From 71cdad060b7ff5efe308d7899a776bc9d9915c9a Mon Sep 17 00:00:00 2001 From: Tiago Salvador <38894497+tiagosalvador@users.noreply.github.com> Date: Sat, 19 Nov 2022 05:19:47 -0500 Subject: [PATCH] Add imagenet_cartoon and imagenet_drawing (#80) Co-authored-by: Alexander Panfilov <39771221+kotekjedi@users.noreply.github.com> Co-authored-by: Roland Zimmermann <5895436+zimmerrol@users.noreply.github.com> --- shifthappens/tasks/__init__.py | 2 + .../tasks/imagenet_cartoon/CITATION.cff | 27 ++++++ shifthappens/tasks/imagenet_cartoon/README.md | 23 +++++ .../tasks/imagenet_cartoon/__init__.py | 1 + .../imagenet_cartoon/imagenet_cartoon.py | 88 +++++++++++++++++++ .../tasks/imagenet_drawing/CITATION.cff | 27 ++++++ shifthappens/tasks/imagenet_drawing/README.md | 23 +++++ .../tasks/imagenet_drawing/__init__.py | 1 + .../imagenet_drawing/imagenet_drawing.py | 88 +++++++++++++++++++ 9 files changed, 280 insertions(+) create mode 100644 shifthappens/tasks/imagenet_cartoon/CITATION.cff create mode 100644 shifthappens/tasks/imagenet_cartoon/README.md create mode 100644 shifthappens/tasks/imagenet_cartoon/__init__.py create mode 100644 shifthappens/tasks/imagenet_cartoon/imagenet_cartoon.py create mode 100644 shifthappens/tasks/imagenet_drawing/CITATION.cff create mode 100644 shifthappens/tasks/imagenet_drawing/README.md create mode 100644 shifthappens/tasks/imagenet_drawing/__init__.py create mode 100644 shifthappens/tasks/imagenet_drawing/imagenet_drawing.py diff --git a/shifthappens/tasks/__init__.py b/shifthappens/tasks/__init__.py index a6550227..7ee3a6f4 100644 --- a/shifthappens/tasks/__init__.py +++ b/shifthappens/tasks/__init__.py @@ -1,7 +1,9 @@ """Utility methods and classes for the benchmark's tasks and the individual tasks.""" from shifthappens.tasks import imagenet_c # noqa: F401 +from shifthappens.tasks import imagenet_cartoon # noqa: F401 from shifthappens.tasks import imagenet_d # noqa: F401 +from shifthappens.tasks import imagenet_drawing # noqa: F401 from shifthappens.tasks import imagenet_m # noqa: F401 from shifthappens.tasks import imagenet_metashift # noqa: F401 from shifthappens.tasks import imagenet_patch # noqa F401 diff --git a/shifthappens/tasks/imagenet_cartoon/CITATION.cff b/shifthappens/tasks/imagenet_cartoon/CITATION.cff new file mode 100644 index 00000000..0e884c09 --- /dev/null +++ b/shifthappens/tasks/imagenet_cartoon/CITATION.cff @@ -0,0 +1,27 @@ +cff-version: 1.2.0 +message: "If you use this dataset, please cite it as below." +authors: +- family-names: "Salvador" + given-names: "Tiago" + orcid: "https://orcid.org/0000-0001-9673-0347" +- family-names: "M. Oberman" + given-names: "Adam" + orcid: "https://orcid.org/0000-0002-4214-7364" +title: "ImageNet-Cartoon and ImageNet-Drawing: Two domain shift datasets for ImageNet" +version: 1.0.0 +doi: 10.5281/zenodo.6801109 +date-released: 2022-7-8 +url: "https://github.com/oberman-lab/imagenet-shift" +preferred-citation: + type: conference-paper + authors: + - family-names: "Salvador" + given-names: "Tiago" + orcid: "https://orcid.org/0000-0001-9673-0347" + - family-names: "M. Oberman" + given-names: "Adam" + orcid: "https://orcid.org/0000-0002-4214-7364" + title: "ImageNet-Cartoon and ImageNet-Drawing: two domain shift datasets for ImageNet" + booktile: "ICML Workshop on Shift happens: Crowdsourcing metrics and test datasets beyond ImageNet." + year: 2022 + diff --git a/shifthappens/tasks/imagenet_cartoon/README.md b/shifthappens/tasks/imagenet_cartoon/README.md new file mode 100644 index 00000000..d06ca286 --- /dev/null +++ b/shifthappens/tasks/imagenet_cartoon/README.md @@ -0,0 +1,23 @@ +## Task Description +ImageNet-Cartoon: a dataset to benchmark the robustness of ImageNet models against domain shifts. + +## Dataset Creation +Images are taken from the ImageNet dataset and then transformed into cartoons using the GAN framework proposed by [1]. + +[1] Wang, X. and Yu, J. Learning to cartoonize using white-box cartoon representations. In _Proceedings of the IEEE/CVF +Conference on Computer Vision and Pattern Recognition (CVPR)_, June 2020. + +## Evaluation Metrics +Robust accuracy: correct classification of the transformed images. + +## Expected Insights/Relevance +The accuracy of pretrained ImageNet models decreases significantly on the proposed dataset. + +## Access +We release the dataset on Zenodo (https://zenodo.org/record/6801109), as well as the code to generate it (https://github.com/oberman-lab/imagenet-shift). + +## Data +The dataset is hosted on Zenodo (https://zenodo.org/record/6801109). + +## License +We released the data with the [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/legalcode). diff --git a/shifthappens/tasks/imagenet_cartoon/__init__.py b/shifthappens/tasks/imagenet_cartoon/__init__.py new file mode 100644 index 00000000..bc5a92a6 --- /dev/null +++ b/shifthappens/tasks/imagenet_cartoon/__init__.py @@ -0,0 +1 @@ +"""The ImageNet-Cartoon task.""" diff --git a/shifthappens/tasks/imagenet_cartoon/imagenet_cartoon.py b/shifthappens/tasks/imagenet_cartoon/imagenet_cartoon.py new file mode 100644 index 00000000..3d0692fb --- /dev/null +++ b/shifthappens/tasks/imagenet_cartoon/imagenet_cartoon.py @@ -0,0 +1,88 @@ +"""Shift Happens task: ImageNet-Cartoon""" + +import dataclasses +import os + +import numpy as np +import torchvision.datasets as tv_datasets +import torchvision.transforms as tv_transforms + +import shifthappens.data.base as sh_data +import shifthappens.data.torch as sh_data_torch +import shifthappens.utils as sh_utils +from shifthappens import benchmark as sh_benchmark +from shifthappens.data.base import DataLoader +from shifthappens.models import base as sh_models +from shifthappens.models.base import PredictionTargets +from shifthappens.tasks.base import Task +from shifthappens.tasks.metrics import Metric +from shifthappens.tasks.task_result import TaskResult + + +@sh_benchmark.register_task( + name="ImageNet-Cartoon", relative_data_folder="imagenet_cartoon", standalone=True +) +@dataclasses.dataclass +class ImageNetCartoon(Task): + """ImageNet-Cartoon Dataset. + This task evaluates a model on ImageNet-Cartoon. This + dataset was formed by converting the images in the + ImageNet validation set into cartoons using a GAN + framework. See the readme file for more information + about how the dataset was constructed. + The goal of this evaluation task is to measure the + model's robustness to distribution shifts. + """ + + resources = [ + ( + "imagenet-cartoon.tar.gz", + "https://zenodo.org/record/6801109/files/imagenet-cartoon.tar.gz?download=1", + "a4987ee6efda553299419f47e59a7274", + ) + ] + + def setup(self): + """Setup ImageNet-Cartoon""" + dataset_folder = os.path.join(self.data_root, "imagenet-cartoon") + if not os.path.exists(dataset_folder): + # download data + for file_name, url, md5 in self.resources: + sh_utils.download_and_extract_archive( + url, dataset_folder, md5, file_name + ) + + test_transform = tv_transforms.Compose( + [ + tv_transforms.ToTensor(), + tv_transforms.Lambda(lambda x: x.permute(1, 2, 0)), + ] + ) + + self.ch_dataset = tv_datasets.ImageFolder( + root=dataset_folder, transform=test_transform + ) + self.images_only_dataset = sh_data_torch.IndexedTorchDataset( + sh_data_torch.ImagesOnlyTorchDataset(self.ch_dataset) + ) + + def _prepare_dataloader(self) -> DataLoader: + """Builds the DatasetLoader object.""" + return sh_data.DataLoader(self.images_only_dataset, max_batch_size=None) + + def _evaluate(self, model: sh_models.Model) -> TaskResult: + """Evaluates the model on the ImageNet-Cartoon dataset.""" + dataloader = self._prepare_dataloader() + + all_predicted_labels_list = [] + for predictions in model.predict( + dataloader, PredictionTargets(class_labels=True) + ): + all_predicted_labels_list.append(predictions.class_labels) + all_predicted_labels = np.concatenate(all_predicted_labels_list, 0) + + accuracy = (all_predicted_labels == np.array(self.ch_dataset.targets)).mean() + + return TaskResult( + accuracy=accuracy, summary_metrics={Metric.Robustness: "accuracy"} + ) diff --git a/shifthappens/tasks/imagenet_drawing/CITATION.cff b/shifthappens/tasks/imagenet_drawing/CITATION.cff new file mode 100644 index 00000000..0e884c09 --- /dev/null +++ b/shifthappens/tasks/imagenet_drawing/CITATION.cff @@ -0,0 +1,27 @@ +cff-version: 1.2.0 +message: "If you use this dataset, please cite it as below." +authors: +- family-names: "Salvador" + given-names: "Tiago" + orcid: "https://orcid.org/0000-0001-9673-0347" +- family-names: "M. Oberman" + given-names: "Adam" + orcid: "https://orcid.org/0000-0002-4214-7364" +title: "ImageNet-Cartoon and ImageNet-Drawing: Two domain shift datasets for ImageNet" +version: 1.0.0 +doi: 10.5281/zenodo.6801109 +date-released: 2022-7-8 +url: "https://github.com/oberman-lab/imagenet-shift" +preferred-citation: + type: conference-paper + authors: + - family-names: "Salvador" + given-names: "Tiago" + orcid: "https://orcid.org/0000-0001-9673-0347" + - family-names: "M. Oberman" + given-names: "Adam" + orcid: "https://orcid.org/0000-0002-4214-7364" + title: "ImageNet-Cartoon and ImageNet-Drawing: two domain shift datasets for ImageNet" + booktile: "ICML Workshop on Shift happens: Crowdsourcing metrics and test datasets beyond ImageNet." + year: 2022 + diff --git a/shifthappens/tasks/imagenet_drawing/README.md b/shifthappens/tasks/imagenet_drawing/README.md new file mode 100644 index 00000000..91ab79b9 --- /dev/null +++ b/shifthappens/tasks/imagenet_drawing/README.md @@ -0,0 +1,23 @@ +## Task Description +ImageNet-Drawing: a dataset to benchmark the robustness of ImageNet models against domain shifts. + +## Dataset Creation +Images are taken from the ImageNet dataset and then transformed into drawings using the simple image processing described in [1]. + +[1] Lu, C., Xu, L., and Jia, J. Combining Sketch and Tone for Pencil Drawing Production. In Asente, P. and Grimm, C. +(eds.), _International Symposium on Non-Photorealistic Animation and Rendering_. The Eurographics Association, 2012. ISBN 978-3-905673-90-6. doi: 10.2312/PE/NPAR/NPAR12/065-073. + +## Evaluation Metrics +Robust accuracy: correct classification of the transformed images. + +## Expected Insights/Relevance +The accuracy of pretrained ImageNet models decreases significantly on the proposed dataset. + +## Access +We release the dataset on Zenodo (https://zenodo.org/record/6801109), as well as the code to generate it (https://github.com/oberman-lab/imagenet-shift). + +## Data +The dataset is hosted on Zenodo (https://zenodo.org/record/6801109). + +## License +We released the data with the [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/legalcode). diff --git a/shifthappens/tasks/imagenet_drawing/__init__.py b/shifthappens/tasks/imagenet_drawing/__init__.py new file mode 100644 index 00000000..05919a56 --- /dev/null +++ b/shifthappens/tasks/imagenet_drawing/__init__.py @@ -0,0 +1 @@ +"""The ImageNet-Drawing task.""" diff --git a/shifthappens/tasks/imagenet_drawing/imagenet_drawing.py b/shifthappens/tasks/imagenet_drawing/imagenet_drawing.py new file mode 100644 index 00000000..b9a69b24 --- /dev/null +++ b/shifthappens/tasks/imagenet_drawing/imagenet_drawing.py @@ -0,0 +1,88 @@ +"""Shift Happens task: ImageNet-Drawing""" + +import dataclasses +import os + +import numpy as np +import torchvision.datasets as tv_datasets +import torchvision.transforms as tv_transforms + +import shifthappens.data.base as sh_data +import shifthappens.data.torch as sh_data_torch +import shifthappens.utils as sh_utils +from shifthappens import benchmark as sh_benchmark +from shifthappens.data.base import DataLoader +from shifthappens.models import base as sh_models +from shifthappens.models.base import PredictionTargets +from shifthappens.tasks.base import Task +from shifthappens.tasks.metrics import Metric +from shifthappens.tasks.task_result import TaskResult + + +@sh_benchmark.register_task( + name="ImageNet-Drawing", relative_data_folder="imagenet_drawing", standalone=True +) +@dataclasses.dataclass +class ImageNetDrawing(Task): + """ImageNet-Drawing Dataset. + This task evaluates a model on ImageNet-Drawing. This + dataset was formed by converting the images in the + ImageNet validation set into colored pencil drawings + using simple image processing. See the readme file for + more information about how the dataset was constructed. + The goal of this evaluation task is to measure the + model's robustness to distribution shifts. + """ + + resources = [ + ( + "imagenet-drawing.tar.gz", + "https://zenodo.org/record/6801109/files/imagenet-drawing.tar.gz?download=1", + "3fb1206b6e3190d0159e5dc01c0f97ab", + ) + ] + + def setup(self): + """Setup ImageNet-Drawing""" + dataset_folder = os.path.join(self.data_root, "imagenet-drawing") + if not os.path.exists(dataset_folder): + # download data + for file_name, url, md5 in self.resources: + sh_utils.download_and_extract_archive( + url, dataset_folder, md5, file_name + ) + + test_transform = tv_transforms.Compose( + [ + tv_transforms.ToTensor(), + tv_transforms.Lambda(lambda x: x.permute(1, 2, 0)), + ] + ) + + self.ch_dataset = tv_datasets.ImageFolder( + root=dataset_folder, transform=test_transform + ) + self.images_only_dataset = sh_data_torch.IndexedTorchDataset( + sh_data_torch.ImagesOnlyTorchDataset(self.ch_dataset) + ) + + def _prepare_dataloader(self) -> DataLoader: + """Builds the DatasetLoader object.""" + return sh_data.DataLoader(self.images_only_dataset, max_batch_size=None) + + def _evaluate(self, model: sh_models.Model) -> TaskResult: + """Evaluates the model on the ImageNet-Drawing dataset.""" + dataloader = self._prepare_dataloader() + + all_predicted_labels_list = [] + for predictions in model.predict( + dataloader, PredictionTargets(class_labels=True) + ): + all_predicted_labels_list.append(predictions.class_labels) + all_predicted_labels = np.concatenate(all_predicted_labels_list, 0) + + accuracy = (all_predicted_labels == np.array(self.ch_dataset.targets)).mean() + + return TaskResult( + accuracy=accuracy, summary_metrics={Metric.Robustness: "accuracy"} + )