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)