintors/two_stage.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
from pathlib import Path
import mmcv
import torch
from torchvision.utils import save_image
from mmedit.core import tensor2img
from ..common.model_utils import set_requires_grad
from ..registry import MODELS
from .one_stage import OneStageInpaintor
... | 14,418 | 39.052778 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/inpaintors/one_stage.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
from pathlib import Path
import mmcv
import torch
from mmcv.runner import auto_fp16
from torchvision.utils import save_image
from mmedit.core import L1Evaluation, psnr, ssim, tensor2img
from ..base import BaseModel
from ..builder import build_backb... | 16,856 | 36.795964 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/inpaintors/pconv_inpaintor.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
from pathlib import Path
import mmcv
import torch
from mmedit.core import tensor2img
from ..registry import MODELS
from .one_stage import OneStageInpaintor
@MODELS.register_module()
class PConvInpaintor(OneStageInpaintor):
def forward_test(s... | 5,306 | 35.349315 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/inpaintors/gl_inpaintor.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from ..common import extract_around_bbox, extract_bbox_patch, set_requires_grad
from ..registry import MODELS
from .one_stage import OneStageInpaintor
@MODELS.register_module()
class GLInpaintor(OneStageInpaintor):
"""Inpaintor for global&local method.... | 9,507 | 37.650407 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/inpaintors/deepfillv1.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch.nn.parallel import DataParallel, DistributedDataParallel
from ..common import extract_around_bbox, extract_bbox_patch, set_requires_grad
from ..registry import MODELS
from .two_stage import TwoStageInpaintor
@MODELS.register_module()
class DeepF... | 12,647 | 39.8 | 79 | py |
AdaInt | AdaInt-main/mmedit/models/components/stylegan2/generator_discriminator.py | # Copyright (c) OpenMMLab. All rights reserved.
import random
import mmcv
import numpy as np
import torch
import torch.nn as nn
from mmcv.runner.checkpoint import _load_checkpoint_with_prefix
from mmedit.models.registry import COMPONENTS
from .common import get_mean_latent, get_module_device, style_mixing
from .modul... | 21,897 | 39.402214 | 167 | py |
AdaInt | AdaInt-main/mmedit/models/components/stylegan2/modules.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
from copy import deepcopy
from functools import partial
import mmcv
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.cnn.bricks.activation import build_activation_layer
from mmcv.cnn.utils import nor... | 32,421 | 33.236536 | 89 | py |
AdaInt | AdaInt-main/mmedit/models/components/stylegan2/common.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
def get_module_device(module):
"""Get the device of a module.
Args:
module (nn.Module): A module contains the parameters.
Returns:
torch.device: The device of the module.
"""
try:
next(module.parameters())
e... | 2,847 | 28.061224 | 78 | py |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.