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from stl import mesh
from mpl_toolkits import mplot3d
from matplotlib import pyplot as plt
from typing import List, Tuple
def generate_mesh_images(file_path: str, viewing_angles: List[Tuple[int, int]], output_prefix: str = 'mesh_') -> List[str]:
"""
Generate images of an STL file from different viewing angles and return their file paths.
Args:
file_path (str): Path to the STL file.
viewing_angles (List[Tuple[int, int]]): List of tuples containing the elevation and azimuth angles for viewing.
output_prefix (str, optional): Prefix for the output image filenames. Defaults to 'mesh_'.
Returns:
List[str]: List of file paths of the generated images.
"""
# Load the STL file
your_mesh = mesh.Mesh.from_file(file_path)
# List to store the file paths of the generated images
image_paths = []
# Iterate over each viewing angle and generate an image
for i, (elev, azim) in enumerate(viewing_angles, start=1):
# Create a new plot with a larger figure size
fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(111, projection='3d')
# Add the STL file to the plot
ax.add_collection3d(mplot3d.art3d.Poly3DCollection(your_mesh.vectors))
# Calculate the limits of the mesh
max_dim = max(your_mesh.points.flatten())
min_dim = min(your_mesh.points.flatten())
# Set the limits of the plot
ax.set_xlim([min_dim, max_dim])
ax.set_ylim([min_dim, max_dim])
ax.set_zlim([min_dim, max_dim])
# Set the viewing angle
ax.view_init(elev=elev, azim=azim)
# Save the plot as an image
image_path = f'{output_prefix}{i}.png'
plt.savefig(image_path)
image_paths.append(image_path)
# Close the plot to avoid memory leaks
plt.close()
return image_paths
if __name__ == "__main__":
# Example usage:
# file_path = 'sample_data.stl'
viewing_angles = [(30, 45), (60, 90), (45, 135)]
# generate_mesh_images(file_path, viewing_angles)
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