Image to 3D & spin with python
This code loads an image, converts it to grayscale, and creates a 3D plot of the image intensity values using matplotlib. The plot shows the intensity of each pixel in the image as a point in 3D space, with the x and y coordinates representing the pixel's position in the image and the z coordinate representing the pixel's intensity.
The code also creates an animation of the plot, which rotates the viewpoint of the 3D plot around the z axis.
Here is a step-by-step explanation of the code:
The necessary libraries are imported, including matplotlib for plotting, numpy for numerical operations, and PIL for loading and converting the image.
The image is loaded using the Image module from PIL and converted to grayscale using the "L" mode.
The image is converted to a numpy array for processing.
A grid of vertices is created using np.meshgrid to represent the x and y coordinates of each pixel in the image.
The intensity values of each pixel in the image are assigned to the z coordinates of the vertices.
A 3D plot is created using the ax.plot_surface method, with the x, y, and z coordinates of the vertices used as input. The cmap argument is set to 'gray' to display the plot in grayscale.
The axis limits and labels are set using the ax.set_xlim3d, ax.set_ylim3d, and ax.set_zlim3d methods.
A function called "update" is defined to update the viewpoint of the 3D plot. The function takes a single argument "i", which represents the elevation angle in degrees.
An animation is created using FuncAnimation from matplotlib.animation. The animation updates the plot by calling the "update" function with a range of elevation angles from -90 to 90 degrees in steps of 2 degrees. The interval argument is set to 50 milliseconds to control the speed of the animation.
The plot and animation are displayed using plt.show().
Image by https://rudalle.ru/
code is here: https://github.com/msamsonov1/imageTo3D
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