Merge branch 'master' into dev

Author: constantinpape

doc/annotation_tools.md

@@ -19,11 +19,18 @@ The annotation tools can be started from the napari plugin menu:
 
 You can find additional information on the annotation tools [in the FAQ section](#usage-question).
 
+HINT: If you would like to start napari to use `micro-sam` from the plugin menu, you must start it by activating the environment where `micro-sam` has been installed using:
+
+```bash
+$ mamba activate <ENVIRONMENT_NAME>
+$ napari
+```
+
 
 ## Annotator 2D
 
 The 2d annotator can be started by
-- clicking `Annotator 2d` in the plugin menu.
+- clicking `Annotator 2d` in the plugin menu after starting `napari`.
 - running `$ micro_sam.annotator_2d` in the command line.
 - calling `micro_sam.sam_annotator.annotator_2d` in a python script. Check out [examples/annotator_2d.py](https://github.com/computational-cell-analytics/micro-sam/blob/master/examples/annotator_2d.py) for details.
 
@@ -55,7 +62,7 @@ Check out [the video tutorial](https://youtu.be/9xjJBg_Bfuc) for an in-depth exp
 ## Annotator 3D
 
 The 3d annotator can be started by
-- clicking `Annotator 3d` in the plugin menu.
+- clicking `Annotator 3d` in the plugin menu after starting `napari`.
 - running `$ micro_sam.annotator_3d` in the command line.
 - calling `micro_sam.sam_annotator.annotator_3d` in a python script. Check out [examples/annotator_3d.py](https://github.com/computational-cell-analytics/micro-sam/blob/master/examples/annotator_3d.py) for details.
 
@@ -81,7 +88,7 @@ Check out [the video tutorial](https://youtu.be/nqpyNQSyu74) for an in-depth exp
 ## Annotator Tracking
 
 The tracking annotator can be started by
-- clicking `Annotator Tracking` in the plugin menu.
+- clicking `Annotator Tracking` in the plugin menu after starting `napari`.
 - running `$ micro_sam.annotator_tracking` in the command line.
 - calling `micro_sam.sam_annotator.annotator_tracking` in a python script. Check out [examples/annotator_tracking.py](https://github.com/computational-cell-analytics/micro-sam/blob/master/examples/annotator_tracking.py) for details. 
 
@@ -107,7 +114,7 @@ Check out [the video tutorial](https://youtu.be/1gg8OPHqOyc) for an in-depth exp
 ## Image Series Annotator
 
 The image series annotation tool enables running the [2d annotator](#annotator-2d) or [3d annotator](#annotator-3d) for multiple images that are saved in a folder. This makes it convenient to annotate many images without having to restart the tool for every image. It can be started by
-- clicking `Image Series Annotator` in the plugin menu.
+- clicking `Image Series Annotator` in the plugin menu after starting `napari`.
 - running `$ micro_sam.image_series_annotator` in the command line.
 - calling `micro_sam.sam_annotator.image_series_annotator` in a python script. Check out [examples/image_series_annotator.py](https://github.com/computational-cell-analytics/micro-sam/blob/master/examples/image_series_annotator.py) for details. 
 
@@ -126,7 +133,7 @@ Check out [the video tutorial](https://youtu.be/HqRoImdTX3c) for an in-depth exp
 
 ## Finetuning UI
 
-We also provide a graphical inferface for fine-tuning models on your own data. It can be started by clicking `Finetuning` in the plugin menu.
+We also provide a graphical inferface for fine-tuning models on your own data. It can be started by clicking `Finetuning` in the plugin menu after starting `napari`.
 
 **Note:** if you know a bit of python programming we recommend to use a script for model finetuning instead. This will give you more options to configure the training. See [these instructions](#training-your-own-model) for details.
 

doc/faq.md

@@ -146,13 +146,13 @@ NOTE: It is important to choose the correct model type when you opt for the abov
 
 ### 1. I have a microscopy dataset I would like to fine-tune Segment Anything for. Is it possible using `micro_sam`?
 Yes, you can fine-tune Segment Anything on your own dataset. Here's how you can do it:
-- Check out the [tutorial notebook](https://github.com/computational-cell-analytics/micro-sam/blob/master/notebooks/micro-sam-finetuning.ipynb) on how to fine-tune Segment Anything with our `micro_sam.training` library.
+- Check out the [tutorial notebook](https://github.com/computational-cell-analytics/micro-sam/blob/master/notebooks/sam_finetuning.ipynb) on how to fine-tune Segment Anything with our `micro_sam.training` library.
 - Or check the [examples](https://github.com/computational-cell-analytics/micro-sam/tree/master/examples/finetuning) for additional scripts that demonstrate finetuning.
 - If you are not familiar with coding in python at all then you can also use the [graphical interface for finetuning](finetuning-ui). But we recommend using a script for more flexibility and reproducibility.
 
 
 ### 2. I would like to fine-tune Segment Anything on open-source cloud services (e.g. Kaggle Notebooks), is it possible?
-Yes, you can fine-tune Segment Anything on your custom datasets on Kaggle (and [BAND](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html#using-micro_sam-on-band)). Check out our [tutorial notebook](https://github.com/computational-cell-analytics/micro-sam/blob/master/notebooks/micro-sam-finetuning.ipynb) for this.
+Yes, you can fine-tune Segment Anything on your custom datasets on Kaggle (and [BAND](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html#using-micro_sam-on-band)). Check out our [tutorial notebook](https://github.com/computational-cell-analytics/micro-sam/blob/master/notebooks/sam_finetuning.ipynb) for this.
 
 
 <!---

doc/installation.md

@@ -22,13 +22,23 @@ You can follow the instructions [here](https://mamba.readthedocs.io/en/latest/in
 $ mamba install -c pytorch -c conda-forge micro_sam
 ```
 or you can create a new environment (here called `micro-sam`) via:
+
 ```bash
 $ mamba create -c pytorch -c conda-forge -n micro-sam micro_sam
 ```
+
 if you want to use the GPU you need to install PyTorch from the `pytorch` channel instead of `conda-forge`. For example:
+
 ```bash
 $ mamba create -c pytorch -c nvidia -c conda-forge -n micro-sam micro_sam pytorch pytorch-cuda=12.1
 ```
+
+NOTE: If you create a new enviroment (eg. here called `micro-sam`), you must activate the environment using
+
+```bash
+$ mamba activate micro-sam
+```
+
 You may need to change this command to install the correct CUDA version for your system, see [https://pytorch.org/](https://pytorch.org/) for details.
 
 

doc/start_page.md

@@ -22,12 +22,17 @@ If you run into any problems or have questions please [open an issue](https://gi
 ## Quickstart
 
 You can install `micro_sam` via mamba:
-```
+```bash
 $ mamba install -c conda-forge micro_sam
 ```
 We also provide installers for Windows and Linux. For more details on the available installation options, check out [the installation section](#installation).
 
-After installing `micro_sam` you can start napari and select the annotation tool you want to use from `Plugins -> SegmentAnything for Microscopy`. Check out the [quickstart tutorial video](https://youtu.be/gcv0fa84mCc) for a short introduction and [the annotation tool section](#annotation-tools) for details.
+After installing `micro_sam`, you can start napari from within your environment using
+
+```bash
+$ napari
+```
+After starting napari, you can select the annotation tool you want to use from `Plugins -> SegmentAnything for Microscopy`. Check out the [quickstart tutorial video](https://youtu.be/gcv0fa84mCc) for a short introduction and [the annotation tool section](#annotation-tools) for details.
 
 The `micro_sam` python library can be imported via