Can not plot off file using plotly mesh plots

Question

I am trying to plot/visualize an off plot using python. Currently, I am trying to use the Plotly mesh plots for the same.
This is the mesh I am trying to plot:

First, I am trying to read the OFF file and extract all the vertices from it, and then giving the x y and z coordinates of these vertices to plotly mesh3d function as shown in the reference. However, that results in a plot that is nowhere similar to the orginal mesh. This is what the result looks like:

Here is my code for the same:

import plotly.graph_objects as go
import numpy as np

# loading the mesh and getting the vertices
def ExtractRawData(filepath):
    # read the file path
    with open(filepath) as file:
        if 'OFF' != file.readline().strip():
            raise('Not a valid OFF header')
        n_verts, n_faces, n_dontknow = tuple([int(s) for s in file.readline().strip().split(' ')])
        verts = [[float(s) for s in file.readline().strip().split(' ')] for i_vert in range(n_verts)]
        faces = [[int(s) for s in file.readline().strip().split(' ')][1:] for i_face in range(n_faces)]
        return np.array(verts), np.array(faces)

# extracting the vertices from the off file 
verts, faces = ExtractRawData('Turbine blade.off')
# getting the x, y and z coordinates from the vertices
x = verts[:,0]
y = verts[:,1]
z = verts[:,2]

# plotting the mesh
fig = go.Figure(data=[go.Mesh3d(x=x, y=y, z=z)])
fig.show()

Is there anything wrong with my code? How do I get the right plot?

Hamudi Naanaa · Accepted Answer · 2022-06-05 18:00:52Z

I had a similar issue with my .off model and the solution was to state the x,y,z coordinates of the triangles used to build the mesh (=faces in .off) explicitly by including i,j,k parameters in the Mesh3d call:

Mesh3d(
  ...
  i=..., # list of all x coordinates of faces
  j=..., # list of all y coordinates of faces
  k=..., # list of all z coordinates of faces
  ...
)

Here's my full code:

# read_off reads all vertices and faces as numpy arrays
vertices, faces = read_off("ex03/model.off")
x, y, z = vertices[:,0], vertices[:,1], vertices[:,2]
i, j, k = faces[:,0], faces[:,1], faces[:,2]

# Just to make sure I've read everything correctly
print(f"x:\n{x}\ny:\n{y}\nz:\n{z}\nfaces:\n{faces}")

fig = go.Figure(data=[go.Mesh3d(
        # 8 vertices of a cube
        x=x,
        y=y,
        z=z,
        colorbar_title='z',
        colorscale=[[0, 'gold'],
                    [0.5, 'mediumturquoise'],
                    [1, 'magenta']],
        # Intensity of each vertex, which will be interpolated and color-coded
        intensity = np.linspace(0, 1, 8, endpoint=True),
        # i, j and k give the vertices of triangles
        i = i,
        j = j,
        k = k,
        name='y',
        showscale=True
    )])
fig.show()

My result after this fix

Also, here's my corresponding read_off(...) using pandas and numpy (mine might differ from yours?):

def read_off(filename):
    """TODO: explain"""
    with open(filename) as off:
        # (1) parse header
        first_line = off.readline()
        if "OFF" not in first_line:
            raise ValueError('The file does not start whith the word OFF')
        color = True if "C" in first_line else False

        count = 1
        for line in off:
            count += 1
            # (2) ignore comments
            if line.startswith("#"):
                continue
            # (3) extract metadata
            line = line.strip().split()
            if len(line) > 1:
                n_vertices = int(line[0])
                n_faces = int(line[1])
                break

        # (4) load data
        data = {}
        point_names = ["x", "y", "z"]
        if color:
            point_names.extend(["red", "green", "blue"])

        data["vertices"] = pd.read_csv(filename, sep=" ", header=None, engine="python",
                                     skiprows=count, skipfooter=n_faces,
                                     names=point_names, index_col=False)
        for n in ["x", "y", "z"]:
            data["vertices"][n] = data["vertices"][n].astype(np.float32)

        if color:
            for n in ["red", "green", "blue"]:
                data["vertices"][n] = data["vertices"][n].astype(np.uint8)

        data["faces"] = pd.read_csv(filename, sep=" ", header=None, engine="python",
                                   skiprows=(count + n_vertices), usecols=[1, 2, 3],
                                   names=["v1", "v2", "v3"])

        return pd.DataFrame.to_numpy(data["vertices"]), pd.DataFrame.to_numpy(data["faces"])

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