Remove sam_ prefix from example scripts

Author: constantinpape

doc/annotation_tools.md

@@ -22,7 +22,7 @@ The `micro_sam` applications are mainly based on [the point layer](https://napar
 The 2d annotator can be started by
 - clicking `2d annotator` in the `micro_sam` GUI.
 - running `$ micro_sam.annotator_2d` in the command line. Run `micro_sam.annotator_2d -h` for details.
-- calling `micro_sam.sam_annotator.annotator_2d` in a python script. Check out [examples/sam_annotator_2d.py](https://github.com/computational-cell-analytics/micro-sam/blob/master/examples/sam_annotator_2d.py) for details. 
+- 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. 
 
 The user interface of the 2d annotator looks like this:
 
@@ -46,14 +46,14 @@ Note that point prompts and box prompts can be combined. When you're using point
 
 Check out [this video](https://youtu.be/DfWE_XRcqN8) for an example of how to use the interactive 2d annotator.
 
-We also provide the `image series annotator`, which can be used for running the 2d annotator for several images in a folder. You can start by clicking `Image series annotator` in the GUI, running `micro_sam.image_series_annotator` in the command line or from a [python script](https://github.com/computational-cell-analytics/micro-sam/blob/master/examples/sam_image_series_annotator.py).
+We also provide the `image series annotator`, which can be used for running the 2d annotator for several images in a folder. You can start by clicking `Image series annotator` in the GUI, running `micro_sam.image_series_annotator` in the command line or from a [python script](https://github.com/computational-cell-analytics/micro-sam/blob/master/examples/image_series_annotator.py).
 
 ## Annotator 3D
 
 The 3d annotator can be started by
 - clicking `3d annotator` in the `micro_sam` GUI.
 - running `$ micro_sam.annotator_3d` in the command line. Run `micro_sam.annotator_3d -h` for details.
-- calling `micro_sam.sam_annotator.annotator_3d` in a python script. Check out [examples/sam_annotator_3d.py](https://github.com/computational-cell-analytics/micro-sam/blob/master/examples/sam_annotator_3d.py) for details.
+- 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.
 
 The user interface of the 3d annotator looks like this:
 
@@ -76,7 +76,7 @@ Check out [this video](https://youtu.be/5Jo_CtIefTM) for an overview of the inte
 The tracking annotator can be started by
 - clicking `Tracking annotator` in the `micro_sam` GUI.
 - running `$ micro_sam.annotator_tracking` in the command line. Run `micro_sam.annotator_tracking -h` for details.
-- calling `micro_sam.sam_annotator.annotator_tracking` in a python script. Check out [examples/sam_annotator_tracking.py](https://github.com/computational-cell-analytics/micro-sam/blob/master/examples/sam_annotator_tracking.py) for details. 
+- 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. 
 
 The user interface of the tracking annotator looks like this:
 

doc/python_library.md

@@ -11,7 +11,7 @@ This functionality is used to implement the `micro_sam` annotation tools, but yo
 ## Finetuned models
 
 We provide fine-tuned Segment Anything models for microscopy data. They are still in an experimental stage and we will upload more and better models soon, as well as the code for fine-tuning.
-For using the current models, check out the [2d annotator example](https://github.com/computational-cell-analytics/micro-sam/blob/master/examples/sam_annotator_2d.py#L62) and set `use_finetuned_model` to `True`.
+For using the current models, check out the [2d annotator example](https://github.com/computational-cell-analytics/micro-sam/blob/master/examples/annotator_2d.py#L62) and set `use_finetuned_model` to `True`.
 See the difference between the normal and fine-tuned Segment Anything ViT-h model on an image from [LiveCELL](https://sartorius-research.github.io/LIVECell/):
 
 <img src="https://raw.githubusercontent.com/computational-cell-analytics/micro-sam/master/doc/images/vanilla-v-finetuned.png" width="768">

examples/README.md

@@ -1,10 +1,10 @@
 # micro_sam examples
 
 Examples for using the micro_sam annotation tools:
-- `sam_annotator_2d.py`: run the interactive 2d annotation tool
-- `sam_annotator_3d.py`: run the interactive 3d annotation tool
-- `sam_annotator_tracking.py`: run the interactive tracking annotation tool
-- `sam_image_series_annotator.py`: run the annotation tool for a series of images
+- `annotator_2d.py`: run the interactive 2d annotation tool
+- `annotator_3d.py`: run the interactive 3d annotation tool
+- `annotator_tracking.py`: run the interactive tracking annotation tool
+- `image_series_annotator.py`: run the annotation tool for a series of images
 
 The folder `use_as_library` contains example scripts that show how `micro_sam` can be used as a python
 library to apply Segment Anything on mult-dimensional data.

examples/sam_annotator_2d.py examples/annotator_2d.pyexamples/sam_annotator_2d.py renamed to examples/annotator_2d.py

@@ -6,7 +6,7 @@
 
 def cell_segmentation():
     """Run the instance segmentation functionality from micro_sam for segmentation of
-    HeLA cells. You need to run examples/sam_annotator_2d.py:hela_2d_annotator once before
+    HeLA cells. You need to run examples/annotator_2d.py:hela_2d_annotator once before
     running this script so that all required data is downloaded and pre-computed.
     """
     image_path = "../data/hela-2d-image.png"
@@ -66,7 +66,7 @@ def cell_segmentation():
 
 def segmentation_with_tiling():
     """Run the instance segmentation functionality from micro_sam for segmentation of
-    cells in a large image. You need to run examples/sam_annotator_2d.py:wholeslide_annotator once before
+    cells in a large image. You need to run examples/annotator_2d.py:wholeslide_annotator once before
     running this script so that all required data is downloaded and pre-computed.
     """
     image_path = "../data/whole-slide-example-image.tif"