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# 🪐 Objaverse-XL Rendering Script
Scripts for rendering Objaverse-XL with [Blender](https://www.blender.org/). Rendering is the process of taking pictures of the 3D objects. These images can then be used for training AI models.
## 🖥️ Setup
1. Clone the repository and enter the rendering directory:
```bash
git clone https://github.com/allenai/objaverse-xl.git && \
cd objaverse-xl/scripts/rendering
```
2. Download Blender:
```bash
wget https://download.blender.org/release/Blender3.2/blender-3.2.2-linux-x64.tar.xz && \
tar -xf blender-3.2.2-linux-x64.tar.xz && \
rm blender-3.2.2-linux-x64.tar.xz
```
3. If you're on a headless Linux server, install Xorg and start it:
```bash
sudo apt-get install xserver-xorg -y && \
sudo python3 start_x_server.py start
```
4. Install the Python dependencies. Note that Python >3.8 is required:
```bash
cd ../.. && \
pip install -r requirements.txt && \
pip install -e . && \
cd scripts/rendering
```
## 📸 Example Usage
After setup, we can start to render objects using the `main.py` script:
```bash
python3 main.py
```
After running this, you should see 10 zip files located in `~/.objaverse/github/renders`, which correspond to renders of objects from [our example 3D objects repo](https://github.com/mattdeitke/objaverse-xl-test-files):
```bash
> ls ~/.objaverse/github/renders
0fde27a0-99f0-5029-8e20-be9b8ecabb59.zip 54f7478b-4983-5541-8cf7-1ab2e39a842e.zip 93499b75-3ee0-5069-8f4b-1bab60d2e6d6.zip
21dd4d7b-b203-5d00-b325-0c041f43524e.zip 5babbc61-d4e1-5b5c-9b47-44994bbf958e.zip ab30e24f-1046-5257-8806-2e346f4efebe.zip
415ca2d5-9d87-568c-a5ff-73048a084229.zip 5f6d2547-3661-54d5-9895-bebc342c753d.zip
44414a2a-e8f0-5a5f-bb58-6be50d8fd034.zip 8a170083-0529-547f-90ec-ebc32eafe594.zip
```
If we unzip one of the zip files:
```bash
> cd ~/.objaverse/github/renders
> unzip 0fde27a0-99f0-5029-8e20-be9b8ecabb59.zip
```
we will see that there is a new `0fde27a0-99f0-5029-8e20-be9b8ecabb59` directory. If we look in that directory, we'll find the following files:
```bash
> ls 0fde27a0-99f0-5029-8e20-be9b8ecabb59
000.npy 001.npy 002.npy 003.npy 004.npy 005.npy 006.npy 007.npy 008.npy 009.npy 010.npy 011.npy metadata.json
000.png 001.png 002.png 003.png 004.png 005.png 006.png 007.png 008.png 009.png 010.png 011.png
```
Here, we see that there are 12 renders `[000-011].png`. Each render will look something like one of the 4 images shown below, but likely with the camera at a different location as its location is randomized during rendering:
Additionally, there are 12 npy files `[000-011].npy`, which information about the cameras pose for a given render. We can read the npy files using:
```python
import numpy as np
array = np.load("000.npy")
```
where array is now a 3x4 [camera matrix](https://en.wikipedia.org/wiki/Camera_matrix) that looks something like:
```python
array([[6.07966840e-01, 7.93962419e-01, 3.18103019e-08, 2.10451518e-07],
[4.75670159e-01, -3.64238620e-01, 8.00667346e-01, -5.96046448e-08],
[6.35699809e-01, -4.86779213e-01, -5.99109232e-01, -1.66008198e+00]])
```
**Note.** USDZ support is experimental. Since Blender does not natively support usdz, we use [this Blender addon](https://github.com/robmcrosby/BlenderUSDZ), but it doesn't work with all types of USDZs. If you have a better solution, PRs are very much welcome 😄!
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