More renaming (#590)

README.md

@@ -60,13 +60,11 @@ We hope nerfstudio enables you to build faster :hammer: learn together :books: a
 The quickstart will help you get started with the default vanilla nerf trained on the classic blender lego scene.
 For more complex changes (e.g. running with your own data/ setting up a new NeRF graph, please refer to our [references](#learn-more).
 
-#### 1. Installation: Setup the environment
+## 1. Installation: Setup the environment
 
-This repository is tested with CUDA 11.3. Make sure to install [Conda](https://docs.conda.io/en/latest/miniconda.html#linux-installers) before preceding.
+### Create environment
 
-</details>
-
-Create the python environment
+We reccomend using conda to manage dependencies. Make sure to install [Conda](https://docs.conda.io/en/latest/miniconda.html) before preceding.
 
 ```
 conda create --name nerfstudio python=3.8.13
@@ -74,36 +72,46 @@ conda activate nerfstudio
 python -m pip install --upgrade pip
 ```
 
-Clone the repo
+### Dependencies
 
-```
-git clone git@github.com:plenoptix/nerfstudio.git
-```
-
-Install dependencies and nerfstudio as a library
-
-```
-cd nerfstudio
-pip install -e .
-```
-
-Install tiny-cuda-nn (tcnn) to run instant_ngp
+Install pytorch with CUDA (this repo has been tested with CUDA 11.3) and [tiny-cuda-nn](https://github.com/NVlabs/tiny-cuda-nn)
 
 ```
 pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 -f https://download.pytorch.org/whl/torch_stable.html
 pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch
 ```
 
-Install tab completion for nerfstudio (bash & zsh)
+### Installing nerfstudio
+
+Easy option:
 
 ```
-nf-install-cli
+pip install nerfstudio
 ```
 
-Run the test cases
+If you would want the latest and greatest:
 
 ```
-pytest tests
+git clone git@github.com:plenoptix/nerfstudio.git
+cd nerfstudio
+pip install -e .
+```
+
+### Optional Installs
+
+**Tab completion (bash & zsh)**
+
+This needs to be rerun when the CLI changes, for example if nerfstudio is updated.
+
+```bash
+ns-install-cli
+```
+
+**Development packages**
+
+```bash
+pip install -e.[dev]
+pip install -e.[docs]
 ```
 
 #### 2. Getting the data
@@ -111,7 +119,7 @@ pytest tests
 Download the original NeRF Blender dataset. We support the major datasets and allow users to create their own dataset, described in detail [here](https://plenoptix-nerfstudio.readthedocs-hosted.com/en/latest/tutorials/data/index.html).
 
 ```
-python scripts/downloads/download_data.py --dataset=blender
+ns-download-data --dataset=blender
 ```
 
 Use `--help` to view all currently available datasets. The resulting script should download and unpack the dataset as follows:
@@ -128,40 +136,34 @@ Use `--help` to view all currently available datasets. The resulting script shou
          ...
 ```
 
-#### 3. Training a model
+## 3. Training a model
 
 To run with all the defaults, e.g. vanilla nerf method with the blender lego image
 
 ```
 # To see what models are available.
-python scripts/train.py --help
+ns-train --help
 
 # Run a vanilla nerf model.
-python scripts/train.py vanilla_nerf
+ns-train vanilla-nerf
 
-# Run a faster version with instant ngp using tcnn (without the viewer).
-python scripts/train.py instant_ngp
+#
+ns-train nerfacto
 ```
 
-#### 3.x Training a model with the viewer
+### 3.x Training a model with the viewer
 
 Make sure to forward a port for the websocket to localhost. The default port is 7007, which you should be expose to localhost:7007.
 
 ```bash
 # with the default port
-python scripts/train.py instant_ngp --viewer.enable
+ns-train nerfacto --vis viewer
 
 # with a specified websocket port
-python scripts/train.py instant_ngp --viewer.enable --viewer.websocket-port=7008
-
-# with the viewer bridge server as a separate process
-# in one terminal, start the bridge server:
-viewer-bridge-server # or equivalently, python scripts/run_viewer_bridge_server.py
-# in another terminal, start training:
-python scripts/train.py instant_ngp --viewer.enable --viewer.no-launch-bridge-server
+ns-train nerfacto --vis viewer --viewer.websocket-port=7008
 ```
 
-#### 4. Visualizing training runs
+### 4. Visualizing training runs
 
 We support multiple methods to visualize training, the default configuration uses Tensorboard. More information on logging can be found [here](https://plenoptix-nerfactory.readthedocs-hosted.com/en/latest/tooling/logging_profiling.html).
 
@@ -170,7 +172,7 @@ We support multiple methods to visualize training, the default configuration use
 
 We have developed our own Real-time web viewer, more information can be found [here](https://plenoptix-nerfactory.readthedocs-hosted.com/en/latest/tutorials/viewer/index.html). This viewer runs during training and is designed to work with models that have fast rendering pipelines.
 
-To turn on the viewer, simply add the flag `--viewer.enable`.
+To turn on the viewer, simply add the flag `--vis viewer`.
 
 </details>
 
@@ -192,13 +194,13 @@ We support logging to weights and biases. To enable wandb logging, add the flag
 
 </details>
 
-#### 5. Rendering a trajectories during inference
+## 5. Rendering a trajectories during inference
 
 ```
-python scripts/eval.py render-trajectory --load-config=outputs/blender_lego/instant_ngp/2022-07-07_230905/config.yml--traj=spiral --output-path=output.mp4
+ns-eval render-trajectory --load-config=outputs/blender_lego/instant_ngp/2022-07-07_230905/config.yml--traj=spiral --output-path=output.mp4
 ```
 
-#### 6. In-depth guide
+## 6. In-depth guide
 
 For a more in-depth tutorial on how to modify/implement your own NeRF Graph, please see our [walk-through](https://plenoptix-nerfactory.readthedocs-hosted.com/en/latest/tutorials/pipelines/index.html).