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Remove CenterCrop from Classification test pipeline and editing missing docs link #2375

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sungmanc merged 2 commits into from
Jul 19, 2023
Merged

Remove CenterCrop from Classification test pipeline and editing missing docs link #2375

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6ff762c
Fix missing link for docs and removing centercrop for classification …
sungmanc Jul 19, 2023
6c44220
Revert the test threshold
sungmanc Jul 19, 2023
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4 changes: 2 additions & 2 deletions docs/source/guide/explanation/algorithms/segmentation/semantic_segmentation.rst
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Expand Up @@ -42,7 +42,7 @@ Dataset Format

For the dataset handling inside OpenVINO™ Training Extensions, we use `Dataset Management Framework (Datumaro) <https://github.com/openvinotoolkit/datumaro>`_.

At this end we support `Common Semantic Segmentation <https://openvinotoolkit.github.io/datumaro/docs/formats/common_semantic_segmentation/>`_ data format.
At this end we support `Common Semantic Segmentation <https://github.com/openvinotoolkit/datumaro/blob/develop/docs/source/docs/data-formats/formats/common_semantic_segmentation.md>`_ data format.
If you organized supported dataset format, starting training will be very simple. We just need to pass a path to the root folder and desired model template to start training:

.. code-block::
Expand Down Expand Up @@ -278,4 +278,4 @@ It can be launched only with supervised (incremental) training type.
.. Incremental Learning
.. ********************

.. To be added soon
.. To be added soon
5 changes: 2 additions & 3 deletions src/otx/algorithms/classification/configs/base/data/data_pipeline.py
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Expand Up @@ -20,7 +20,7 @@
__resize_target_size = 224

__train_pipeline = [
dict(type="RandomResizedCrop", size=224, efficientnet_style=True),
dict(type="RandomResizedCrop", size=__resize_target_size, efficientnet_style=True),
dict(type="RandomFlip", flip_prob=0.5, direction="horizontal"),
dict(type="Normalize", **__img_norm_cfg),
dict(type="ImageToTensor", keys=["img"]),
Expand All @@ -29,8 +29,7 @@
]

__test_pipeline = [
dict(type="Resize", size=(256, -1)),
dict(type="CenterCrop", crop_size=224),
dict(type="Resize", size=__resize_target_size),
dict(type="Normalize", **__img_norm_cfg),
dict(type="ImageToTensor", keys=["img"]),
dict(type="Collect", keys=["img"]),
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3 changes: 1 addition & 2 deletions tests/e2e/cli/classification/test_classification.py
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Expand Up @@ -180,8 +180,7 @@ def test_otx_explain_openvino(self, template, tmp_dir_path):
@pytest.mark.parametrize("half_precision", [True, False])
def test_otx_eval_openvino(self, template, tmp_dir_path, half_precision):
tmp_dir_path = tmp_dir_path / "multi_class_cls"
# FIXME [Jaeguk] Revert threshold to 0.2 when model api supports resize and centercrop.
otx_eval_openvino_testing(template, tmp_dir_path, otx_dir, args, threshold=0.5, half_precision=half_precision)
otx_eval_openvino_testing(template, tmp_dir_path, otx_dir, args, threshold=0.2, half_precision=half_precision)

@e2e_pytest_component
@pytest.mark.skipif(TT_STABILITY_TESTS, reason="This is TT_STABILITY_TESTS")
Expand Down