SLEAP v1.2.3 (#727)

* Add support for new maDLC labels format (#678) * Supervised Identity Prediction (#460) (#679) * squash merge from roomrys/sleap-1 (#460) * Add test dataset with tracks * Add track indices to labels provider * Add identity class map generator * Update docstring * Add class map model trainer, head and config * Add inference * Docs and tests for identity module - Slightly modified matching to greedy-like behavior * Fix inference - Add imports to evals inference - Move the common Predictor.predict() method to base class - Fix docstrings for new inference classes - Add test model and integration test * Generate tracks from config metadata if not provided * Force typecasting in identity functions * Force boolean masking op * Clean up inference module - Move common Predictor methods to base class - Switch to `model.predict_on_batch()` for massive performance increase with `predictor.predict()`. - Enable prediction directly on arrays (slow) * Enable Qt5Agg backend only when necessary during training * Top-down supervised identity prediction (#476) * Add sizematcher to new training pipelines * Fix topdown ID visualization during training * Add LabeledFrame.tracked_instances property for filtering - Greedy checking in has_* properties * Add Labels.copy() method for creating deep copies - Works by serializing and deserializing to JSON (inefficient, but guaranteed to work since we have lots of coverage on I/O) * Extract labels with tracked instances - Add copy kwarg to extract to return deep copies - Remove user and/or untracked instances in with_user_labels_only(). Previously this functionality was blocked since we couldn't remove the instances from labeled frames without affecting the source labels. - Add remove_untracked_instances() utility for filtering out instances from the labels. * Add track filtering in LabelsReader provider - This is slightly redundant with Labels.with_user_labels_only(..., with_track_only=True) but serves as an extra guarantee that we don't train on instances without tracks accidentally, regardless of how the data is preprocessed. Can still emit "empty" frames if no instances have tracks set, however. * Add track filtering in DataReaders during training - Auto-enabled when training from ID models - Filters out instances without tracks BEFORE train/val splitting - Split is now done on copy of labels - Fix DataReaders arg typing - Tests for DataReaders * Add crop size detection to topdown ID models - Add training integration test for topdown ID * add removal of untracked instances for labeled instances (#460) * Add removal of untracked instances for labeled instances - previously used `LabeledFrame.tracked_instances()` which only returns predicted instances with tracking - created `LabeledFrame.remove_untracked` which returns both user labeled and predicted instances with tracking * Formatting - using black v20.8b1 * add tests for Labels and LabeledFrames (#460) * Add tests - test `Labels.remove_untracked_instances()` for both cases of `remove_empty_frames: bool` -test `LabeledFrames.remove_untracked()` for both user-labeled and predicted frames * formatting (#460) * add newline (no indent) at end of files which had failed Lint test * clean-up comments and unneeded parenthesis (#460) * Last merge fixes * Lint * Bump minor version (#684) * Fix numpy conversion in inference (#687) * Expose identity module in nn * Override predict_on_batch to optionally cast data to numpy * Fix topological sorting to always start with root node (#688) * Fix topological sorting to always start with root node * Add test * Create unique default shortcuts (#686) (#690) * Training monitor enhancements (#691) * Training monitor enhancements - Cleaned up imports - Docstrings - Now update based on time, not epochs - Added markers for epoch-level losses - Added best validation loss marker and text - Reduced minimum possible y-axis value when log scaling - Marker colors, alpha, sizes and line widths adjusted * Move training monitor to gui submodule * add metrics to training monitor title * add mean time per epoch * add ETA to finish next 10 epochs * add plateau patience fraction (when in plateau) * update dev_requirements to install version of click that does not break black * Add code coverage * add coverage for all lines within LossViewer.update_runtime() Co-authored-by: roomrys <[email protected]> * add hide instance menu item and hotkey (#692) * Single press of hotkey (H) toggles instance visibility * Add instance visibility message/warning to status bar * Resize keyboard shortcuts dialog box * Fix formatting to read and save tracking scores (#693) * Update formatting to include tracking_scores * Add formatting fixtures, tracking_scores test * Hide predicted instances with hotkey (#694) * add hide instance menu item and hotkey * single press of hotkey (H) toggles instance visibility * Add instance visibility message to status bar * Resize keyboard shortcuts dialog box * Make shortcuts pop-up slightly narrower and taller * Hide predicted instances as well * hide predicted instances * update status bar message: - count only visible predicted and labeled instances - only show "hidden instances" warning when number instances in frame is greater than 0 - normal font weight * Logic update for detecting instances to show * Add test for instance visibility * Change which qtbot wait is used * Change timeout of qtbot.waitActive - attempt to pass ubuntu tests on github actions * Use arbitrary qtbot.wait Hope to verify that ubuntu test fails due to a waiting error * Add test for instance colors - predict ubuntu test will fail * Add test skip mark for ubuntu * Import pytest * Skip test for linux * Remove unused packages * Talmo/pre v1.2.2 (#696) * Change default tab appearance * Bump to 1.2.2 * Add more notebooks to docs (#698) * Fix missing links and update content * Add new notebooks * Add troubleshooting guide * Datasets and paper link update * Add support for new single animal DLC format (#704) * Add support for single animal DLC files (#702) * Add test for new format single animal DLC * Add test images for visual verification * Add data and test for old version single animal DLC file * Add edges to analysis h5 (#707) * Add edge names and edge indices to analysis h5 * Add test for node names and edge names in analysis h5 export * Speed-up labeling suggestions look-up (#709) * Use data cache to speed-up labeling suggestions * Move logic from Labels.__getitem__ to Labels.get * Use Labels.__getitem__ as a wrapper to Labels.get * Add support for AlphaTracker import (#716) * Add support for AlphaTrackor import * Integrate adaptor into sleap * Add tests * Specify pip version in environment_no_cuda.yml * Specify pip version in environment.yml * Remove pip version from environment_no_cuda.yml * Specify channel and version for pip in environment_no_cuda * Add GUI-based test * Add property tests and lint * Delete condaenv.25edtblj.requirements.txt Co-authored-by: Talmo Pereira <[email protected]> * Update links from murthylab to talmolab (#724) * Update links from murthylab to talmolab * Add conda channel for pip install in no cuda yml * Add try/except for release checker * Update rest API link * SLEAP v1.2.3 (#726) * Update links from murthylab to talmolab * Add conda channel for pip install in no cuda yml * Add try/except for release checker * Update rest API link * Update pip in all environments * Update to v1.2.3 * Fix typo on the datasets Co-authored-by: sheridana <[email protected]> Co-authored-by: roomrys <[email protected]> Co-authored-by: sheridana <[email protected]>
talmolab · May 10, 2022 · d5f8b61 · d5f8b61
1 parent dd34399
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diff --git a/.conda/meta.yaml b/.conda/meta.yaml
@@ -35,7 +35,7 @@ requirements:
     - shapely=1.7.1
     - conda-forge::pandas
     - ffmpeg
-    - pip
+    - conda-forge::pip<=22.0.3
 
   run:
     - python=3.7
@@ -52,7 +52,7 @@ requirements:
     - cudatoolkit=11.3.1
     - cudnn=8.2.1
     - nvidia::cuda-nvcc=11.3
-    - pip
+    - conda-forge::pip<=22.0.3
 
   run_constrained:
     - pyqt==9999999999

diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md
@@ -15,8 +15,8 @@
 
 ### Outside contributors checklist
 
-- [ ] Review the [guidelines for contributing](https://github.com/murthylab/sleap/wiki/Developer-Guide) to this repository
-- [ ] Read and sign the [CLA](https://github.com/murthylab/sleap/blob/develop/sleap-cla.pdf) and add yourself to the [authors list](https://github.com/murthylab/sleap/blob/develop/AUTHORS)
+- [ ] Review the [guidelines for contributing](https://github.com/talmolab/sleap/wiki/Developer-Guide) to this repository
+- [ ] Read and sign the [CLA](https://github.com/talmolab/sleap/blob/develop/sleap-cla.pdf) and add yourself to the [authors list](https://github.com/talmolab/sleap/blob/develop/AUTHORS)
 - [ ] Make sure you are making a pull request against the **develop** branch (not *main*). Also you should start *your branch* off *develop*
 - [ ] Add tests that prove your fix is effective or that your feature works
 - [ ] Add necessary documentation (if appropriate)

diff --git a/README.rst b/README.rst
@@ -1,17 +1,17 @@
 |CI| |Coverage| |Documentation| |Downloads| |Stable version| |Latest version|
 
 .. |CI| image:: 
-   https://github.com/murthylab/sleap/workflows/CI/badge.svg?event=push&branch=develop
-   :target: https://github.com/murthylab/sleap/actions?query=workflow:CI
+   https://github.com/talmolab/sleap/workflows/CI/badge.svg?event=push&branch=develop
+   :target: https://github.com/talmolab/sleap/actions?query=workflow:CI
    :alt: Continuous integration status
 
 .. |Coverage| image::
-   https://codecov.io/gh/murthylab/sleap/branch/develop/graph/badge.svg?token=YWQYBN6820
-   :target: https://codecov.io/gh/murthylab/sleap
+   https://codecov.io/gh/talmolab/sleap/branch/develop/graph/badge.svg?token=YWQYBN6820
+   :target: https://codecov.io/gh/talmolab/sleap
    :alt: Coverage
 
 .. |Documentation| image:: 
-   https://img.shields.io/github/workflow/status/murthylab/sleap/Build%20website?label=Documentation
+   https://img.shields.io/github/workflow/status/talmolab/sleap/Build%20website?label=Documentation
    :target: https://sleap.ai
    :alt: Documentation
 
@@ -20,12 +20,12 @@
    :target: https://pepy.tech/project/sleap
    :alt: Downloads
 
-.. |Stable version| image:: https://img.shields.io/github/v/release/murthylab/sleap?label=stable
-   :target: https://github.com/murthylab/sleap/releases/
+.. |Stable version| image:: https://img.shields.io/github/v/release/talmolab/sleap?label=stable
+   :target: https://github.com/talmolab/sleap/releases/
    :alt: Stable version
 
-.. |Latest version| image:: https://img.shields.io/github/v/release/murthylab/sleap?include_prereleases&label=latest
-   :target: https://github.com/murthylab/sleap/releases/
+.. |Latest version| image:: https://img.shields.io/github/v/release/talmolab/sleap?include_prereleases&label=latest
+   :target: https://github.com/talmolab/sleap/releases/
    :alt: Latest version
 
 
@@ -57,7 +57,7 @@ Get some SLEAP
 --------------
 SLEAP is installed as a Python package. We strongly recommend using `Miniconda <https://https://docs.conda.io/en/latest/miniconda.html>`_ to install SLEAP in its own environment.
 
-You can find the latest version of SLEAP in the `Releases <https://github.com/murthylab/sleap/releases>`_ page.
+You can find the latest version of SLEAP in the `Releases <https://github.com/talmolab/sleap/releases>`_ page.
 
 Quick install
 ^^^^^^^^^^^^^
@@ -138,7 +138,7 @@ Follow `@talmop <https://twitter.com/talmop>`_ on Twitter for news and updates!
 **Technical issue with the software?**
 
 1. Check the `Help page <https://sleap.ai/help.html>`_.
-2. Search the `issues on GitHub <https://github.com/murthylab/sleap/issues>`_ or open a new one.
+2. Search the `issues on GitHub <https://github.com/talmolab/sleap/issues>`_ or open a new one.
 
 
 **General inquiries?**
@@ -170,7 +170,7 @@ This work was made possible through our funding sources, including:
 
 License
 -------
-SLEAP is released under a `Clear BSD License <https://raw.githubusercontent.com/murthylab/sleap/main/LICENSE>`_ and is intended for research/academic use only. For commercial use, please contact: Laurie Tzodikov (Assistant Director, Office of Technology Licensing), Princeton University, 609-258-7256.
+SLEAP is released under a `Clear BSD License <https://raw.githubusercontent.com/talmolab/sleap/main/LICENSE>`_ and is intended for research/academic use only. For commercial use, please contact: Laurie Tzodikov (Assistant Director, Office of Technology Licensing), Princeton University, 609-258-7256.
 
 
 .. end-inclusion-marker-do-not-remove

diff --git a/docs/conf.py b/docs/conf.py
@@ -28,15 +28,15 @@
 copyright = f"2019–{date.today().year}, Talmo Lab"
 
 # The short X.Y version
-version = "1.2.2"
+version = "1.2.3"
 
 # Get the sleap version
 # with open("../sleap/version.py") as f:
 #     version_file = f.read()
 #     version = re.search("\d.+(?=['\"])", version_file).group(0)
 
 # Release should be the full branch name
-release = "v1.2.2"
+release = "v1.2.3"
 
 html_title = f"SLEAP ({release})"
 html_short_title = "SLEAP"
@@ -100,7 +100,7 @@ def linkcode_resolve(domain, info):
         filename = docs.utils.resolve(info["module"], info["fullname"])
         if filename is None:
             return None
-        return f"https://github.com/murthylab/sleap/blob/{release}/{filename}"
+        return f"https://github.com/talmolab/sleap/blob/{release}/{filename}"
     except:
         print(info)
         raise
@@ -132,7 +132,7 @@ def linkcode_resolve(domain, info):
     # "light_logo": "logo.png",
     # "dark_logo": "logo.png",
     # https://sphinx-book-theme.readthedocs.io/en/stable/customize/index.html#theme-options
-    "repository_url": "https://github.com/murthylab/sleap",
+    "repository_url": "https://github.com/talmolab/sleap",
     "use_download_button": False,
     "use_fullscreen_button": False,
     "use_repository_button": True,

diff --git a/docs/datasets.md b/docs/datasets.md
@@ -115,7 +115,7 @@ widths: 10 40
 * - Labels
   - 1000 frames, 2950 instances
 * - Download
-  - [Train](https://storage.googleapis.com/sleap-data/datasets/wang_4mice_john/labels.full/random_split1/test.pkg.slp) / [Validation](https://storage.googleapis.com/sleap-data/datasets/wang_4mice_john/labels.full/random_split1/val.pkg.slp) / [Test](https://storage.googleapis.com/sleap-data/datasets/wang_4mice_john/labels.full/random_split1/test.pkg.slp)
+  - [Train](https://storage.googleapis.com/sleap-data/datasets/wang_4mice_john/labels.full/random_split1/train.pkg.slp) / [Validation](https://storage.googleapis.com/sleap-data/datasets/wang_4mice_john/labels.full/random_split1/val.pkg.slp) / [Test](https://storage.googleapis.com/sleap-data/datasets/wang_4mice_john/labels.full/random_split1/test.pkg.slp)
 * - Credit
   - [Pereira et al. (2022)](https://www.nature.com/articles/s41592-022-01426-1), John D'Uva, Mikhail Kislin, Samuel S.-H. Wang
 ```

diff --git a/docs/guides/cli.rst b/docs/guides/cli.rst
@@ -296,7 +296,7 @@ Debugging
 ``sleap-diagnostic``
 ++++++++++++++++++++
 
-There's also a script to output diagnostic information which may help us if you need to contact us about problems installing or running SLEAP. If you were able to install the SLEAP Python package, you can run this script with :code:`sleap-diagnostic`. Otherwise, you can download `diagnostic.py <https://raw.githubusercontent.com/murthylab/sleap/main/sleap/diagnostic.py>`_ and run :code:`python diagnostic.py`.
+There's also a script to output diagnostic information which may help us if you need to contact us about problems installing or running SLEAP. If you were able to install the SLEAP Python package, you can run this script with :code:`sleap-diagnostic`. Otherwise, you can download `diagnostic.py <https://raw.githubusercontent.com/talmolab/sleap/main/sleap/diagnostic.py>`_ and run :code:`python diagnostic.py`.
 
 
 .. code-block:: none

diff --git a/docs/guides/custom-training.md b/docs/guides/custom-training.md
@@ -8,7 +8,7 @@ Hyperparameters include the model architecture, learning rate, and data augmenta
 
 This guide will explain how to create a custom training profile but doesn't cover how to decide what the hyperpameters should be. For more information about the hyperparameters, see our guide to {ref}`choosing-models`.
 
-Training profiles are JSON files. The JSON format is fairly easy to read (and edit) with a text-editor and you can use the default "baseline" profiles as a starting point for creating your own training profiles. For example, take a look at the [baseline bottom-up profile](https://github.com/murthylab/sleap/blob/main/sleap/training_profiles/baseline_medium_rf.bottomup.json) or our [other baseline profiles](https://github.com/murthylab/sleap/blob/main/sleap/training_profiles).
+Training profiles are JSON files. The JSON format is fairly easy to read (and edit) with a text-editor and you can use the default "baseline" profiles as a starting point for creating your own training profiles. For example, take a look at the [baseline bottom-up profile](https://github.com/talmolab/sleap/blob/main/sleap/training_profiles/baseline_medium_rf.bottomup.json) or our [other baseline profiles](https://github.com/talmolab/sleap/blob/main/sleap/training_profiles).
 
 But if this sounds intimidating, you don't have to edit the JSON file by hand! You can use the same GUI that's used for training on a local machine to export custom training profiles.
 
@@ -46,4 +46,4 @@ for each model you want to train (where `path/to/custom/profile.json` should be
 
 ```{note}
 If you exported the training package as a ZIP file, it contains both the `.pkg.slp` and `.json` files necessary to train with the configuration you selected in the GUI. Before running the [`sleap-train`](sleap-train) command, make sure to unzip this file.
-```
+```
diff --git a/docs/guides/remote.md b/docs/guides/remote.md
@@ -28,7 +28,7 @@ But in most cases it's best to create a training job package and just use that f
 
 **Training profile**:
 
-SLEAP comes with "default" training profiles for training confidence maps, part affinity fields, centroids, or top-down confidence maps (which allow multi-instance inference without using part affinity fields). Any file in the [training_profiles](https://github.com/murthylab/sleap/tree/main/sleap/training_profiles) directory of the SLEAP package can be used by specifying its filename (e.g., {code}`baseline_medium_rf.bottomup.json`) as the training profile—the full path isn't required to use these built-in profiles.
+SLEAP comes with "default" training profiles for training confidence maps, part affinity fields, centroids, or top-down confidence maps (which allow multi-instance inference without using part affinity fields). Any file in the [training_profiles](https://github.com/talmolab/sleap/tree/main/sleap/training_profiles) directory of the SLEAP package can be used by specifying its filename (e.g., {code}`baseline_medium_rf.bottomup.json`) as the training profile—the full path isn't required to use these built-in profiles.
 
 Our guide to [custom-training] explains how to use the GUI to export custom training profiles. You can also use the {code}`initial_config.json` file saved from previous training run as a template for a new training config. You can copy the {code}`json` file and edit it in any text editor.
 

diff --git a/docs/guides/troubleshooting-workflows.md b/docs/guides/troubleshooting-workflows.md
@@ -25,6 +25,6 @@ performance by tuning hyperparameters that don't perform as well with little dat
 ![Stage 3 troubleshooting workflow](../_static/troubleshooting_stage3.png)
 
 If you still aren't getting good results, feel free to reach out by emailing us at
-`[email protected]` or opening a [Github Issue](https://github.com/murthylab/sleap/issues) 
+`[email protected]` or opening a [Github Issue](https://github.com/talmolab/sleap/issues) 
 and tell us a bit about your data (preferably with sample screenshots/clips) and what
-kinds of problems you're facing.
+kinds of problems you're facing.
diff --git a/docs/help.md b/docs/help.md
@@ -9,7 +9,7 @@ Stuck? Can't get SLEAP to run? Crashing? Try the recommended tips below.
 
 Have you tried all of the steps in the [installation instructions](installation)?
 
-If so, please feel free to [open an issue](https://github.com/murthylab/sleap/issues) and tell us how you're trying to install it, what error messages you're getting and which operating system you're on.
+If so, please feel free to [open an issue](https://github.com/talmolab/sleap/issues) and tell us how you're trying to install it, what error messages you're getting and which operating system you're on.
 
 ### Can I install it on a computer without a GPU?
 
@@ -73,10 +73,10 @@ Check out the [Analysis examples](notebooks/Analysis_examples) notebooks.
 
 ### I've found a bug or have another problem!
 
-Feel free to [open an issue](https://github.com/murthylab/sleap/issues) and we'll get back to you as soon as we can!
+Feel free to [open an issue](https://github.com/talmolab/sleap/issues) and we'll get back to you as soon as we can!
 
 ### Can I just talk to someone?
 
 SLEAP is a complex machine learning system intended for general use, so it's possible that we failed to consider the specifics of the situation in which you may be interested in using it with.
 
-Feel free to reach out to us at `[email protected]` if you have a question that isn't covered here.
+Feel free to reach out to us at `[email protected]` if you have a question that isn't covered here.
diff --git a/docs/index.rst b/docs/index.rst
@@ -17,6 +17,6 @@ SLEAP Documentation
     notebooks/index
     Developer API <api>
     datasets
-    GitHub <https://github.com/murthylab/sleap>
-    Releases <https://github.com/murthylab/sleap/releases>
+    GitHub <https://github.com/talmolab/sleap>
+    Releases <https://github.com/talmolab/sleap/releases>
     help
diff --git a/docs/installation.md b/docs/installation.md
@@ -4,7 +4,7 @@ SLEAP can be installed as a Python package on Windows, Linux and Mac OS X. We cu
 
 SLEAP requires many complex dependencies, so we **strongly** recommend using [Miniconda](https://docs.conda.io/en/latest/miniconda.html) to install it in its own isolated environment. See {ref}`Installing Miniconda<miniconda>` below for more instructions.
 
-The newest version of SLEAP can always be found in the [Releases page](https://github.com/murthylab/sleap/releases).
+The newest version of SLEAP can always be found in the [Releases page](https://github.com/talmolab/sleap/releases).
 
 ```{contents} Contents
 ---
@@ -55,7 +55,7 @@ On Windows, our personal preference is to use alternative terminal apps like [Cm
 ````
 ### `conda` package
 ```bash
-conda create -y -n sleap -c sleap -c nvidia -c conda-forge sleap=1.2.2
+conda create -y -n sleap -c sleap -c nvidia -c conda-forge sleap=1.2.3
 ```
 **This is the recommended installation method**. Works on **Windows** and **Linux**.
 
@@ -68,7 +68,7 @@ conda create -y -n sleap -c sleap -c nvidia -c conda-forge sleap=1.2.2
 ### `conda` from source
 1. First, clone the repository:
    ```bash
-   git clone https://github.com/murthylab/sleap && cd sleap
+   git clone https://github.com/talmolab/sleap && cd sleap
    ```
 
 2. Then, install from the environment file:
@@ -84,7 +84,7 @@ This works on **Windows**, **Linux** and **Mac OS X** (pre-M1). This is the **re
 
 ### `pip` package
 ```bash
-pip install sleap==1.2.2
+pip install sleap==1.2.3
 ```
 This works on **any OS** and on **Google Colab**.
 ```{note}
@@ -125,7 +125,7 @@ SLEAP can be installed on newer M1 Macs by following these instructions:
 
 5. **Download the SLEAP M1 branch**:
    ```bash
-   cd ~ && git clone -b talmo/m1 --single-branch https://github.com/murthylab/sleap.git sleap_m1 && cd sleap_m1
+   cd ~ && git clone -b talmo/m1 --single-branch https://github.com/talmolab/sleap.git sleap_m1 && cd sleap_m1
    ```
    *Note:* This installs SLEAP in development mode, so changes to the source code are immediately applied in case you wanted to mess around with it. You can also just do a `git pull` to update it (no need to re-do any of the previous steps).
 
@@ -140,7 +140,7 @@ SLEAP can be installed on newer M1 Macs by following these instructions:
    conda activate sleap_m1 && sleap-label
    ```
 
-See [this Issue](https://github.com/murthylab/sleap/issues/579#issuecomment-1028602327) for more information on M1 support.
+See [this Issue](https://github.com/talmolab/sleap/issues/579#issuecomment-1028602327) for more information on M1 support.
 
 
 ## Testing that things are working
@@ -242,7 +242,7 @@ Once the environment has been removed, you are free to install SLEAP using any o
 
 
 ## Getting help
-If you run into any problems, check out the [GitHub Issues](https://github.com/murthylab/sleap/issues) to see if others have had the same problem.
+If you run into any problems, check out the [GitHub Issues](https://github.com/talmolab/sleap/issues) to see if others have had the same problem.
 
 If you get any errors or the GUI fails to launch, try running the diagnostics to see what SLEAP is able to detect on your system:
 ```bash
@@ -254,4 +254,4 @@ If you were not able to get SLEAP installed, activate the conda environment it i
 conda list
 ```
 
-Then, [open a new Issue](https://github.com/murthylab/sleap/issues) providing the versions from either command above, as well as any errors you saw in the console during the installation.
+Then, [open a new Issue](https://github.com/talmolab/sleap/issues) providing the versions from either command above, as well as any errors you saw in the console during the installation.