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基于Paddle的Instant-NGP复现

本项目中有关nerf部分的代码参考至:https://github.com/kongdebug/nerf-paddle.git。

本项目有关instant-ngp的部分参考至其pytorch实现方式:https://github.com/yashbhalgat/HashNeRF-pytorch

数据集获取:https://aistudio.baidu.com/datasetdetail/136989

其中数据集和模型的实现,均进行了一定程度的重写,以个人认为比较好理解和好阅读的方式进行了改写,其中本项目并没有针对精度和速度方面进行复现,但大体思路上的实现没有太大问题。

代码结构

  • 在configs中保存了相关模型和数据集的参数细节,而在utils中的config_parse中进行参数的读取。
  • 在dataset中存放了数据集读取的实现细节,本项目仅对nerf中lego数据集进行了复现,如果需要使用其他数据集,可以参考其中的实现。
  • losses中存放nerf使用的mse损失以及hashnerf中提出的variation损失
  • metrics中则存放有关psnr的计算实现
  • model中存放nerf和hashnerf的实现细节,以及模型后处理部分的实现

训练代码

Installation

Step 0. Install Paddle。按照Paddle官网要求安装paddle:https://www.paddlepaddle.org.cn/

Step 1. Install requirements.

Prepare Dataset

Step 0. 从提供的网站中下载示例lego数据集:https://aistudio.baidu.com/datasetdetail/136989

Step 1. 创建data文件夹,将解压后的数据集放入data中,按需修改config文件路径

Tutorials

Train.

python train.py --config configs/nerf_lego.yml

Test.

python test.py --config configs/nerf_lego.yml --save_dir save --load_from save/040000.pdparams

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