The camera created from an OpenCV camera pose does not project the vertices the same way as MeshRenderer:

import numpy as np
import matplotlib.pyplot as plt
import torch
from pytorch3d.structures import Meshes
from pytorch3d.renderer import MeshRenderer, MeshRasterizer, RasterizationSettings, SoftPhongShader
from pytorch3d.renderer import TexturesVertex
from pytorch3d.utils import cameras_from_opencv_projection

# Camera parameters
R = np.eye(3)
t = np.array([0, 0, 5])
f = 1731.2994092344502
w, h = 1280, 720
K = np.array([
    [f, 0, w/2],
    [0, f, h/2],
    [0, 0, 1],
])

# Mesh parameters
verts = np.array([
    [0.0, 0.0, 0.0],
    [0.5, 0.5, 0.0],
    [0.5, 0.0, 0.0],
])
faces = torch.tensor([[[0, 1, 2]]])

verts = torch.FloatTensor(verts).unsqueeze(0)
tex = TexturesVertex(torch.ones_like(verts))

# Create camera
camera = cameras_from_opencv_projection(
    torch.FloatTensor(R).unsqueeze(0),
    torch.FloatTensor(t).unsqueeze(0),
    torch.FloatTensor(K).unsqueeze(0),
    torch.Tensor([w, h]).unsqueeze(0),
)

# Create mesh and renderer
mesh = Meshes(verts, faces, tex)
renderer = MeshRenderer(
    rasterizer=MeshRasterizer(
        raster_settings=RasterizationSettings(image_size=(h, w)),
        cameras=camera,
    ),
    shader=SoftPhongShader(cameras=camera),
)

# Render image
mesh_img = renderer(mesh)
mesh_img = mesh_img.squeeze().cpu().numpy()

# Project vertices
points = camera.transform_points_screen(mesh.verts_packed())
points = points.squeeze().cpu().numpy()[:, :2]

# Plot
plt.figure(figsize=(10, 5))
plt.imshow(mesh_img)

for pt in points:
    plt.scatter(pt[0], pt[1], color='red', s=50)

plt.show()

That code produces the following image:

I was expecting the vertices projected by PerspectiveCamera.transform_points_screen would align with the image rendered by MeshRenderer, but they clearly do not. The points generated by PerspectiveCamera.transform_points_screen match my expectations, but why does the image created by MeshRenderer not line up?