Merge pull request #3 from Crackodu91/main

Huge mistakes

Author: guillaumelegoc

docs/guide-pipeline.md

@@ -17,7 +17,7 @@ Three main scripts and function are used within the pipeline :
     - add atlas coordinates to detections
     - add hemisphere to detections' parents
     - add regions measurements 
-        * count for punctal objects
+        * count for punctual objects
         * cumulated length for lines objects
     - export detections measurements
         * as CSV for punctual objects
@@ -103,4 +103,4 @@ cuisto.display.plot_2D_distributions(df_coordinates, cfg)
 ```
 
 !!! tip
-    You can see a live example in [this demo notebook](demo_notebooks/fibers_length_multi.ipynb).
+    You can see a live example in [this demo notebook](demo_notebooks/fibers_length_multi.ipynb).

docs/guide-prepare-qupath.md

@@ -1,6 +1,6 @@
 # Prepare QuPath data
 
-`cuisto` uses some QuPath classifications concepts, make sure to be familiar with them with the [official documentation](https://qupath.readthedocs.io/en/stable/docs/concepts/classifications.html#classifications-derived-classifications). Notably, we use the concept of primary classification and derived classification : an object classfied as `First: second` is of classification `First` and of derived classification `second`.
+`cuisto` uses some QuPath classifications concepts, make sure to be familiar with them with the [official documentation](https://qupath.readthedocs.io/en/stable/docs/concepts/classifications.html#classifications-derived-classifications). Notably, we use the concept of primary classification and derived classification : an object classified as `First: second` is of classification `First` and of derived classification `second`.
 
 ## QuPath requirements
 `cuisto` assumes a specific way of storing regions and objects information in the TSV files exported from QuPath. Note that only one primary classification is supported, but you can have any number of derived classifications.
@@ -40,7 +40,7 @@ While you're free to add any measurements as long as they follow [the requiremen
 
 It is then up to you to select which metrics among those to compute and display and name them, via the [configuration file](main-configuration-files.md#configtoml).
 
-For punctal detections (eg. objects whose only the centroid is considered), only the atlas coordinates are used, to compute and display spatial distributions of objects across the brain (using their classifications to give each distributions different hues).  
+For punctual detections (eg. objects whose only the centroid is considered), only the atlas coordinates are used, to compute and display spatial distributions of objects across the brain (using their classifications to give each distributions different hues).  
 For fibers-like objects, it requires to export the lines detections atlas coordinates as JSON files, with the `exportFibersAtlasCoordinates.groovy` script (this is done automatically when using the [pipeline](guide-pipeline.md)).
 
 ### Adding measurements
@@ -63,7 +63,7 @@ Once you imported atlas regions registered with ABBA, detected objects in your i
 + Head to `Measure > Export measurements`
 + Select relevant images
 + Choose the `Output file` (specify in the file name if it is a detections or annotations file)
-+ Chose either `Detections` or `Annoations` in `Export type`
++ Choose either `Detections` or `Annoations` in `Export type`
 + Click `Export`
 
 Do this for both Detections and Annotations, you can then use those files with `cuisto` (see the [Examples](main-using-notebooks.md)).