0.16 docs

0.16/_sources/auto_examples/others/plot_optical_flow.rst.txt

@@ -352,7 +352,7 @@ ffmpeg -f image2 -framerate 30 -i predicted_flow_%d.jpg -loop -1 flow.gif
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 9.992 seconds)
+   **Total running time of the script:** (0 minutes 10.096 seconds)
 
 
 .. _sphx_glr_download_auto_examples_others_plot_optical_flow.py:

0.16/_sources/auto_examples/others/plot_repurposing_annotations.rst.txt

@@ -417,7 +417,7 @@ Here is an example where we re-purpose the dataset from the
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 2.715 seconds)
+   **Total running time of the script:** (0 minutes 2.507 seconds)
 
 
 .. _sphx_glr_download_auto_examples_others_plot_repurposing_annotations.py:

0.16/_sources/auto_examples/others/plot_scripted_tensor_transforms.rst.txt

@@ -239,7 +239,7 @@ Since the model is scripted, it can be easily dumped on disk and re-used
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 1.672 seconds)
+   **Total running time of the script:** (0 minutes 1.683 seconds)
 
 
 .. _sphx_glr_download_auto_examples_others_plot_scripted_tensor_transforms.py:

0.16/_sources/auto_examples/others/plot_video_api.rst.txt

@@ -551,7 +551,7 @@ We can generate a dataloader and test the dataset.
 
     /pytorch/vision/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).
       warnings.warn(
-    {'video': ['./dataset/2/v_SoccerJuggling_g24_c01.avi', './dataset/2/v_SoccerJuggling_g23_c01.avi', './dataset/2/v_SoccerJuggling_g24_c01.avi', './dataset/2/v_SoccerJuggling_g23_c01.avi', './dataset/2/v_SoccerJuggling_g24_c01.avi'], 'start': [1.0105714579990077, 1.4112325561163752, 0.2561907936526305, 1.0557042088788688, 6.0416417274969625], 'end': [1.534867, 1.9352669999999998, 0.7674329999999999, 1.568233, 6.573233], 'tensorsize': [torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112])]}
+    {'video': ['./dataset/1/RATRACE_wave_f_nm_np1_fr_goo_37.avi', './dataset/2/SOX5yA1l24A.mp4', './dataset/2/SOX5yA1l24A.mp4', './dataset/2/v_SoccerJuggling_g24_c01.avi', './dataset/2/v_SoccerJuggling_g23_c01.avi'], 'start': [1.2933978369482158, 1.7918684185786267, 4.373791147055652, 3.9307513195312067, 3.6426948895065263], 'end': [1.7999999999999998, 2.3023, 4.9049, 4.437767, 4.170833], 'tensorsize': [torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112])]}
 
 
 
@@ -609,7 +609,7 @@ Cleanup the video and dataset:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 4.643 seconds)
+   **Total running time of the script:** (0 minutes 5.277 seconds)
 
 
 .. _sphx_glr_download_auto_examples_others_plot_video_api.py:

0.16/_sources/auto_examples/others/plot_visualization_utils.rst.txt

@@ -1064,7 +1064,7 @@ We pass the above list to the connectivity parameter to connect the keypoints.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 24.360 seconds)
+   **Total running time of the script:** (0 minutes 14.555 seconds)
 
 
 .. _sphx_glr_download_auto_examples_others_plot_visualization_utils.py:

0.16/_sources/auto_examples/others/sg_execution_times.rst.txt

@@ -6,16 +6,16 @@
 
 Computation times
 =================
-**00:43.382** total execution time for **auto_examples_others** files:
+**00:34.118** total execution time for **auto_examples_others** files:
 
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_others_plot_visualization_utils.py` (``plot_visualization_utils.py``)               | 00:24.360 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_others_plot_visualization_utils.py` (``plot_visualization_utils.py``)               | 00:14.555 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_others_plot_optical_flow.py` (``plot_optical_flow.py``)                             | 00:09.992 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_others_plot_optical_flow.py` (``plot_optical_flow.py``)                             | 00:10.096 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_others_plot_video_api.py` (``plot_video_api.py``)                                   | 00:04.643 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_others_plot_video_api.py` (``plot_video_api.py``)                                   | 00:05.277 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_others_plot_repurposing_annotations.py` (``plot_repurposing_annotations.py``)       | 00:02.715 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_others_plot_repurposing_annotations.py` (``plot_repurposing_annotations.py``)       | 00:02.507 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_others_plot_scripted_tensor_transforms.py` (``plot_scripted_tensor_transforms.py``) | 00:01.672 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_others_plot_scripted_tensor_transforms.py` (``plot_scripted_tensor_transforms.py``) | 00:01.683 | 0.0 MB |
 +------------------------------------------------------------------------------------------------------------------+-----------+--------+

0.16/_sources/auto_examples/transforms/plot_custom_transforms.rst.txt

@@ -205,7 +205,7 @@ an issue on our `GitHub repo <https://github.com/pytorch/vision/issues>`_.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 0.007 seconds)
+   **Total running time of the script:** (0 minutes 0.006 seconds)
 
 
 .. _sphx_glr_download_auto_examples_transforms_plot_custom_transforms.py:

0.16/_sources/auto_examples/transforms/plot_cutmix_mixup.rst.txt

@@ -263,7 +263,7 @@ by passing a callable to the ``labels_getter`` parameter. For example:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 0.162 seconds)
+   **Total running time of the script:** (0 minutes 0.155 seconds)
 
 
 .. _sphx_glr_download_auto_examples_transforms_plot_cutmix_mixup.py:

0.16/_sources/auto_examples/transforms/plot_transforms_e2e.rst.txt

@@ -336,7 +336,7 @@ v2). So don't be afraid to simplify and only keep what you need.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 4.987 seconds)
+   **Total running time of the script:** (0 minutes 4.813 seconds)
 
 
 .. _sphx_glr_download_auto_examples_transforms_plot_transforms_e2e.py:

0.16/_sources/auto_examples/transforms/plot_transforms_getting_started.rst.txt

@@ -400,7 +400,7 @@ Either way, the logic will depend on your specific dataset.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 0.860 seconds)
+   **Total running time of the script:** (0 minutes 0.838 seconds)
 
 
 .. _sphx_glr_download_auto_examples_transforms_plot_transforms_getting_started.py:

0.16/_sources/auto_examples/transforms/plot_transforms_illustrations.rst.txt

@@ -809,7 +809,7 @@ randomly applies a list of transforms, with a given probability.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 9.073 seconds)
+   **Total running time of the script:** (0 minutes 8.772 seconds)
 
 
 .. _sphx_glr_download_auto_examples_transforms_plot_transforms_illustrations.py:

0.16/_sources/auto_examples/transforms/plot_tv_tensors.rst.txt

@@ -411,7 +411,7 @@ tensor:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 0.009 seconds)
+   **Total running time of the script:** (0 minutes 0.008 seconds)
 
 
 .. _sphx_glr_download_auto_examples_transforms_plot_tv_tensors.py:

0.16/_sources/auto_examples/transforms/sg_execution_times.rst.txt

@@ -6,20 +6,20 @@
 
 Computation times
 =================
-**00:15.101** total execution time for **auto_examples_transforms** files:
+**00:14.597** total execution time for **auto_examples_transforms** files:
 
 +----------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_transforms_plot_transforms_illustrations.py` (``plot_transforms_illustrations.py``)     | 00:09.073 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_transforms_plot_transforms_illustrations.py` (``plot_transforms_illustrations.py``)     | 00:08.772 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_transforms_plot_transforms_e2e.py` (``plot_transforms_e2e.py``)                         | 00:04.987 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_transforms_plot_transforms_e2e.py` (``plot_transforms_e2e.py``)                         | 00:04.813 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_transforms_plot_transforms_getting_started.py` (``plot_transforms_getting_started.py``) | 00:00.860 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_transforms_plot_transforms_getting_started.py` (``plot_transforms_getting_started.py``) | 00:00.838 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_transforms_plot_cutmix_mixup.py` (``plot_cutmix_mixup.py``)                             | 00:00.162 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_transforms_plot_cutmix_mixup.py` (``plot_cutmix_mixup.py``)                             | 00:00.155 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_transforms_plot_tv_tensors.py` (``plot_tv_tensors.py``)                                 | 00:00.009 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_transforms_plot_tv_tensors.py` (``plot_tv_tensors.py``)                                 | 00:00.008 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_transforms_plot_custom_transforms.py` (``plot_custom_transforms.py``)                   | 00:00.007 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_transforms_plot_custom_transforms.py` (``plot_custom_transforms.py``)                   | 00:00.006 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------------------+-----------+--------+
 | :ref:`sphx_glr_auto_examples_transforms_plot_custom_tv_tensors.py` (``plot_custom_tv_tensors.py``)                   | 00:00.004 | 0.0 MB |
 +----------------------------------------------------------------------------------------------------------------------+-----------+--------+

0.16/_static/documentation_options.js

@@ -1,6 +1,6 @@
 var DOCUMENTATION_OPTIONS = {
     URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'),
-    VERSION: '0.16',
+    VERSION: 'main',
     LANGUAGE: 'en',
     COLLAPSE_INDEX: false,
     BUILDER: 'html',

0.16/auto_examples/others/plot_optical_flow.html

@@ -548,7 +548,7 @@ <h2>Bonus: Creating GIFs of predicted flows<a class="headerlink" href="#bonus-cr
 <p>Once the .jpg flow images are saved, you can convert them into a video or a
 GIF using ffmpeg with e.g.:</p>
 <p>ffmpeg -f image2 -framerate 30 -i predicted_flow_%d.jpg -loop -1 flow.gif</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 9.992 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 10.096 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-others-plot-optical-flow-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/6acd2f50f8be085d0a8ac5874560f268/plot_optical_flow.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_optical_flow.py</span></code></a></p>

0.16/auto_examples/others/plot_repurposing_annotations.html

@@ -589,7 +589,7 @@ <h2>Converting Segmentation Dataset to Detection Dataset<a class="headerlink" hr
         <span class="k">return</span> <a href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="torch.Tensor" class="sphx-glr-backref-module-torch sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">img</span></a><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">target</span></a>
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 2.715 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 2.507 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-others-plot-repurposing-annotations-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/6159c523793cb1afbb503259bd141f91/plot_repurposing_annotations.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_repurposing_annotations.py</span></code></a></p>

0.16/auto_examples/others/plot_scripted_tensor_transforms.html

@@ -474,7 +474,7 @@
 <span class="k">assert</span> <span class="p">(</span><a href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="torch.Tensor" class="sphx-glr-backref-module-torch sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">res_scripted_dumped</span></a> <span class="o">==</span> <a href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="torch.Tensor" class="sphx-glr-backref-module-torch sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">res_scripted</span></a><span class="p">)</span><span class="o">.</span><span class="n">all</span><span class="p">()</span>
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 1.672 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 1.683 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-others-plot-scripted-tensor-transforms-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/1c7d3f45724a1171e328ce5cdd7bc79a/plot_scripted_tensor_transforms.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_scripted_tensor_transforms.py</span></code></a></p>

0.16/auto_examples/others/plot_video_api.html

@@ -848,7 +848,7 @@ <h2>3. Building an example randomly sampled dataset (can be applied to training
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/pytorch/vision/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).
   warnings.warn(
-{&#39;video&#39;: [&#39;./dataset/2/v_SoccerJuggling_g24_c01.avi&#39;, &#39;./dataset/2/v_SoccerJuggling_g23_c01.avi&#39;, &#39;./dataset/2/v_SoccerJuggling_g24_c01.avi&#39;, &#39;./dataset/2/v_SoccerJuggling_g23_c01.avi&#39;, &#39;./dataset/2/v_SoccerJuggling_g24_c01.avi&#39;], &#39;start&#39;: [1.0105714579990077, 1.4112325561163752, 0.2561907936526305, 1.0557042088788688, 6.0416417274969625], &#39;end&#39;: [1.534867, 1.9352669999999998, 0.7674329999999999, 1.568233, 6.573233], &#39;tensorsize&#39;: [torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112])]}
+{&#39;video&#39;: [&#39;./dataset/1/RATRACE_wave_f_nm_np1_fr_goo_37.avi&#39;, &#39;./dataset/2/SOX5yA1l24A.mp4&#39;, &#39;./dataset/2/SOX5yA1l24A.mp4&#39;, &#39;./dataset/2/v_SoccerJuggling_g24_c01.avi&#39;, &#39;./dataset/2/v_SoccerJuggling_g23_c01.avi&#39;], &#39;start&#39;: [1.2933978369482158, 1.7918684185786267, 4.373791147055652, 3.9307513195312067, 3.6426948895065263], &#39;end&#39;: [1.7999999999999998, 2.3023, 4.9049, 4.437767, 4.170833], &#39;tensorsize&#39;: [torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112]), torch.Size([16, 3, 112, 112])]}
 </pre></div>
 </div>
 </section>
@@ -871,7 +871,7 @@ <h2>4. Data Visualization<a class="headerlink" href="#data-visualization" title=
 <a href="https://docs.python.org/3/library/shutil.html#shutil.rmtree" title="shutil.rmtree" class="sphx-glr-backref-module-shutil sphx-glr-backref-type-py-function"><span class="n">shutil</span><span class="o">.</span><span class="n">rmtree</span></a><span class="p">(</span><span class="s2">&quot;./dataset&quot;</span><span class="p">)</span>
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 4.643 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 5.277 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-others-plot-video-api-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/175e3bb1b03a25b015d65842a3b8a883/plot_video_api.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_video_api.py</span></code></a></p>