`#` ComfyUI RenderFormer Custom Nodes: Implementation Plan

This document outlines the plan for creating ComfyUI custom nodes to integrate the RenderFormer model.

## 1. Project Setup

- **Directory:** A new directory named `ComfyUI-PHRenderFormerWrapper` will be created to house all the necessary files for the custom node.
- **Core Files:**
    - `__init__.py`: This file will register the custom nodes with ComfyUI, making them available in the user interface.
    - `nodes.py`: This file will contain the Python code for all the custom nodes.
    - `requirements.txt`: This file will list all the Python dependencies required for the nodes to function correctly.

## 2. Dependencies

The `requirements.txt` file will include a merged list of dependencies from both the original RenderFormer model and the standard requirements for a ComfyUI custom node. This ensures a complete and functional environment. Key dependencies will include:

- `torch`
- `trimesh`
- `huggingface_hub`
- `simple-ocio`
- `dacite`
- `einops`
- `roma`
- `safetensors`
- `scipy`
- `pymeshlab`
- `h5py`
- `natsort`
- `imageio[ffmpeg]`
- `git+https://github.com/iamNCJ/renderformer-liger-kernel.git`

## 3. Node Implementation (`nodes.py`)

The integration will be achieved through a set of modular and user-friendly nodes that form a clear pipeline within ComfyUI.

### Node 1: `RenderFormerModelLoader`

- **Purpose:** To load the pre-trained RenderFormer model from Hugging Face.
- **Inputs:**
    - `model_id` (string): The identifier of the model on Hugging Face (e.g., `microsoft/renderformer-v1.1-swin-large`).
- **Logic:**
    - The node will call `RenderFormerRenderingPipeline.from_pretrained(model_id)` to download and initialize the model.
- **Output:**
    - `RENDERFORMER_PIPELINE`: A pipeline object that is ready for rendering.

### Node 2: `RenderFormerSceneBuilder`

- **Purpose:** To construct a 3D scene in the format that RenderFormer requires, directly from inputs within the ComfyUI. This node abstracts the manual process of creating JSON and HDF5 files.
- **Inputs:**
    - `trimesh`: A mesh object provided by another node (e.g., a mesh loader).
    - `camera_config`: A configuration object for the camera, including position, look-at point, and field of view (FOV).
    - `material_properties`: A configuration object for material properties like diffuse color, roughness, and emissive values.
- **Logic:**
    - This node will programmatically generate the necessary data tensors (`triangles`, `texture`, `vn`, `c2w`, `fov`) in memory, replicating the logic from `scene_processor/to_h5.py`.
- **Output:**
    - `RENDERFORMER_SCENE`: A scene object containing all the prepared data tensors required for rendering.

### Node 3: `RenderFormerGenerator`

- **Purpose:** The main node that executes the rendering process.
- **Inputs:**
    - `pipeline`: The `RENDERFORMER_PIPELINE` object from the model loader node.
    - `scene`: The `RENDERFORMER_SCENE` object from the scene builder node.
    - `resolution` (integer): The desired width and height of the output image.
    - `tone_mapper` (string, optional): The tone mapping algorithm to apply to the final image (e.g., 'agx', 'filmic').
- **Logic:**
    - The node will invoke the `pipeline.render()` method, passing in the scene data and rendering parameters, as demonstrated in the `infer.py` script.
- **Output:**
    - `IMAGE`: The final rendered image.

This plan ensures a robust, modular, and user-friendly integration of RenderFormer into ComfyUI.>`

create a detailed plan to integrate the RenderFormer Model from @/url_to_microsoft github_rep with a complete repository of custom nodes for @/url_to_ComfyUI , make sure to follow these steps:

- look at the requirements of the renderformer model and add them to the requirements of this repository
- look at @/renderformer/readme_file and make sure to follow the process to render an image for creating nodes
- create a set of nodes to load the model in comfyui and render a 3d scene