update cli refs in readme (#225)

Author: TeunHuijben

README.md

@@ -107,29 +107,29 @@ This approach consists of two steps: converting the tracking data into our speci
 For the first step, we assume your cell tracking data is saved as `tracks.csv` (or `tracks.parquet`, or [GEFF](https://live-image-tracking-tools.github.io/geff/main/#installation) file) in the format as described above (5-6 columns, with column names: `track_id, t, (z), y, x, (parent_track_id)]`), where `z` and `parent_track_id` are optional (no `z` column assumes 2D data, and no `parent_track_id` column assumes no cell divisions). This `tracks.csv` file can be converted to our Zarr format using the following command-line function (found in [/python/src/intracktive/convert.py](/python/src/intracktive/convert.py)):
 
 ```
-intracktive convert --input_file /path/to/tracks.csv
+intracktive convert /path/to/tracks.csv
 ```
 
 This function converts `tracks.csv` to `tracks_bundle.zarr` (if interested, see the [Zarr format](public/docs/file_format.md)). Change `/path/to/tracks.csv` into the actual path to your `tracks.csv`. By default, `tracks_bundle.zarr` is saved in the same directory as `tracks.csv`, unless `--out_dir` is specified as the extra parameter to the function call (see the [function itself](python/src/intracktive/convert.py#L717) for more details). The conversion script works for 2D and 3D datasets (when the column `z` is not present, a 2D dataset is assumed, i.e., all `z`-values will be set to 0)
 
 By default, all the cells are represented by equally-sized dots in `inTRACKtive`. The conversion script has the option of giving each cell a different size. For this: 1) make sure `tracks.csv` has an extra column named `radius`, and 2) use the flag `--add_radius` when calling the conversion script:
 
 ```
-intracktive convert --input_file path/to/tracks.csv --add_radius
+intracktive convert path/to/tracks.csv --add_radius
 ```
 
 Or use `intracktive convert --help` for the documentation on the inputs and outputs
 
 Additionally, inTRACKtive has the option of giving each cell a different color based on provided data attributes (see the example [Jupyter Notebook (`/napari/src/intracktive/examples`)](/python/src/intracktive/examples/notebook1_inTRACKtive_from_notebook.ipynb), and [videos](public/docs/videos.md)). One can add any attributes to the Zarr file, as long as they are present as columns in the `tracks.csv` tracking data. Using the following command-line interface, you can add one/multiple/all columns as attributes to the data:
 ```
 #add specific column as attribute
-intracktive convert --input_file path/to/file.csv --add_attribute cell_size
+intracktive convert path/to/file.csv --add_attribute cell_size
 
 #add multiple columns as attributes
-intracktive convert --input_file path/to/file.csv --add_attribute cell_size,time,diameter,color
+intracktive convert path/to/file.csv --add_attribute cell_size,time,diameter,color
 
 #add all columns as attributes
-intracktive convert --input_file path/to/tracks.csv --add_all_attributes
+intracktive convert path/to/tracks.csv --add_all_attributes
 ```
 When using `add_all_attributes`, the code will add all given columns as an attribute, apart from the default columns (`track_id`, `t`, `z`, `y`, `x`, and `parent_track_id`). If desired, one can manually add these columns as attributes using `add_attribute x`,  for example. The conversion script will detect whether each provided column represents a categorical or continuous attribute. This information is saved in the Zarr attributes information and loaded by inTRACKtive to use the appropriate colormap. 
 
@@ -139,23 +139,23 @@ In order for the viewer to access the data, the data must be hosted at a locatio
 intracktive serve path/to/data
 ```
 
-where `path/to/data` is the full path to the folder containing your data (e.g., `tracks_bundle.zarr`). Note that the path should **not** include the Zarr filename, so if the `tracks_bundle.zarr` is located in your Downloads folder, use `intracktive server ~/Downloads`. The tool will create a `localhost` with a name similar to `http://127.0.0.1:8000/`. 
+where `path/to/data` is the full path to the folder containing your data (e.g., `tracks_bundle.zarr`). Note that the path should **not** include the Zarr filename, so if the `tracks_bundle.zarr` is located in your Downloads folder, use `intracktive serve ~/Downloads`. The tool will create a `localhost` with a name similar to `http://127.0.0.1:8000/`. 
 
 Open this link in the browser, navigate to the exact dataset, right-click on the dataset (`tracks-bundle.zarr`) and `copy link` (depending on the browser). Then, open [the `inTRACKtive` viewer](https://intracktive.sf.czbiohub.org/), paste the copied link into the viewer (use the :globe_with_meridians: icon in the lower-left corner), and visualize your own data!
 
-Alternatively, you can use use a single command to serve and view the Zarr bundle with inTRACKtive: 
+Alternatively, you can use use a single command to serve and view the Zarr bundle with inTRACKtive:
 
 ```
-intracktive open path/to/.zarr
+intracktive open path/to/tracks_bundle.zarr
 
-intracktive open path/to/.csv
+intracktive open path/to/tracks.csv
 
-intracktive open path/to/.parquet
+intracktive open path/to/tracks.parquet
 
-intracktive open path/to/.geff
+intracktive open path/to/tracks.geff
 ```
 
-where `path/to/zarr` is the full path to the Zarr bundle, including the Zarr filename (example: `~/Downloads/tracks_bundle.zarr`). This command will spin up a local host at the location of the Zarr bundle, and open a browser tab with `inTRACKtive` running with this dataset. If you `intracktive open` an csv/parquet/GEFF file, the command will first convert the input to our Zarr format and open that file. 
+where the path is the full path to the file, including the filename (example: `~/Downloads/tracks_bundle.zarr`). This command will spin up a local host at the location of the Zarr bundle, and open a browser tab with `inTRACKtive` running with this dataset. If you `intracktive open` a CSV/Parquet/GEFF file, the command will first convert the input to our Zarr format and open that file. 
 
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