SLEAP 1.3.3 (#1505)

* Do not try to remove item if already deleted (#1498)

* Set `LD_LIBRARY_PATH` on `mamba activate` (#1496)

* Add version restrictions to tensorflow for pypi (#1485)

* Remove `imageio` pin (#1501)

* Reset LD_LIBRARY_PATH on deactivate (#1502)

* Brown bag bump to 1.3.3 (#1484)

.conda/README.md

@@ -3,7 +3,7 @@ This folder defines the conda package build for Linux and Windows. There are run
 To build, first go to the base repo directory and install the build environment:
 
 ```
-conda env create -f environment_build.yml -n sleap_build && conda activate sleap_build
+mamba env create -f environment_build.yml -n sleap_build && conda activate sleap_build
 ```
 
 And finally, run the build command pointing to this directory:
@@ -15,7 +15,7 @@ conda build .conda --output-folder build -c conda-forge -c nvidia -c https://con
 To install the local package:
 
 ```
-conda create -n sleap_0 -c conda-forge -c nvidia -c ./build -c https://conda.anaconda.org/sleap/ -c anaconda sleap=x.x.x
+mamba create -n sleap_0 -c conda-forge -c nvidia -c ./build -c https://conda.anaconda.org/sleap/ -c anaconda sleap=x.x.x
 ```
 
 replacing x.x.x with the version of SLEAP that you just built.

.conda/build.sh

@@ -12,4 +12,12 @@ pip install --no-cache-dir -r ./requirements.txt
 
 # Install sleap itself. This does not install the requirements, but will list which 
 # requirements are missing (see "install_requires") when user attempts to install.
-python setup.py install --single-version-externally-managed --record=record.txt
+python setup.py install --single-version-externally-managed --record=record.txt
+
+# Copy the activate scripts to $PREFIX/etc/conda/activate.d.
+# This will allow them to be run on environment activation.
+for CHANGE in "activate" "deactivate"
+do
+    mkdir -p "${PREFIX}/etc/conda/${CHANGE}.d"
+    cp "${RECIPE_DIR}/${PKG_NAME}_${CHANGE}.sh" "${PREFIX}/etc/conda/${CHANGE}.d/${PKG_NAME}_${CHANGE}.sh"
+done

.conda/sleap_activate.sh

@@ -0,0 +1,6 @@
+#!/bin/sh
+
+# Remember the old library path for when we deactivate
+export SLEAP_OLD_LD_LIBRARY_PATH=$LD_LIBRARY_PATH
+# Help CUDA find GPUs!
+export LD_LIBRARY_PATH=$CONDA_PREFIX/lib:$LD_LIBRARY_PATH

.conda/sleap_deactivate.sh

@@ -0,0 +1,4 @@
+#!/bin/sh
+
+# Reset to the old library path for when deactivating the environment
+export LD_LIBRARY_PATH=$SLEAP_OLD_LD_LIBRARY_PATH

.github/ISSUE_TEMPLATE/bug_report.md

@@ -28,7 +28,7 @@ Please include information about how you installed.
 - OS:
 <!-- [e.g. ubuntu 20.04, macOS 11.0] -->
 - Version(s):
-<!-- e.g. [SLEAP v1.3.2, python 3.8] --->
+<!-- e.g. [SLEAP v1.3.3, python 3.8] --->
 - SLEAP installation method (listed [here](https://sleap.ai/installation.html#)):
   - [ ] [Conda from package](https://sleap.ai/installation.html#conda-package)
   - [ ] [Conda from source](https://sleap.ai/installation.html#conda-from-source)

docs/conf.py

@@ -28,15 +28,15 @@
 copyright = f"2019–{date.today().year}, Talmo Lab"
 
 # The short X.Y version
-version = "1.3.2"
+version = "1.3.3"
 
 # 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 = "v1.3.2"
+release = "v1.3.3"
 
 html_title = f"SLEAP ({release})"
 html_short_title = "SLEAP"

docs/installation.md

@@ -232,7 +232,7 @@ Although you do not need Mambaforge installed to perform a `pip install`, we rec
 3. Finally, we can perform the `pip install`:
 
    ```bash
-   pip install sleap[pypi]==1.3.2
+   pip install sleap[pypi]==1.3.3
    ```
 
    This works on **any OS except Apple silicon** and on **Google Colab**.
@@ -343,10 +343,45 @@ python -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU')
 ````{warning}
 TensorFlow 2.7+ is currently failing to detect CUDA Toolkit and CuDNN on some systems (see [Issue thread](https://github.com/tensorflow/tensorflow/issues/52988)).
 
-If you run into issues, try downgrading the TensorFlow 2.6:
+If you run into issues, either try downgrading the TensorFlow 2.6:
 ```bash
 pip install tensorflow==2.6.3
 ```
+or follow the note below.
+````
+
+````{note}
+If you are on Linux, have a NVIDIA GPU, but cannot detect your GPU:
+
+```bash
+W tensorflow/stream_executor/platform/default/dso_loader.cc:64 Could not load dynamic 
+library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object 
+file: No such file or directory
+```
+
+then activate the environment:
+
+```bash
+mamba activate sleap
+```
+
+and run the commands:
+```bash
+mkdir -p $CONDA_PREFIX/etc/conda/activate.d
+echo '#!/bin/sh' >> $CONDA_PREFIX/etc/conda/activate.d/sleap_activate.sh
+echo 'export SLEAP_OLD_LD_LIBRARY_PATH=$LD_LIBRARY_PATH' >> $CONDA_PREFIX/etc/conda/activate.d/sleap_activate.sh
+echo 'export LD_LIBRARY_PATH=$CONDA_PREFIX/lib:$LD_LIBRARY_PATH' >> $CONDA_PREFIX/etc/conda/activate.d/sleap_activate.sh
+source $CONDA_PREFIX/etc/conda/activate.d/sleap_activate.sh
+```
+
+This will set the environment variable `LD_LIBRARY_PATH` each time the environment is activated. The environment variable will remain set in the current terminal even if we deactivate the environment. Although not strictly necessary, if you would also like the environment variable to be reset to the original value when deactivating the environment, we can run the following commands:
+```bash
+mkdir -p $CONDA_PREFIX/etc/conda/deactivate.d
+echo '#!/bin/sh' >> $CONDA_PREFIX/etc/conda/deactivate.d/sleap_deactivate.sh
+echo 'export LD_LIBRARY_PATH=$SLEAP_OLD_LD_LIBRARY_PATH' >> $CONDA_PREFIX/etc/conda/deactivate.d/sleap_deactivate.sh
+```
+
+These commands only need to be run once and will subsequently run automatically upon [de]activating your `sleap` environment.
 ````
 
 ## Upgrading and uninstalling

docs/notebooks/Data_structures.ipynb

@@ -56,7 +56,7 @@
       "source": [
         "# This should take care of all the dependencies on colab:\n",
         "!pip uninstall -qqq -y opencv-python opencv-contrib-python\n",
-        "!pip install -qqq sleap==1.3.1111\n",
+        "!pip install -qqq \"sleap[pypi]>=1.3.3\"\n",
         "\n",
         "# But to do it locally, we'd recommend the conda package (available on Windows + Linux):\n",
         "# conda create -n sleap -c sleap -c conda-forge -c nvidia sleap"

docs/notebooks/Interactive_and_realtime_inference.ipynb

@@ -60,7 +60,7 @@
       "source": [
         "# This should take care of all the dependencies on colab:\n",
         "!pip uninstall -qqq -y opencv-python opencv-contrib-python\n",
-        "!pip install -qqq sleap==1.3.1\n",
+        "!pip install -qqq \"sleap[pypi]>=1.3.3\"\n",
         "\n",
         "\n",
         "# But to do it locally, we'd recommend the conda package (available on Windows + Linux):\n",

docs/notebooks/Interactive_and_resumable_training.ipynb

@@ -62,7 +62,7 @@
       "source": [
         "# This should take care of all the dependencies on colab:\n",
         "!pip uninstall -qqq -y opencv-python opencv-contrib-python\n",
-        "!pip install -qqq sleap==1.3.1\n",
+        "!pip install -qqq \"sleap[pypi]>=1.3.3\"\n",
         "\n",
         "\n",
         "# But to do it locally, we'd recommend the conda package (available on Windows + Linux):\n",

docs/notebooks/Model_evaluation.ipynb

@@ -40,7 +40,7 @@
       ],
       "source": [
         "!pip uninstall -qqq -y opencv-python opencv-contrib-python\n",
-        "!pip install -qqq sleap==1.3.1\n",
+        "!pip install -qqq \"sleap[pypi]>=1.3.3\"\n",
         "!apt -qq install tree\n",
         "!wget -q https://storage.googleapis.com/sleap-data/reference/flies13/td_fast.210505_012601.centered_instance.n%3D1800.zip\n",
         "!unzip -qq -o -d \"td_fast.210505_012601.centered_instance.n=1800\" \"td_fast.210505_012601.centered_instance.n=1800.zip\""

docs/notebooks/Post_inference_tracking.ipynb

@@ -61,7 +61,7 @@
       "source": [
         "# This should take care of all the dependencies on colab:\n",
         "!pip uninstall -qqq -y opencv-python opencv-contrib-python\n",
-        "!pip install -qqq sleap==1.3.1\n",
+        "!pip install -qqq \"sleap[pypi]>=1.3.3\"\n",
         "\n",
         "# But to do it locally, we'd recommend the conda package (available on Windows + Linux):\n",
         "# conda create -n sleap -c sleap -c conda-forge -c nvidia sleap"

docs/notebooks/Training_and_inference_on_an_example_dataset.ipynb

@@ -62,7 +62,7 @@
    ],
    "source": [
     "!pip uninstall -qqq -y opencv-python opencv-contrib-python\n",
-    "!pip install -qqq sleap==1.3.1"
+    "!pip install -qqq \"sleap[pypi]>=1.3.3\""
    ]
   },
   {

docs/notebooks/Training_and_inference_using_Google_Drive.ipynb

@@ -59,7 +59,7 @@
    ],
    "source": [
     "!pip uninstall -qqq -y opencv-python opencv-contrib-python\n",
-    "!pip install -qqq sleap==1.3.1"
+    "!pip install -qqq \"sleap[pypi]>=1.3.3\""
    ]
   },
   {

environment.yml

@@ -46,3 +46,4 @@ dependencies:
 
     - pip:  
         - "--editable=.[conda_dev]"
+

pypi_requirements.txt

@@ -12,24 +12,34 @@ jsonpickle==1.2
 networkx
 numpy>=1.19.5,<1.23.0
 opencv-python>=4.2.0,<=4.6.0
-# opencv-python-headless>=4.2.0.34,<=4.5.5.62
 pandas
 pillow>=8.3.1,<=8.4.0
 psutil
 pykalman==0.9.5
 PySide2>=5.13.2,<=5.14.1; platform_machine != 'arm64'
 PySide6; sys_platform == 'darwin' and platform_machine == 'arm64'
-python-rapidjson
+# Otherwise error: Microsoft Visual C++ 14.0 is required. 
+python-rapidjson <=1.10; sys_platform == 'win32'
+python-rapidjson; sys_platform != 'win32'
 pyyaml
 pyzmq
 qtpy>=2.0.1
 rich==10.16.1
-imageio<=2.15.0
 imgaug==0.4.0
 scipy>=1.4.1,<=1.9.0
 scikit-image
 scikit-learn ==1.0.*
 scikit-video
 seaborn
-tensorflow
-tensorflow-hub
+tensorflow>=2.6.3,<2.9; platform_machine != 'arm64'
+tensorflow-hub<=0.14.0
+# These dependencies are untested since we do not offer a wheel for apple silicon atm.
+tensorflow-macos==2.9.2; sys_platform == 'darwin' and platform_machine == 'arm64'
+tensorflow-metal==0.5.0; sys_platform == 'darwin' and platform_machine == 'arm64'
+
+# Dependencies of dependencies
+# google-auth 2.23.0 has requirement urllib3<2.0
+urllib3<2.0  # Not a 'noticed' runtime-dependency
+# tensorboard 2.11.2 has requirement protobuf<4,>=3.9.2
+# tensorflow 2.11.0 has requirement protobuf<3.20,>=3.9.2
+protobuf<3.20  # Makes GUI work in windows

sleap/gui/overlays/base.py

@@ -8,20 +8,22 @@
 so that current frame must be redrawn).
 """
 
-from qtpy import QtWidgets
-
-import attr
 import abc
-import numpy as np
+import logging
 from typing import Sequence, Union, Optional, List
 
+import attr
+import numpy as np
+from qtpy import QtWidgets
 from qtpy.QtWidgets import QGraphicsItem
 
 from sleap import Labels, Video
 from sleap.gui.widgets.video import QtVideoPlayer
 from sleap.nn.data.providers import VideoReader
 from sleap.nn.inference import VisualPredictor
 
+logger = logging.getLogger(__name__)
+
 
 @attr.s(auto_attribs=True)
 class BaseOverlay(abc.ABC):
@@ -64,7 +66,15 @@ def remove_from_scene(self):
         if self.items is None:
             return
         for item in self.items:
-            self.player.scene.removeItem(item)
+            try:
+                self.player.scene.removeItem(item)
+
+            except RuntimeError as e:  # Internal C++ object (PySide2.QtWidgets.QGraphicsPathItem) already deleted.
+                logger.debug(e)
+                pass
+
+        # Stop tracking the items after they been removed from the scene
+        self.items = []
 
     def redraw(self, video, frame_idx, *args, **kwargs):
         """Remove all items from the scene before adding new items to the scene.

sleap/version.py

@@ -12,7 +12,7 @@
 """
 
 
-__version__ = "1.3.2"
+__version__ = "1.3.3"
 
 
 def versions():