nerf三维重建算法代码

NERF（Neural Radiance Fields）是一种基于神经网络的三维重建算法，可以从多个二维图像中恢复出一个高质量的三维场景。以下是一个简单的 PyTorch 实现，只包含核心代码：

import torch
import torch.nn as nn
import torch.nn.functional as F

class NeRF(nn.Module):
    def __init__(self, in_features, hidden_features, out_features):
        super(NeRF, self).__init__()
        
        self.fc1 = nn.Linear(in_features, hidden_features)
        self.fc2 = nn.Linear(hidden_features, hidden_features)
        self.fc3 = nn.Linear(hidden_features, out_features)
        
    def forward(self, x):
        x = F.relu(self.fc1(x))
        x = F.relu(self.fc2(x))
        x = self.fc3(x)
        return x

class NeRFRenderer(nn.Module):
    def __init__(self, net, near, far, num_samples):
        super(NeRFRenderer, self).__init__()
        
        self.net = net
        self.near = near
        self.far = far
        self.num_samples = num_samples
        
    def forward(self, ray_origins, ray_directions):
        t_vals = torch.linspace(self.near, self.far, self.num_samples, device=ray_origins.device)
        sample_points = ray_origins[...,None,:] + ray_directions[...,None,:] * t_vals[None,None,:,None]
        
        rgb = 0.0
        alpha = 0.0
        for i in range(self.num_samples):
            rgb_alpha = self.net(sample_points[...,i,:])
            rgb += (1 - alpha) * rgb_alpha[...,0:3] * rgb_alpha[...,3:6]
            alpha += (1 - alpha) * rgb_alpha[...,6]
            
        return rgb, alpha

这里定义了一个 `NeRF` 类，用于构建神经网络，以及一个 `NeRFRenderer` 类，用于实现渲染操作。在 `NeRFRenderer` 中，根据给定的相机位置和方向，通过对多个采样点进行神经网络计算，得到 RGB 颜色和透明度，最终生成渲染图像。