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diff --git a/dev/_images/sphx_glr_plot_trainable_segmentation_001.png b/dev/_images/sphx_glr_plot_trainable_segmentation_001.png
diff --git a/dev/_images/sphx_glr_plot_trainable_segmentation_002.png b/dev/_images/sphx_glr_plot_trainable_segmentation_002.png
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diff --git a/dev/_sources/auto_examples/applications/plot_3d_image_processing.rst.txt b/dev/_sources/auto_examples/applications/plot_3d_image_processing.rst.txt
@@ -351,7 +351,7 @@ will not work either.
 
             interactive(children=(IntSlider(value=34, description='plane', max=59), Output()), _dom_classes=('widget-interact',))
 
-    <function explore_slices.<locals>.display_slice at 0x7fb568d1b6a0>
+    <function explore_slices.<locals>.display_slice at 0x7f53942776a0>
 
 
 
@@ -473,7 +473,7 @@ slices interactively.
 
             interactive(children=(IntSlider(value=34, description='plane', max=59), Output()), _dom_classes=('widget-interact',))
 
-    <function explore_slices.<locals>.display_slice at 0x7fb568f2f6a0>
+    <function explore_slices.<locals>.display_slice at 0x7f539463c040>
 
 
 
@@ -584,7 +584,7 @@ Note that this works in a static HTML page!
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 10.557 seconds)
+   **Total running time of the script:** (0 minutes 10.845 seconds)
 
 
 .. _sphx_glr_download_auto_examples_applications_plot_3d_image_processing.py:

diff --git a/dev/_sources/auto_examples/applications/plot_3d_interaction.rst.txt b/dev/_sources/auto_examples/applications/plot_3d_interaction.rst.txt
@@ -148,7 +148,7 @@ The `imshow` function can display both grayscale and RGB(A) 2D images.
 
     Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers). Got range [64..4095].
 
-    <matplotlib.image.AxesImage object at 0x7f76ff270b00>
+    <matplotlib.image.AxesImage object at 0x7f4e5d3e1880>
 
 
 
@@ -285,9 +285,6 @@ Let us be very specific and pass value ranges on a per-channel basis:
 
 
 
-.. raw:: html
-    :file: images/sphx_glr_plot_3d_interaction_004.html
-
 
 
 
@@ -375,7 +372,7 @@ The biologist's eye can spot that the two bright blobs (best seen in
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 10.788 seconds)
+   **Total running time of the script:** (0 minutes 12.974 seconds)
 
 
 .. _sphx_glr_download_auto_examples_applications_plot_3d_interaction.py:

diff --git a/dev/_sources/auto_examples/applications/plot_3d_structure_tensor.rst.txt b/dev/_sources/auto_examples/applications/plot_3d_structure_tensor.rst.txt
@@ -238,9 +238,6 @@ typical size for strong variations. We shall use this size as the
 
 
 
-.. raw:: html
-    :file: images/sphx_glr_plot_3d_structure_tensor_003.html
-
 
 
 
@@ -349,7 +346,7 @@ where the maximum eigenvalue is found (i.e., ``Z = coords[1]``).
 
 
 .. raw:: html
-    :file: images/sphx_glr_plot_3d_structure_tensor_004.html
+    :file: images/sphx_glr_plot_3d_structure_tensor_003.html
 
 
 
@@ -460,7 +457,7 @@ maximum eigenvalue is found.
 
 
 .. raw:: html
-    :file: images/sphx_glr_plot_3d_structure_tensor_005.html
+    :file: images/sphx_glr_plot_3d_structure_tensor_004.html
 
 
 
@@ -490,7 +487,7 @@ tissue), especially in the Y-Z plane (``longitudinal=1``).
 
 
 .. raw:: html
-    :file: images/sphx_glr_plot_3d_structure_tensor_006.html
+    :file: images/sphx_glr_plot_3d_structure_tensor_005.html
 
 
 
@@ -524,7 +521,7 @@ we would get the pancake situation.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 2.136 seconds)
+   **Total running time of the script:** (0 minutes 2.160 seconds)
 
 
 .. _sphx_glr_download_auto_examples_applications_plot_3d_structure_tensor.py:

diff --git a/dev/_sources/auto_examples/applications/plot_coins_segmentation.rst.txt b/dev/_sources/auto_examples/applications/plot_coins_segmentation.rst.txt
@@ -266,6 +266,9 @@ parts of the histogram of gray values.
    :srcset: /auto_examples/applications/images/sphx_glr_plot_coins_segmentation_007.png
    :class: sphx-glr-single-img
 
+.. raw:: html
+    :file: images/sphx_glr_plot_coins_segmentation_008.html
+
 
 
 
@@ -291,9 +294,9 @@ map starting from the markers determined above:
 
 
 
-.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_coins_segmentation_008.png
+.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_coins_segmentation_009.png
    :alt: segmentation
-   :srcset: /auto_examples/applications/images/sphx_glr_plot_coins_segmentation_008.png
+   :srcset: /auto_examples/applications/images/sphx_glr_plot_coins_segmentation_009.png
    :class: sphx-glr-single-img
 
 
@@ -330,9 +333,9 @@ labeled individually.
 
 
 
-.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_coins_segmentation_009.png
+.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_coins_segmentation_010.png
    :alt: plot coins segmentation
-   :srcset: /auto_examples/applications/images/sphx_glr_plot_coins_segmentation_009.png
+   :srcset: /auto_examples/applications/images/sphx_glr_plot_coins_segmentation_010.png
    :class: sphx-glr-single-img
 
 
@@ -342,7 +345,7 @@ labeled individually.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 2.153 seconds)
+   **Total running time of the script:** (0 minutes 1.956 seconds)
 
 
 .. _sphx_glr_download_auto_examples_applications_plot_coins_segmentation.py:

diff --git a/dev/_sources/auto_examples/applications/plot_colocalization_metrics.rst.txt b/dev/_sources/auto_examples/applications/plot_colocalization_metrics.rst.txt
@@ -177,7 +177,7 @@ much lower than the overlap coefficient.
  .. code-block:: none
 
 
-    np.float64(0.2450786076122774)
+    np.float64(0.34419177880941715)
 
 
 
@@ -250,6 +250,9 @@ every pixel to see the relationship between them.
          :srcset: /auto_examples/applications/images/sphx_glr_plot_colocalization_metrics_003.png
          :class: sphx-glr-multi-img
 
+.. raw:: html
+    :file: images/sphx_glr_plot_colocalization_metrics_004.html
+
 
 .. rst-class:: sphx-glr-script-out
 
@@ -281,7 +284,7 @@ would give us a good measure of how strong the association is.
 
  .. code-block:: none
 
-    PCC: 0.872, p-val: 0
+    PCC: 0.81, p-val: 0
 
 
 
@@ -309,7 +312,7 @@ case.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 1.597 seconds)
+   **Total running time of the script:** (0 minutes 1.569 seconds)
 
 
 .. _sphx_glr_download_auto_examples_applications_plot_colocalization_metrics.py:

diff --git a/dev/_sources/auto_examples/applications/plot_cornea_spot_inpainting.rst.txt b/dev/_sources/auto_examples/applications/plot_cornea_spot_inpainting.rst.txt
@@ -126,9 +126,6 @@ represented as grayscale.
 
 
 
-.. raw:: html
-    :file: images/sphx_glr_plot_cornea_spot_inpainting_001.html
-
 
 
 
@@ -171,9 +168,9 @@ variance.
 
 
 
-.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_002.png
+.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_001.png
    :alt: Image median over time, Image variance over time
-   :srcset: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_002.png
+   :srcset: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_001.png
    :class: sphx-glr-single-img
 
 
@@ -247,9 +244,9 @@ it is easier for us to compare them:
 
 
 
-.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_003.png
+.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_002.png
    :alt: block_size = 21, block_size = 43
-   :srcset: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_003.png
+   :srcset: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_002.png
    :class: sphx-glr-single-img
 
 
@@ -281,9 +278,9 @@ closer to the desired results.
 
 
 
-.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_004.png
+.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_003.png
    :alt: No offset, Offset = 15
-   :srcset: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_004.png
+   :srcset: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_003.png
    :class: sphx-glr-single-img
 
 
@@ -318,9 +315,9 @@ lines, while preserving the shape and size of larger objects.
 
 
 
-.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_005.png
+.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_004.png
    :alt: mask before, after opening
-   :srcset: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_005.png
+   :srcset: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_004.png
    :class: sphx-glr-single-img
 
 
@@ -355,9 +352,9 @@ Next, we can make the detected areas wider by applying a dilation filter:
 
 
 
-.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_006.png
+.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_005.png
    :alt: Before, After dilation
-   :srcset: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_006.png
+   :srcset: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_005.png
    :class: sphx-glr-single-img
 
 
@@ -464,9 +461,9 @@ parameter).
 
 
 
-.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_007.png
+.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_006.png
    :alt: Segmented spots over restored image
-   :srcset: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_007.png
+   :srcset: /auto_examples/applications/images/sphx_glr_plot_cornea_spot_inpainting_006.png
    :class: sphx-glr-single-img
 
 
@@ -495,7 +492,7 @@ the opening processing step, when removing fine-grained features.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 29.626 seconds)
+   **Total running time of the script:** (0 minutes 28.467 seconds)
 
 
 .. _sphx_glr_download_auto_examples_applications_plot_cornea_spot_inpainting.py:

diff --git a/dev/_sources/auto_examples/applications/plot_face_detection.rst.txt b/dev/_sources/auto_examples/applications/plot_face_detection.rst.txt
@@ -134,7 +134,7 @@ using `OpenCV train cascade utility
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 0.392 seconds)
+   **Total running time of the script:** (0 minutes 0.456 seconds)
 
 
 .. _sphx_glr_download_auto_examples_applications_plot_face_detection.py:

diff --git a/dev/_sources/auto_examples/applications/plot_fluorescence_nuclear_envelope.rst.txt b/dev/_sources/auto_examples/applications/plot_fluorescence_nuclear_envelope.rst.txt
@@ -119,9 +119,6 @@ The dataset is a 2D image stack with 15 frames (time points) and 2 channels.
 
 
 
-.. raw:: html
-    :file: images/sphx_glr_plot_fluorescence_nuclear_envelope_001.html
-
 
 
 
@@ -285,9 +282,9 @@ Let us visualize these processing steps in a sequence of subplots.
 
 
 
-.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_fluorescence_nuclear_envelope_002.png
+.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_fluorescence_nuclear_envelope_001.png
    :alt: a) Raw, b) Blur, c) Threshold, c-1) Fill in, c-2) Keep one nucleus, d) Dilate, e) Erode, f) Nucleus Rim
-   :srcset: /auto_examples/applications/images/sphx_glr_plot_fluorescence_nuclear_envelope_002.png
+   :srcset: /auto_examples/applications/images/sphx_glr_plot_fluorescence_nuclear_envelope_001.png
    :class: sphx-glr-single-img
 
 
@@ -324,9 +321,9 @@ it as a mask to measure the intensity in the second channel.
 
 
 
-.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_fluorescence_nuclear_envelope_003.png
+.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_fluorescence_nuclear_envelope_002.png
    :alt: Second channel (raw), Selection
-   :srcset: /auto_examples/applications/images/sphx_glr_plot_fluorescence_nuclear_envelope_003.png
+   :srcset: /auto_examples/applications/images/sphx_glr_plot_fluorescence_nuclear_envelope_002.png
    :class: sphx-glr-single-img
 
 
@@ -597,9 +594,9 @@ regions.
 
 
 
-.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_fluorescence_nuclear_envelope_004.png
+.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_fluorescence_nuclear_envelope_003.png
    :alt: Change in fluorescence intensity at the nuclear envelope
-   :srcset: /auto_examples/applications/images/sphx_glr_plot_fluorescence_nuclear_envelope_004.png
+   :srcset: /auto_examples/applications/images/sphx_glr_plot_fluorescence_nuclear_envelope_003.png
    :class: sphx-glr-single-img
 
 
@@ -615,7 +612,7 @@ time points, and then becomes roughly constant.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 4.490 seconds)
+   **Total running time of the script:** (0 minutes 4.582 seconds)
 
 
 .. _sphx_glr_download_auto_examples_applications_plot_fluorescence_nuclear_envelope.py:

diff --git a/...uto_examples/applications/plot_haar_extraction_selection_classification.rst.txt b/...uto_examples/applications/plot_haar_extraction_selection_classification.rst.txt
@@ -282,15 +282,15 @@ Once the features are extracted, we can train and test a new classifier.
 
  .. code-block:: none
 
-    Computing the full feature set took 28.379s, plus 2.690s training, for an AUC of 1.00. Computing the restricted feature set took 0.099s, plus 2.208s training, for an AUC of 1.00.
+    Computing the full feature set took 28.624s, plus 2.918s training, for an AUC of 1.00. Computing the restricted feature set took 0.164s, plus 2.389s training, for an AUC of 1.00.
 
 
 
 
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 36.263 seconds)
+   **Total running time of the script:** (0 minutes 37.659 seconds)
 
 
 .. _sphx_glr_download_auto_examples_applications_plot_haar_extraction_selection_classification.py:

diff --git a/dev/_sources/auto_examples/applications/plot_human_mitosis.rst.txt b/dev/_sources/auto_examples/applications/plot_human_mitosis.rst.txt
@@ -350,9 +350,6 @@ by dichotomy, visually and manually.
    :srcset: /auto_examples/applications/images/sphx_glr_plot_human_mitosis_005.png
    :class: sphx-glr-single-img
 
-.. raw:: html
-    :file: images/sphx_glr_plot_human_mitosis_006.html
-
 
 
 
@@ -445,9 +442,9 @@ label with argument `bg_label=0`.
 
 
 
-.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_human_mitosis_007.png
+.. image-sg:: /auto_examples/applications/images/sphx_glr_plot_human_mitosis_006.png
    :alt: Overlapping nuclei, Segmented nuclei
-   :srcset: /auto_examples/applications/images/sphx_glr_plot_human_mitosis_007.png
+   :srcset: /auto_examples/applications/images/sphx_glr_plot_human_mitosis_006.png
    :class: sphx-glr-single-img
 
 
@@ -522,7 +519,7 @@ cells in this sample. Therefore, we estimate the mitotic index to be:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 3.164 seconds)
+   **Total running time of the script:** (0 minutes 3.200 seconds)
 
 
 .. _sphx_glr_download_auto_examples_applications_plot_human_mitosis.py:

diff --git a/dev/_sources/auto_examples/applications/plot_image_comparison.rst.txt b/dev/_sources/auto_examples/applications/plot_image_comparison.rst.txt
@@ -192,7 +192,7 @@ Blend
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 2.784 seconds)
+   **Total running time of the script:** (0 minutes 2.671 seconds)
 
 
 .. _sphx_glr_download_auto_examples_applications_plot_image_comparison.py: