From 16d3c4f0ad85f1eba06e22dc59d9581da1ee8f84 Mon Sep 17 00:00:00 2001 From: Shakib-IO Date: Thu, 14 Mar 2024 17:53:37 -0400 Subject: [PATCH] Remove input_size argument from models #1827 --- src/anomalib/models/image/cfa/lightning_model.py | 2 -- src/anomalib/models/image/cfa/torch_model.py | 1 - src/anomalib/models/image/cflow/lightning_model.py | 2 -- src/anomalib/models/image/cflow/torch_model.py | 1 - src/anomalib/models/image/csflow/lightning_model.py | 4 +--- src/anomalib/models/image/fastflow/lightning_model.py | 2 -- src/anomalib/models/image/ganomaly/lightning_model.py | 4 +--- src/anomalib/models/image/padim/lightning_model.py | 2 -- src/anomalib/models/image/padim/torch_model.py | 1 - src/anomalib/models/image/patchcore/anomaly_map.py | 5 ++--- src/anomalib/models/image/patchcore/lightning_model.py | 2 -- src/anomalib/models/image/patchcore/torch_model.py | 1 - .../models/image/reverse_distillation/lightning_model.py | 2 -- .../models/image/reverse_distillation/torch_model.py | 4 ++-- src/anomalib/models/image/stfpm/lightning_model.py | 2 -- src/anomalib/models/image/stfpm/torch_model.py | 3 +-- src/anomalib/models/image/uflow/lightning_model.py | 1 - 17 files changed, 7 insertions(+), 32 deletions(-) diff --git a/src/anomalib/models/image/cfa/lightning_model.py b/src/anomalib/models/image/cfa/lightning_model.py index 7c1c02db45..11d957cacf 100644 --- a/src/anomalib/models/image/cfa/lightning_model.py +++ b/src/anomalib/models/image/cfa/lightning_model.py @@ -30,8 +30,6 @@ class Cfa(AnomalyModule): """CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly Localization. Args: - input_size (tuple[int, int]): Size of the model input. - Defaults to ``(256, 256)``. backbone (str): Backbone CNN network Defaults to ``"wide_resnet50_2"``. gamma_c (int, optional): gamma_c value from the paper. diff --git a/src/anomalib/models/image/cfa/torch_model.py b/src/anomalib/models/image/cfa/torch_model.py index 5553fdb9fe..25667d28c2 100644 --- a/src/anomalib/models/image/cfa/torch_model.py +++ b/src/anomalib/models/image/cfa/torch_model.py @@ -85,7 +85,6 @@ class CfaModel(DynamicBufferMixin): """Torch implementation of the CFA Model. Args: - input_size: (tuple[int, int]): Input size of the image tensor. backbone (str): Backbone CNN network. gamma_c (int): gamma_c parameter from the paper. gamma_d (int): gamma_d parameter from the paper. diff --git a/src/anomalib/models/image/cflow/lightning_model.py b/src/anomalib/models/image/cflow/lightning_model.py index 63593dda68..74fdc4427d 100644 --- a/src/anomalib/models/image/cflow/lightning_model.py +++ b/src/anomalib/models/image/cflow/lightning_model.py @@ -32,8 +32,6 @@ class Cflow(AnomalyModule): """PL Lightning Module for the CFLOW algorithm. Args: - input_size (tuple[int, int], optional): Input image size. - Defaults to ``(256, 256)``. backbone (str, optional): Backbone CNN architecture. Defaults to ``"wide_resnet50_2"``. layers (Sequence[str], optional): Layers to extract features from. diff --git a/src/anomalib/models/image/cflow/torch_model.py b/src/anomalib/models/image/cflow/torch_model.py index a2bc38928c..90ee8b551a 100644 --- a/src/anomalib/models/image/cflow/torch_model.py +++ b/src/anomalib/models/image/cflow/torch_model.py @@ -20,7 +20,6 @@ class CflowModel(nn.Module): """CFLOW: Conditional Normalizing Flows. Args: - input_size (tuple[int, int]): Input image size. backbone (str): Backbone CNN architecture. layers (Sequence[str]): Layers to extract features from. pre_trained (bool): Whether to use pre-trained weights. diff --git a/src/anomalib/models/image/csflow/lightning_model.py b/src/anomalib/models/image/csflow/lightning_model.py index 58a71d540b..a918e32ce4 100644 --- a/src/anomalib/models/image/csflow/lightning_model.py +++ b/src/anomalib/models/image/csflow/lightning_model.py @@ -28,8 +28,6 @@ class Csflow(AnomalyModule): """Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection. Args: - input_size (tuple[int, int]): Size of the model input. - Defaults to ``(256, 256)``. n_coupling_blocks (int): Number of coupling blocks in the model. Defaults to ``4``. cross_conv_hidden_channels (int): Number of hidden channels in the cross convolution. @@ -59,7 +57,7 @@ def __init__( self.model: CsFlowModel def _setup(self) -> None: - assert self.input_size is not None, "Csflow needs input size to build torch model." + assert self.input_size is not None, "CsFlow needs input size to build torch model." self.model = CsFlowModel( input_size=self.input_size, cross_conv_hidden_channels=self.cross_conv_hidden_channels, diff --git a/src/anomalib/models/image/fastflow/lightning_model.py b/src/anomalib/models/image/fastflow/lightning_model.py index caacf73ce7..e76e96d356 100644 --- a/src/anomalib/models/image/fastflow/lightning_model.py +++ b/src/anomalib/models/image/fastflow/lightning_model.py @@ -24,8 +24,6 @@ class Fastflow(AnomalyModule): """PL Lightning Module for the FastFlow algorithm. Args: - input_size (tuple[int, int]): Model input size. - Defaults to ``(256, 256)``. backbone (str): Backbone CNN network Defaults to ``resnet18``. pre_trained (bool, optional): Boolean to check whether to use a pre_trained backbone. diff --git a/src/anomalib/models/image/ganomaly/lightning_model.py b/src/anomalib/models/image/ganomaly/lightning_model.py index 8279d65e1a..b48defd9cc 100644 --- a/src/anomalib/models/image/ganomaly/lightning_model.py +++ b/src/anomalib/models/image/ganomaly/lightning_model.py @@ -27,8 +27,6 @@ class Ganomaly(AnomalyModule): """PL Lightning Module for the GANomaly Algorithm. Args: - input_size (tuple[int, int]): Input dimension. - Defaults to ``(256, 256)``. batch_size (int): Batch size. Defaults to ``32``. n_features (int): Number of features layers in the CNNs. @@ -93,7 +91,7 @@ def __init__( self.model: GanomalyModel def _setup(self) -> None: - assert self.input_size is not None, "CSflow needs input size to build torch model." + assert self.input_size is not None, "GANomaly needs input size to build torch model." self.model = GanomalyModel( input_size=self.input_size, num_input_channels=3, diff --git a/src/anomalib/models/image/padim/lightning_model.py b/src/anomalib/models/image/padim/lightning_model.py index 9cef82e7ed..5da69e3c8f 100644 --- a/src/anomalib/models/image/padim/lightning_model.py +++ b/src/anomalib/models/image/padim/lightning_model.py @@ -27,8 +27,6 @@ class Padim(MemoryBankMixin, AnomalyModule): """PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization. Args: - input_size (tuple[int, int]): Size of the model input. - Defaults to ``(256, 256)``. backbone (str): Backbone CNN network Defaults to ``resnet18``. layers (list[str]): Layers to extract features from the backbone CNN diff --git a/src/anomalib/models/image/padim/torch_model.py b/src/anomalib/models/image/padim/torch_model.py index 89b1a218cd..d9d8f6b400 100644 --- a/src/anomalib/models/image/padim/torch_model.py +++ b/src/anomalib/models/image/padim/torch_model.py @@ -55,7 +55,6 @@ class PadimModel(nn.Module): """Padim Module. Args: - input_size (tuple[int, int]): Input size for the model. layers (list[str]): Layers used for feature extraction backbone (str, optional): Pre-trained model backbone. Defaults to "resnet18". Defaults to ``resnet18``. diff --git a/src/anomalib/models/image/patchcore/anomaly_map.py b/src/anomalib/models/image/patchcore/anomaly_map.py index ae630a1474..8cbd2d668e 100644 --- a/src/anomalib/models/image/patchcore/anomaly_map.py +++ b/src/anomalib/models/image/patchcore/anomaly_map.py @@ -15,8 +15,7 @@ class AnomalyMapGenerator(nn.Module): """Generate Anomaly Heatmap. Args: - input_size (ListConfig, tuple): Size of the input image. - The anomaly map is upsampled to this dimension. + The anomaly map is upsampled to this dimension. sigma (int, optional): Standard deviation for Gaussian Kernel. Defaults to ``4``. """ @@ -65,7 +64,7 @@ def forward( Defaults to None. Example: - >>> anomaly_map_generator = AnomalyMapGenerator(input_size=input_size) + >>> anomaly_map_generator = AnomalyMapGenerator() >>> map = anomaly_map_generator(patch_scores=patch_scores) Returns: diff --git a/src/anomalib/models/image/patchcore/lightning_model.py b/src/anomalib/models/image/patchcore/lightning_model.py index 1c3d3f977e..3451e7ffd2 100644 --- a/src/anomalib/models/image/patchcore/lightning_model.py +++ b/src/anomalib/models/image/patchcore/lightning_model.py @@ -26,8 +26,6 @@ class Patchcore(MemoryBankMixin, AnomalyModule): """PatchcoreLightning Module to train PatchCore algorithm. Args: - input_size (tuple[int, int]): Size of the model input. - Defaults to ``(224, 224)``. backbone (str): Backbone CNN network Defaults to ``wide_resnet50_2``. layers (list[str]): Layers to extract features from the backbone CNN diff --git a/src/anomalib/models/image/patchcore/torch_model.py b/src/anomalib/models/image/patchcore/torch_model.py index 3d85c72392..fd2a5e865f 100644 --- a/src/anomalib/models/image/patchcore/torch_model.py +++ b/src/anomalib/models/image/patchcore/torch_model.py @@ -22,7 +22,6 @@ class PatchcoreModel(DynamicBufferMixin, nn.Module): """Patchcore Module. Args: - input_size (tuple[int, int]): Input size for the model. layers (list[str]): Layers used for feature extraction backbone (str, optional): Pre-trained model backbone. Defaults to ``resnet18``. diff --git a/src/anomalib/models/image/reverse_distillation/lightning_model.py b/src/anomalib/models/image/reverse_distillation/lightning_model.py index 72484b0a21..8e440a5158 100644 --- a/src/anomalib/models/image/reverse_distillation/lightning_model.py +++ b/src/anomalib/models/image/reverse_distillation/lightning_model.py @@ -26,8 +26,6 @@ class ReverseDistillation(AnomalyModule): """PL Lightning Module for Reverse Distillation Algorithm. Args: - input_size (tuple[int, int]): Size of model input - Defaults to ``(256, 256)``. backbone (str): Backbone of CNN network Defaults to ``wide_resnet50_2``. layers (list[str]): Layers to extract features from the backbone CNN diff --git a/src/anomalib/models/image/reverse_distillation/torch_model.py b/src/anomalib/models/image/reverse_distillation/torch_model.py index 5c857c15be..17ae61a070 100644 --- a/src/anomalib/models/image/reverse_distillation/torch_model.py +++ b/src/anomalib/models/image/reverse_distillation/torch_model.py @@ -26,8 +26,8 @@ class ReverseDistillationModel(nn.Module): self.encoder = torchvision.models.wide_resnet50_2(pretrained=True) Args: - backbone (str): Name of the backbone used for encoder and decoder - input_size (tuple[int, int]): Size of input image + backbone (str): Name of the backbone used for encoder and decoder. + input_size (tuple[int, int]): Size of input image. layers (list[str]): Name of layers from which the features are extracted. anomaly_map_mode (str): Mode used to generate anomaly map. Options are between ``multiply`` and ``add``. pre_trained (bool, optional): Boolean to check whether to use a pre_trained backbone. diff --git a/src/anomalib/models/image/stfpm/lightning_model.py b/src/anomalib/models/image/stfpm/lightning_model.py index 3c46fa00e4..34aeb8c7d4 100644 --- a/src/anomalib/models/image/stfpm/lightning_model.py +++ b/src/anomalib/models/image/stfpm/lightning_model.py @@ -27,8 +27,6 @@ class Stfpm(AnomalyModule): """PL Lightning Module for the STFPM algorithm. Args: - input_size (tuple[int, int]): Size of the model input. - Defaults to ``(256, 256)``. backbone (str): Backbone CNN network Defaults to ``resnet18``. layers (list[str]): Layers to extract features from the backbone CNN diff --git a/src/anomalib/models/image/stfpm/torch_model.py b/src/anomalib/models/image/stfpm/torch_model.py index 0629d3b935..98ddf5d46a 100644 --- a/src/anomalib/models/image/stfpm/torch_model.py +++ b/src/anomalib/models/image/stfpm/torch_model.py @@ -22,8 +22,7 @@ class STFPMModel(nn.Module): """STFPM: Student-Teacher Feature Pyramid Matching for Unsupervised Anomaly Detection. Args: - layers (list[str]): Layers used for feature extraction - input_size (tuple[int, int]): Input size for the model. + layers (list[str]): Layers used for feature extraction. backbone (str, optional): Pre-trained model backbone. Defaults to ``resnet18``. """ diff --git a/src/anomalib/models/image/uflow/lightning_model.py b/src/anomalib/models/image/uflow/lightning_model.py index b7a66aec1a..252c5f0504 100644 --- a/src/anomalib/models/image/uflow/lightning_model.py +++ b/src/anomalib/models/image/uflow/lightning_model.py @@ -41,7 +41,6 @@ def __init__( """Uflow model. Args: - input_size (tuple[int, int]): Input image size. backbone (str): Backbone name. flow_steps (int): Number of flow steps. affine_clamp (float): Affine clamp.