.. _sphx_glr_gallery_image:

Image domain
============

Image-domain metrics are pivotal for gauging the performance of models in tasks like object detection, and segmentation. TorchMetrics provides a suite of specialized metrics designed for these purposes. Using these image-specific metrics from Torch Metrics helps in developing more precise and robust image-based models, ensuring that performance evaluations are both meaningful and directly applicable to practical vision tasks.



.. raw:: html

    <div class="sphx-glr-thumbnails">

.. thumbnail-parent-div-open

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="The Spatial Correlation Coefficient can be applied to compare the spatial structure of two images, which can be valuable in various domains such as medical imaging, remote sensing, and quality assessment in manufacturing or design processes.">

.. only:: html

  .. image:: /gallery/image/images/thumb/sphx_glr_spatial_correlation_coef_thumb.png
    :alt:

  :ref:`sphx_glr_gallery_image_spatial_correlation_coef.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Spatial Correlation Coefficient</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="The CLIPScore is a model-based image captioning metric that correlates well with human judgments.">

.. only:: html

  .. image:: /gallery/image/images/thumb/sphx_glr_clip_score_thumb.gif
    :alt:

  :ref:`sphx_glr_gallery_image_clip_score.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">CLIPScore</div>
    </div>


.. thumbnail-parent-div-close

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /gallery/image/spatial_correlation_coef
   /gallery/image/clip_score