Mitsuba 3: Mesh Loading Discrepancies Explained

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Mitsuba 3: Understanding Mesh Loading Discrepancies Between `mi.load_dict` and `trimesh.load`

Hey guys! Ever wondered why your 3D meshes look different when loaded using different methods in Mitsuba 3? Specifically, why does a mesh loaded with mi.load_dict appear different from one loaded with trimesh.load? Let's dive into this interesting issue and figure out what's going on.

The Curious Case of the Diverging Meshes

Imagine you're working on a cool rendering project using Mitsuba 3, and you've got a mesh generated by some fancy generative model. You want to bring that mesh into Mitsuba 3 for rendering. Now, you've got two main ways to do this:

  1. Using mi.load_dict: This method involves loading the mesh from a file (like a .obj file) directly into Mitsuba 3.
  2. Using trimesh.load: This involves loading the mesh using the trimesh library and then feeding the mesh data (vertices, faces, normals, etc.) into Mitsuba 3.

Now, here's the catch: you might notice that the rendered results look different depending on which method you use! That's the puzzle we're going to solve today.

Why the Visual Discrepancy?

The core issue lies in how Mitsuba 3 interprets and processes the mesh data in each loading scenario. When you load a mesh using mi.load_dict, Mitsuba 3 handles the entire loading process, including parsing the file format, extracting the mesh data, and creating the necessary internal data structures. This method ensures that the mesh is correctly interpreted according to the file format specifications.

On the other hand, when you load a mesh using trimesh.load, you're essentially taking on the responsibility of extracting the mesh data and feeding it into Mitsuba 3. This process involves accessing the mesh attributes (vertices, faces, normals) from the trimesh object and then manually creating a Mitsuba 3 Mesh object. This manual process can introduce discrepancies if the data isn't formatted or interpreted correctly.

Digging into the Code: Spotting the Difference

Let's take a closer look at the code snippets provided and highlight the key differences:

Loading with mi.load_dict:

my_mesh_shading = {
    'type': 'obj',
    'filename': str(mesh_path),
    'bsdf': {
        'type': 'ref',
        'id': 'diffuse_white'
    },
    'id': 'scene'
}

scene_dict = {
    "type": "scene",
    "my_integrator": {
        "type": integrator,
        "max_depth": max_depth,
        "hide_emitters": True,
    },
    "my_sensor": my_sensor,
    "my_texture": diffuse_white,
    # "my_obj": mi_mesh,
    "my_obj": my_mesh_shading,
    "my_envmap": my_envmap,
}

scene = mi.load_dict(scene_dict)
image = mi.render(scene, spp=64)

In this method, you're simply telling Mitsuba 3 the file path of the mesh, and it takes care of the rest. It's like ordering a pizza – you just specify the toppings, and the chef handles the cooking.

Loading with trimesh.load:

mesh_trimesh = trimesh.load(mesh_path)

mi_mesh = mi.Mesh(
    "mi_mesh",
    vertex_count= vertex_count,
    face_count= face_count,
)

params = mi.traverse(mi_mesh)
for key in params.keys():
    if 'vertex_positions' in key.lower():
        params[key] = dr.cuda.Float(np.array(mesh_trimesh.vertices.ravel()))
    if 'faces' in key.lower():
        params[key] = dr.cuda.UInt32(np.array(mesh_trimesh.faces.ravel()))
    if 'vertex_normals' in key.lower():
        params[key] = dr.cuda.Float(np.array(mesh_trimesh.vertex_normals.ravel()))

params.update()

scene_dict = {
    "type": "scene",
    "my_integrator": {
        "type": integrator,
        "max_depth": max_depth,
        "hide_emitters": True,
    },
    "my_sensor": my_sensor,
    "my_texture": diffuse_white,
    "my_obj": mi_mesh,
    # "my_obj": my_mesh_shading,
    "my_envmap": my_envmap,
}

scene = load_dict(scene_dict)
image = mi.render(scene, spp=64)

Here, you're loading the mesh with trimesh, then manually creating a mi.Mesh object and feeding in the vertex, face, and normal data. This is like cooking the pizza yourself – you have more control, but you also need to make sure you're adding the ingredients in the right way.

The key part to pay attention to is this section:

params = mi.traverse(mi_mesh)
for key in params.keys():
    if 'vertex_positions' in key.lower():
        params[key] = dr.cuda.Float(np.array(mesh_trimesh.vertices.ravel()))
    if 'faces' in key.lower():
        params[key] = dr.cuda.UInt32(np.array(mesh_trimesh.faces.ravel()))
    if 'vertex_normals' in key.lower():
        params[key] = dr.cuda.Float(np.array(mesh_trimesh.vertex_normals.ravel()))

This is where the manual data transfer happens. The code iterates through the parameters of the mi.Mesh object and populates the vertex positions, faces, and normals with data from the trimesh object. Any mismatch in data types, ordering, or interpretation here can lead to rendering artifacts.

Different Attributes, Different Behavior

Another crucial point mentioned in the original post is that the mi.Mesh object has different attributes depending on the loading method. Specifically, the vertex_positions_buffer() and face_indices_buffer() attributes might behave differently.

When you load a mesh using mi.load_dict, Mitsuba 3 creates these buffers internally and manages them automatically. However, when you create the mi.Mesh object manually, you're responsible for ensuring that these buffers are correctly initialized and populated. If there's a mismatch in the buffer format or data layout, it can lead to unexpected rendering results.

Finding the Fix: How to Load Meshes Correctly with Trimesh

So, how do we fix this and ensure that meshes loaded with trimesh.load look the same as those loaded with mi.load_dict? Here are a few strategies to consider:

1. Data Type and Layout Consistency

The most critical step is to ensure that the data types and layout of the vertex positions, faces, and normals are consistent between trimesh and Mitsuba 3. Let's break this down:

  • Vertex Positions: trimesh stores vertex positions as a NumPy array of shape (N, 3), where N is the number of vertices. Each row represents the (x, y, z) coordinates of a vertex. In Mitsuba 3, vertex positions are typically expected as a flat array of floats, where the coordinates are interleaved (e.g., [x1, y1, z1, x2, y2, z2, ...]).

    • Solution: Ensure that you're flattening the trimesh vertex array correctly using mesh_trimesh.vertices.ravel() and that the data type matches what Mitsuba 3 expects (usually dr.cuda.Float or np.float32).

  • Faces: trimesh stores faces as a NumPy array of shape (F, 3), where F is the number of faces. Each row represents the indices of the three vertices that make up a face. Mitsuba 3 also expects face indices as a flat array of unsigned integers (usually dr.cuda.UInt32 or np.uint32).

    • Solution: Flatten the trimesh faces array using mesh_trimesh.faces.ravel() and ensure the data type is correct.

  • Vertex Normals: trimesh stores vertex normals as a NumPy array of shape (N, 3), similar to vertex positions. Mitsuba 3 expects vertex normals in a flat, interleaved format as well.

    • Solution: Flatten the trimesh vertex normals array using mesh_trimesh.vertex_normals.ravel() and ensure the data type is consistent.

2. Understanding Data Representation in Dr.Jit

Mitsuba 3 leverages Dr.Jit for vectorized computations, meaning that data needs to be in a format that Dr.Jit can efficiently process. When you're manually feeding data into Mitsuba 3, you need to convert your NumPy arrays into Dr.Jit arrays (e.g., dr.cuda.Float, dr.cuda.UInt32).

Make sure you're using the correct Dr.Jit data types and that the data is properly transferred to the GPU if you're using CUDA.

3. Normal Orientation and Winding Order

Another potential issue is the orientation of the normals and the winding order of the faces. If the normals are flipped or the faces are wound in the wrong direction, it can lead to incorrect shading and visual artifacts.

  • Solution: You can try flipping the normals by negating them or reversing the order of the vertices in the faces. trimesh provides functions for manipulating normals and winding order, which can be helpful in these situations.

4. Utilizing mitsuba.core.Mesh Correctly

When creating the mi.Mesh object manually, ensure that you are setting the vertex_count and face_count parameters correctly. These values tell Mitsuba 3 how many vertices and faces to expect, and incorrect values can lead to memory access errors or rendering issues.

Also, double-check that you're updating the mesh parameters correctly using params.update(). This step is crucial for applying the changes you've made to the mesh data.

A Practical Example: Corrected Code Snippet

Let's put these concepts into practice with a corrected code snippet:

import mitsuba as mi
import drjit as dr
import trimesh
import numpy as np

mi.set_variant("cuda_ad_rgb") # Or your preferred variant

def load_mesh_trimesh(mesh_path):
    mesh_trimesh = trimesh.load(mesh_path)
    vertex_count = len(mesh_trimesh.vertices)
    face_count = len(mesh_trimesh.faces)

    mi_mesh = mi.Mesh(
        "mi_mesh",
        vertex_count=vertex_count,
        face_count=face_count,
    )

    params = mi.traverse(mi_mesh)
    params["vertex_positions"] = dr.cuda.Float(np.array(mesh_trimesh.vertices.ravel(), dtype=np.float32))
    params["faces"] = dr.cuda.UInt32(np.array(mesh_trimesh.faces.ravel(), dtype=np.uint32))
    if mesh_trimesh.vertex_normals is not None:
        params["vertex_normals"] = dr.cuda.Float(np.array(mesh_trimesh.vertex_normals.ravel(), dtype=np.float32))
    params.update()
    return mi_mesh

# Example Usage
mesh_path = "path/to/your/mesh.obj"  # Replace with your mesh file path
mi_mesh = load_mesh_trimesh(mesh_path)

scene_dict = {
    "type": "scene",
    "my_integrator": {
        "type": "path",  # Example integrator
        "max_depth": 8,
        "hide_emitters": True,
    },
    "my_sensor": {
        "type": "perspective",
        "fov": 45,
        "to_world": mi.ScalarTransform4f.look_at(
            target=[0, 0, 0],
            origin=[0, 0, 5],
            up=[0, 1, 0]
        ),
        "film": {
            "type": "hdrfilm",
            "width": 640,
            "height": 480,
        },
    },
    "my_texture": {
        "type": "diffuse",
        "reflectance": {
            "type": "rgb",
            "value": [0.8, 0.8, 0.8],
        },
    },
    "my_obj": {
        "type": "shape",
        "shape": mi_mesh,
        "bsdf": {
            "type": "diffuse",
            "reflectance": {
                "type": "ref",
                "id": "my_texture",
            },
        },
    },
    "my_envmap": {
        "type": "envmap",
        "filename": "",  # Replace with your envmap path (optional)
        "scale": 0.5,
    },
}

scene = mi.load_dict(scene_dict)
image = mi.render(scene, spp=64)

# You can now save the image using mi.util.write_image(filename, image)

Key improvements in this snippet:

  • Explicit Data Type Conversion: We're explicitly converting the NumPy arrays to np.float32 and np.uint32 before creating the Dr.Jit arrays. This ensures that the data types are consistent.
  • Correct Parameter Assignment: We're directly assigning the Dr.Jit arrays to the corresponding mesh parameters using `params[