mirror of
https://github.com/nerfstudio-project/nerfstudio.git
synced 2026-11-11 02:24:38 +08:00
Ethan Weber
GitHub
parent
03b7c44880
commit
020662d4e4
@ -6,7 +6,7 @@
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"tags": []
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},
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"source": [
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"# Creating Custom Pipelines\n",
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"# Creating Custom Methods\n",
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"\n",
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"> Our goal is to enable nerfstudio users to implement an entire NeRF method by only editing one file.\n",
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"\n",
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@ -254,8 +254,6 @@
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"tags": []
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},
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"source": [
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"# Creating pipelines from a config\n",
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"\n",
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"Now we show how to create a pipeline from a config, which has the following form:\n",
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"\n",
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"```python\n",
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@ -345,10 +343,10 @@
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},
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"vscode": {
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"interpreter": {
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||||
"hash": "100252972d4ee5286ab455ef1c778abde05b4affca9d1be78633d3797abf7e8c"
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"hash": "b7b86c17c0dfd6b313529972d424f2e075cc198a46cda005757126afe8133c7b"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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}
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34
docs/tutorials/pipelines/datamanagers.ipynb
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34
docs/tutorials/pipelines/datamanagers.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# DataManagers\n",
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"\n",
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"```{image} imgs/datamanagers.png\n",
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":align: center\n",
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"```"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.8.13 ('nerfactory')",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"name": "python",
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"version": "3.8.13"
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},
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"orig_nbformat": 4,
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"vscode": {
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||||
"interpreter": {
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||||
"hash": "b7b86c17c0dfd6b313529972d424f2e075cc198a46cda005757126afe8133c7b"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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158
docs/tutorials/pipelines/dataparsers.ipynb
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158
docs/tutorials/pipelines/dataparsers.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# DataParsers\n",
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"\n",
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"```{image} imgs/dataparsers.png\n",
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":align: center\n",
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"```\n",
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"\n",
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"## What is a DataParser?\n",
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"\n",
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"The dataparser returns `DataparserOutputs`, which puts all the various datasets into a common format.\n",
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"\n",
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"```python\n",
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"@dataclass\n",
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"class DataparserOutputs:\n",
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" \"\"\"Dataset inputs for the image dataset and the ray generator.\"\"\"\n",
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"\n",
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" image_filenames: List[Path]\n",
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" \"\"\"Filenames for the images.\"\"\"\n",
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" cameras: Cameras\n",
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" \"\"\"Camera object storing collection of camera information in dataset\"\"\"\n",
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" alpha_color: Optional[TensorType[3]] = None\n",
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" \"\"\"color of dataset background\"\"\"\n",
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" scene_box: SceneBox = SceneBox()\n",
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" \"\"\"scene box of dataset. Could be used to bound the scene, or to provide the scene scale depending on model.\"\"\"\n",
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" ...\n",
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"\n",
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"@dataclass\n",
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"class DataParser:\n",
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"\n",
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" @abstractmethod\n",
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" def _generate_dataset_inputs(self, split: str = \"train\") -> DataparserOutputs:\n",
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" \"\"\"Abstract method that returns the dataparser outputs for the given split.\n",
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"\n",
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" Args:\n",
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" split: Which dataset split to generate data for (train/eval/test).\n",
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"\n",
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" Returns:\n",
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" DataparserOutputs for the specified dataset and split.\n",
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" \"\"\"\n",
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"```\n",
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"\n",
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"## Example\n",
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"\n",
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"Here is an example where we implement a DataParser for our Nerfstudio data format.\n",
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"\n",
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"```python\n",
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"@dataclass\n",
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"class NerfstudioDataParserConfig(DataParserConfig):\n",
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" \"\"\"Nerfstudio dataset config\"\"\"\n",
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"\n",
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" _target: Type = field(default_factory=lambda: Nerfstudio)\n",
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" \"\"\"Target class to instantiate.\"\"\"\n",
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" data_directory: Path = Path(\"data/nerfstudio/poster\")\n",
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" \"\"\"Directory specifying location of data.\"\"\"\n",
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" scale_factor: float = 1.0\n",
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" \"\"\"How much to scale the camera origins by.\"\"\"\n",
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" downscale_factor: int = 1\n",
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" \"\"\"How much to downscale images.\"\"\"\n",
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" scene_scale: float = 1.0\n",
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" \"\"\"How much to scale the region of interest by.\"\"\"\n",
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" orientation_method: Literal[\"pca\", \"up\"] = \"up\"\n",
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" \"\"\"The method to use for orientation.\"\"\"\n",
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" train_split_percentage: float = 0.9\n",
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" \"\"\"The percent of images to use for training. The remaining images are for eval.\n",
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" \"\"\"\n",
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"\n",
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"@dataclass\n",
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"class Nerfstudio(DataParser):\n",
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" \"\"\"Nerfstudio Dataset\"\"\"\n",
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"\n",
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" config: NerfstudioDataParserConfig\n",
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"\n",
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" def _generate_dataset_inputs(self, split=\"train\") -> DataParserOutputs:\n",
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" \"\"\"Returns DataParserOutputs.\"\"\"\n",
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"```\n",
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"\n",
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"## Our Implementations\n",
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"\n",
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"###### Nerfstudio\n",
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"\n",
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"This is our custom dataparser.\n",
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"\n",
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"```{button-link} https://github.com/nerfstudio-project/nerfstudio/blob/master/nerfstudio/data/dataparsers/nerfstudio_dataparser.py\n",
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":color: primary\n",
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":outline:\n",
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"See the code!\n",
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"```\n",
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"\n",
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"###### Blender\n",
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"\n",
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"We support the synthetic Blender dataset from the original NeRF paper.\n",
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"\n",
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"```{button-link} https://github.com/nerfstudio-project/nerfstudio/blob/master/nerfstudio/data/dataparsers/blender_dataparser.py\n",
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":color: primary\n",
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":outline:\n",
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"See the code!\n",
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"```\n",
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"\n",
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"###### Instant NGP\n",
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"\n",
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"This supports the Instant NGP dataset.\n",
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"\n",
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"```{button-link} https://github.com/nerfstudio-project/nerfstudio/blob/master/nerfstudio/data/dataparsers/instant_ngp_dataparser.py\n",
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":color: primary\n",
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":outline:\n",
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"See the code!\n",
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"```\n",
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"\n",
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"###### MipNeRF 360\n",
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"\n",
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"```{button-link} https://github.com/nerfstudio-project/nerfstudio/blob/master/nerfstudio/data/dataparsers/mipnerf_dataparser.py\n",
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":color: primary\n",
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":outline:\n",
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"See the code!\n",
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"```\n",
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"\n",
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"###### Record3D\n",
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"\n",
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"This dataparser can use recorded data from a >= iPhone 12 Pro using the Record3D app. Record a video and export with the `EXR + JPG sequence` format. Unzip export and `rgb` folder before training.\n",
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"\n",
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"```{button-link} https://github.com/nerfstudio-project/nerfstudio/blob/master/nerfstudio/data/dataparsers/record3d_dataparser.py\n",
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":color: primary\n",
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":outline:\n",
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"See the code!\n",
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"```\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.8.13 ('nerfactory')",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"name": "python",
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"version": "3.8.13"
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},
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"orig_nbformat": 4,
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"vscode": {
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"interpreter": {
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"hash": "b7b86c17c0dfd6b313529972d424f2e075cc198a46cda005757126afe8133c7b"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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@ -1,10 +1,19 @@
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Creating Custom Pipelines
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Pipelines Overview
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-------------------------
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Here we show you how to create a custom pipeline.
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# TODO: show a figure of what a pipeline is here
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.. image:: imgs/pipelines_overview.png
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:width: 400
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:align: center
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.. toctree::
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:maxdepth: 1
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creating_pipelines.ipynb
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creating_models.ipynb
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dataparsers.ipynb
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datamanagers.ipynb
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models.ipynb
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pipelines.ipynb
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creating_new_methods.ipynb
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Developing Custom Models\n",
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"# Models\n",
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"\n",
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"```{image} imgs/models.png\n",
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":align: center\n",
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"```\n",
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"\n",
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"In this quick tour, we will walk you through the core of training and building any NeRFs with nerfstudio.\n",
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"\n",
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.8.12 ('nerfactory')",
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"display_name": "Python 3.8.13 ('nerfactory')",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.12"
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"version": "3.8.13"
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},
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"orig_nbformat": 4,
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"vscode": {
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"interpreter": {
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"hash": "34c28001ff35fb390494047002768a8182dcf55b1b11415165e62ea61557ab83"
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"hash": "b7b86c17c0dfd6b313529972d424f2e075cc198a46cda005757126afe8133c7b"
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}
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}
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},
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39
docs/tutorials/pipelines/pipelines.ipynb
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39
docs/tutorials/pipelines/pipelines.ipynb
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@ -0,0 +1,39 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Pipelines\n",
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"\n",
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"```{image} imgs/pipelines.png\n",
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":align: center\n",
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"```"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.8.13 ('nerfactory')",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"name": "python",
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"version": "3.8.13"
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},
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"orig_nbformat": 4,
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"vscode": {
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"interpreter": {
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"hash": "b7b86c17c0dfd6b313529972d424f2e075cc198a46cda005757126afe8133c7b"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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