OpenDenoising
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OpenDenoising
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A
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B
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C
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D
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E
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F
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G
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I
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L
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M
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N
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O
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P
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R
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V
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__call__() (data.MatlabDatasetWrapper method)
(evaluation.Metric method)
(evaluation.Visualisation method)
(model.AbstractDeepLearningModel method)
(model.AbstractDenoiser method)
__getitem__() (data.BlindDatasetGenerator method)
(data.CleanDatasetGenerator method)
(data.FullDatasetGenerator method)
__init__() (data.AbstractDatasetGenerator method)
(OpenDenoising.Benchmark method)
(data.BlindDatasetGenerator method)
(data.CleanDatasetGenerator method)
(data.FullDatasetGenerator method)
(data.MatlabDatasetWrapper method)
(evaluation.CheckpointCallback method)
(evaluation.DnCNNSchedule method)
(evaluation.ExponentialSchedule method)
(evaluation.LrSchedulerCallback method)
(evaluation.Metric method)
(evaluation.PolynomialSchedule method)
(evaluation.StepSchedule method)
(evaluation.TensorboardImage method)
(evaluation.Visualisation method)
(model.AbstractDeepLearningModel method)
(model.AbstractDenoiser method)
(model.architectures.pytorch.DnCNN method)
__len__() (data.AbstractDatasetGenerator method)
__next__() (data.BlindDatasetGenerator method)
(data.FullDatasetGenerator method)
__repr__() (data.BlindDatasetGenerator method)
(data.CleanDatasetGenerator method)
(data.FullDatasetGenerator method)
(model.AbstractDeepLearningModel method)
__str__() (data.AbstractDatasetGenerator method)
(OpenDenoising.Benchmark method)
(data.CleanDatasetGenerator method)
(evaluation.Metric method)
(evaluation.Visualisation method)
(model.AbstractDenoiser method)
A
AbstractDatasetGenerator (class in data)
AbstractDeepLearningModel (class in model)
AbstractDenoiser (class in model)
B
batch_size (data.AbstractDatasetGenerator attribute)
(data.BlindDatasetGenerator attribute)
(data.CleanDatasetGenerator attribute)
(data.FullDatasetGenerator attribute)
Benchmark (class in OpenDenoising)
BlindDatasetGenerator (class in data)
boxplot() (in module evaluation)
C
channel_format (data.MatlabDatasetWrapper attribute)
channels_first (data.AbstractDatasetGenerator attribute)
(data.CleanDatasetGenerator attribute)
CheckpointCallback (class in evaluation)
CleanDatasetGenerator (class in data)
D
data (module)
,
[1]
,
[2]
datasets (OpenDenoising.Benchmark attribute)
denoiser (evaluation.CheckpointCallback attribute)
(evaluation.TensorboardImage attribute)
denoising_func (model.MatconvnetModel attribute)
DnCNN (class in model.architectures.pytorch)
dncnn() (in module model.architectures.keras)
(in module model.architectures.tensorflow)
dncnn_augmentation() (in module data)
DnCNNSchedule (class in evaluation)
dropEvery (evaluation.StepSchedule attribute)
E
engine (data.MatlabDatasetWrapper attribute)
evaluate() (OpenDenoising.Benchmark method)
evaluate_model_on_dataset() (OpenDenoising.Benchmark method)
evaluation (module)
,
[1]
,
[2]
,
[3]
,
[4]
,
[5]
ExponentialSchedule (class in evaluation)
ext (data.MatlabDatasetWrapper attribute)
F
factor (evaluation.ExponentialSchedule attribute)
(evaluation.StepSchedule attribute)
folder_string (evaluation.TensorboardImage attribute)
forward() (model.architectures.pytorch.DnCNN method)
framework (model.AbstractDeepLearningModel attribute)
(model.KerasModel attribute)
(model.MatconvnetModel attribute)
(model.MatlabModel attribute)
(model.OnnxModel attribute)
(model.PytorchModel attribute)
(model.TfModel attribute)
freeze_tf_graph() (in module model.utils)
FullDatasetGenerator (class in data)
func (evaluation.Visualisation attribute)
G
gaussian_noise() (in module data)
gen_patches() (in module data)
general (OpenDenoising.Benchmark attribute)
I
images_path (data.MatlabDatasetWrapper attribute)
initial_lr (evaluation.DnCNNSchedule attribute)
(evaluation.ExponentialSchedule attribute)
(evaluation.PolynomialSchedule attribute)
(evaluation.StepSchedule attribute)
L
logdir (evaluation.CheckpointCallback attribute)
(model.AbstractDeepLearningModel attribute)
(model.KerasModel attribute)
(model.MatconvnetModel attribute)
(model.MatlabModel attribute)
,
[1]
(model.OnnxModel attribute)
(model.PytorchModel attribute)
(model.TfModel attribute)
LrSchedulerCallback (class in evaluation)
M
MatlabDatasetWrapper (class in data)
maxEpochs (evaluation.PolynomialSchedule attribute)
Metric (class in evaluation)
metrics (OpenDenoising.Benchmark attribute)
mode (evaluation.CheckpointCallback attribute)
model (model.AbstractDeepLearningModel attribute)
(model.KerasModel attribute)
,
[1]
(model.MatconvnetModel attribute)
(model.MatlabModel attribute)
(model.OnnxModel attribute)
(model.PytorchModel attribute)
(model.TfModel attribute)
(module)
model.architectures.keras (module)
model.architectures.pytorch (module)
model.architectures.tensorflow (module)
model.filtering (module)
model.utils (module)
model_file_path (model.MatconvnetModel attribute)
model_function (model.FilteringModel attribute)
model_input (model.OnnxModel attribute)
model_name (model.AbstractDenoiser attribute)
model_output (model.OnnxModel attribute)
model_path (model.MatconvnetModel attribute)
models (OpenDenoising.Benchmark attribute)
monitor (evaluation.CheckpointCallback attribute)
N
n_channels (data.AbstractDatasetGenerator attribute)
(data.BlindDatasetGenerator attribute)
(data.CleanDatasetGenerator attribute)
(data.FullDatasetGenerator attribute)
n_patches (data.MatlabDatasetWrapper attribute)
name (data.AbstractDatasetGenerator attribute)
(OpenDenoising.Benchmark attribute)
(data.BlindDatasetGenerator attribute)
(data.CleanDatasetGenerator attribute)
(data.FullDatasetGenerator attribute)
(evaluation.Visualisation attribute)
noise_config (data.CleanDatasetGenerator attribute)
noiseFcn (data.MatlabDatasetWrapper attribute)
np_metric (evaluation.Metric attribute)
O
on_epoch_end() (data.AbstractDatasetGenerator method)
(evaluation.LrSchedulerCallback method)
onnx_dynamic_shapes() (in module model.utils)
OpenDenoising (module)
output_dir (OpenDenoising.Benchmark attribute)
P
partial (OpenDenoising.Benchmark attribute)
partition (data.MatlabDatasetWrapper attribute)
patch_size (data.MatlabDatasetWrapper attribute)
path (data.AbstractDatasetGenerator attribute)
(data.BlindDatasetGenerator attribute)
(data.CleanDatasetGenerator attribute)
(data.FullDatasetGenerator attribute)
pb2onnx() (in module model.utils)
period (evaluation.CheckpointCallback attribute)
poisson_noise() (in module data)
PolynomialSchedule (class in evaluation)
power (evaluation.PolynomialSchedule attribute)
preprocessing (data.BlindDatasetGenerator attribute)
(data.CleanDatasetGenerator attribute)
(data.FullDatasetGenerator attribute)
R
rednet() (in module model.architectures.keras)
register() (OpenDenoising.Benchmark method)
return_diff (model.AbstractDeepLearningModel attribute)
(model.KerasModel attribute)
,
[1]
(model.MatconvnetModel attribute)
(model.MatlabModel attribute)
(model.OnnxModel attribute)
(model.PytorchModel attribute)
(model.TfModel attribute)
runtime_session (model.OnnxModel attribute)
S
salt_and_pepper_noise() (in module data)
shuffle (data.AbstractDatasetGenerator attribute)
(data.BlindDatasetGenerator attribute)
(data.CleanDatasetGenerator attribute)
(data.FullDatasetGenerator attribute)
skimage_mse() (in module evaluation)
skimage_psnr() (in module evaluation)
skimage_ssim() (in module evaluation)
speckle_noise() (in module data)
StepSchedule (class in evaluation)
super_resolution_noise() (in module data)
T
target_fcn (data.BlindDatasetGenerator attribute)
TensorboardImage (class in evaluation)
tf_metric (evaluation.Metric attribute)
tf_mse() (in module evaluation)
tf_psnr() (in module evaluation)
tf_se() (in module evaluation)
tf_ssim() (in module evaluation)
train_info (model.AbstractDeepLearningModel attribute)
(model.KerasModel attribute)
(model.MatconvnetModel attribute)
(model.MatlabModel attribute)
(model.OnnxModel attribute)
(model.PytorchModel attribute)
(model.TfModel attribute)
type (data.MatlabDatasetWrapper attribute)
V
valid_generator (evaluation.TensorboardImage attribute)
Visualisation (class in evaluation)
visualizations (OpenDenoising.Benchmark attribute)
visualize() (OpenDenoising.Benchmark method)
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