docs: fix grammer

docs/tutorials/cli.md

@@ -76,15 +76,15 @@ t4viz pointcloud <DATA_ROOT> [OPTIONS]
 
 `scene` and `instance` commands support visualizing future trajectories for each object.
 
-By specifying `-f --future` option, you can render them in the particular time length:
+By specifying `-f [--future]` option, you can render them in the particular time length:
 
 ```shell
 t4viz <COMMAND> ... -f <FUTURE_LENGTH[s]>
 ```
 
 #### Save Recording as `.rrd`
 
-You can save visualized recording with `-o --output` option as follows:
+You can save visualized recording with `-o [--output]` option as follows:
 
 ```shell
 t4viz <COMMAND> ... -o <OUTPUT_DIR>

docs/tutorials/customize.md

@@ -34,10 +34,10 @@ Attribute(token='f40e605870aa29b1473ca6e65255c45e', name='foo', description='thi
 
 You can customize schema classes on your own code, if you need for some reasons.
 
-For example, you might meet the error because some mandatory field but you are OK whatever the actual value is.
+For example, you might meet the error because of missing some mandatory fields but it is OK whatever the actual value is.
 
 In here, let's define a custom `Attribute` class, called `CustomAttribute`, in your workspace.
-This class allows it is OK even `description` field is not recorded in `attribute.json`.
+This class suppresses runtime exception caused by missing `description` in `attribute.json`.
 
 Now you have the following workspace structure:
 
@@ -50,7 +50,7 @@ my_package
 └── pyproject.toml
 ```
 
-By editing `custom_schema.py`, you can overwrite `Attribute` as follows:
+By editing `custom_schema.py`, you can define `CustomAttribute` overwriting `Attribute` as follows:
 
 ```python title="custom_schema.py"
 from __future__ import annotations

docs/tutorials/initialize.md

@@ -70,7 +70,7 @@ Done loading in 0.061 seconds.
 >>> my_sample = t4.get("sample", first_sample_token)
 ```
 
-You can access to the `sample_data` associated with this `sample`.
+You can access the `sample_data` associated with this `sample`.
 `sample.data` returns a `dict` object consists of `{str: <SAMPLE_DATA_TOKEN (str)>}`.
 
 ```python
@@ -90,7 +90,7 @@ You can access to the `sample_data` associated with this `sample`.
 
 `sample_annotation` refers to any 3D bounding box in a corresponding `sample`.
 All location data is given with respect to the global coordinate system.
-You can access to the list of `sample_annotation` tokens with `sample.ann_3ds: list[str]`.
+You can access the list of `sample_annotation` tokens with `sample.ann_3ds: list[str]`.
 
 ```python
 >>> my_annotation_token = my_sample.ann_3ds[0]

docs/tutorials/render.md

@@ -54,11 +54,7 @@ You can save the rendering result as follows:
 >>> t4.render_scene(scene_token, save_dir=<DIR_TO_SAVE>)
 ```
 
-If you don't want to spawn the viewer, please specify `show=False` as below:
-
-```python
->>> t4.render_scene(scene_token, save_dir=<DIR_TO_SAVE>, show=False)
-```
+When you specify `save_dir`, viewer will not be spawned on your screen.
 
 ## Rendering with `RerunViewer`
 
@@ -75,7 +71,7 @@ For details, please refer to the API references.
 >>> viewer.render_box2ds(seconds, box2ds)
 ```
 
-It allows us to render boxes by specifying elements of boxes directly.
+It allows you to render boxes by specifying elements of boxes directly.
 
 ```python
 # Rendering 3D boxes