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Export your results

Taichi has functions that help you export visual results to images or videos. This tutorial demonstrates how to use them step by step.

Export images

  • There are two ways to export visual results of your program to images.
  • The first and easier way is to make use of ti.GUI.
  • The second way is to call some Taichi functions such as ti.imwrite.

Export images using ti.GUI.show

  • ti.GUI.show(filename) can not only display the GUI canvas on your screen, but also save the image to your specified filename.
  • Note that the format of the image is fully determined by the suffix of filename.
  • Taichi now supports saving to png, jpg, and bmp formats.
  • We recommend using png format. For example:
import taichi as ti
import os

ti.init()

pixels = ti.var(ti.u8, shape=(512, 512, 3))

@ti.kernel
def paint():
    for i, j, k in pixels:
        pixels[i, j, k] = ti.random() * 255

iterations = 1000
gui = ti.GUI("Random pixels", res=512)

# mainloop
for i in range(iterations):
    paint()
    gui.set_image(pixels)

    filename = f'frame_{i:05d}.png'   # create filename with suffix png
    print(f'Frame {i} is recorded in {filename}')
    gui.show(filename)  # export and show in GUI
  • After running the code above, you will get a series of images in the current folder.

Export images using ti.imwrite

To save images without invoking ti.GUI.show(filename), use ti.imwrite(filename). For example:

import taichi as ti

ti.init()

pixels = ti.var(ti.u8, shape=(512, 512, 3))

@ti.kernel
def set_pixels():
    for i, j, k in pixels:
        pixels[i, j, k] = ti.random() * 255

set_pixels()
filename = f'imwrite_export.png'
ti.imwrite(pixels.to_numpy(), filename)
print(f'The image has been saved to {filename}')
  • ti.imwrite can export Taichi tensors (ti.Matrix, ti.Vector, ti.var) and numpy tensors np.ndarray.
  • Same as above ti.GUI.show(filename), the image format (png, jpg and bmp) is also controlled by the suffix of filename in ti.imwrite(filename).
  • Meanwhile, the resulted image type (grayscale, RGB, or RGBA) is determined by the number of channels in the input tensor, i.e., the length of the third dimension (tensor.shape[2]).
  • In other words, a tensor that has shape (w, h) or (w, h, 1) will be exported as a grayscale image.
  • If you want to export RGB or RGBA images instead, the input tensor should have a shape (w, h, 3) or (w, h, 4) respectively.

Note

All Taichi tensors have their own data types, such as ti.u8 and ti.f32. Different data types can lead to different behaviors of ti.imwrite. Please check out :ref:`gui` for more details.

  • Taichi offers other helper functions that read and show images in addition to ti.imwrite. They are also demonstrated in :ref:`gui`.

Export videos

Note

The video export utilities of Taichi depend on ffmpeg. If ffmpeg is not installed on your machine, please follow the installation instructions of ffmpeg at the end of this page.

  • ti.VideoManager can help you export results in mp4 or gif format. For example,
import taichi as ti

ti.init()

pixels = ti.var(ti.u8, shape=(512, 512, 3))

@ti.kernel
def paint():
    for i, j, k in pixels:
        pixels[i, j, k] = ti.random() * 255

result_dir = "./results"
video_manager = ti.VideoManager(output_dir=result_dir, framerate=24, automatic_build=False)

for i in range(50):
    paint()

    pixels_img = pixels.to_numpy()
    video_manager.write_frame(pixels_img)
    print(f'\rFrame {i+1}/50 is recorded', end='')

print()
print('Exporting .mp4 and .gif videos...')
video_manager.make_video(gif=True, mp4=True)
print(f'MP4 video is saved to {video_manager.get_output_filename(".mp4")}')
print(f'GIF video is saved to {video_manager.get_output_filename(".gif")}')

After running the code above, you will find the output videos in the ./results/ folder.

Install ffmpeg

Install ffmpeg on Windows

  • Download the ffmpeg archive(named ffmpeg-2020xxx.zip) from ffmpeg;
  • Unzip this archive to a folder, such as "D:/YOUR_FFMPEG_FOLDER";
  • Important: add D:/YOUR_FFMPEG_FOLDER/bin to the PATH environment variable;
  • Open the Windows cmd or PowerShell and type the line of code below to test your installation. If ffmpeg is set up properly, the version information will be printed.
ffmpeg -version

Install ffmpeg on Linux

  • Most Linux distribution came with ffmpeg natively, so you do not need to read this part if the ffmpeg command is already there on your machine.
  • Install ffmpeg on Ubuntu
sudo apt-get update
sudo apt-get install ffmpeg
  • Install ffmpeg on CentOS and RHEL
sudo yum install ffmpeg ffmpeg-devel
  • Install ffmpeg on Arch Linux:
  • Test your installation using
ffmpeg -h

Install ffmpeg on OS X

  • ffmpeg can be installed on OS X using homebrew:
brew install ffmpeg

Export PLY files

  • ti.PLYwriter can help you export results in the ply format. Below is a short example of exporting 10 frames of a moving cube with vertices randomly colored,
import taichi as ti
import numpy as np

ti.init(arch=ti.cpu)

num_vertices = 1000
pos = ti.Vector(3, dt=ti.f32, shape=(10, 10, 10))
rgba = ti.Vector(4, dt=ti.f32, shape=(10, 10, 10))


@ti.kernel
def place_pos():
    for i, j, k in pos:
        pos[i, j, k] = 0.1 * ti.Vector([i, j, k])


@ti.kernel
def move_particles():
    for i, j, k in pos:
        pos[i, j, k] += ti.Vector([0.1, 0.1, 0.1])


@ti.kernel
def fill_rgba():
    for i, j, k in rgba:
        rgba[i, j, k] = ti.Vector(
            [ti.random(), ti.random(), ti.random(), ti.random()])


place_pos()
series_prefix = "example.ply"
for frame in range(10):
    move_particles()
    fill_rgba()
    # now adding each channel only supports passing individual np.array
    # so converting into np.ndarray, reshape
    # remember to use a temp var to store so you dont have to convert back
    np_pos = np.reshape(pos.to_numpy(), (num_vertices, 3))
    np_rgba = np.reshape(rgba.to_numpy(), (num_vertices, 4))
    # create a PLYWriter
    writer = ti.PLYWriter(num_vertices=num_vertices)
    writer.add_vertex_pos(np_pos[:, 0], np_pos[:, 1], np_pos[:, 2])
    writer.add_vertex_rgba(
        np_rgba[:, 0], np_rgba[:, 1], np_rgba[:, 2], np_rgba[:, 3])
    writer.export_frame_ascii(frame, series_prefix)

After running the code above, you will find the output sequence of ply files in the current working directory. Next, we will break down the usage of ti.PLYWriter into 4 steps and show some examples.

  • Setup ti.PLYWriter
# num_vertices must be a positive int
# num_faces is optional, default to 0
# face_type can be either "tri" or "quad", default to "tri"

# in our previous example, a writer with 1000 vertices and 0 triangle faces is created
num_vertices = 1000
writer = ti.PLYWriter(num_vertices=num_vertices)

# in the below example, a writer with 20 vertices and 5 quadrangle faces is created
writer2 = ti.PLYWriter(num_vertices=20, num_faces=5, face_type="quad")
  • Add required channels
# A 2D grid with quad faces
#     y
#     |
# z---/
#    x
#         19---15---11---07---03
#         |    |    |    |    |
#         18---14---10---06---02
#         |    |    |    |    |
#         17---13---19---05---01
#         |    |    |    |    |
#         16---12---08---04---00

writer = ti.PLYWriter(num_vertices=20, num_faces=12, face_type="quad")

# For the vertices, the only required channel is the position,
# which can be added by passing 3 np.array x, y, z into the following function.

x = np.zeros(20)
y = np.array(list(np.arange(0, 4))*5)
z = np.repeat(np.arange(5), 4)
writer.add_vertex_pos(x, y, z)

# For faces (if any), the only required channel is the list of vertex indices that each face contains.
indices = np.array([0, 1, 5, 4]*12)+np.repeat(
    np.array(list(np.arange(0, 3))*4)+4*np.repeat(np.arange(4), 3), 4)
writer.add_faces(indices)
  • Add optional channels
# Add custome vertex channel, the input should include a key, a supported datatype and, the data np.array
vdata = np.random.rand(20)
writer.add_vertex_channel("vdata1", "double", vdata)

# Add custome face channel
foo_data = np.zeros(12)
writer.add_face_channel("foo_key", "foo_data_type", foo_data)
# error! because "foo_data_type" is not a supported datatype. Supported ones are
# ['char', 'uchar', 'short', 'ushort', 'int', 'uint', 'float', 'double']

# PLYwriter already defines several useful helper functions for common channels
# Add vertex color, alpha, and rgba
# using float/double r g b alpha to reprent color, the range should be 0 to 1
r = np.random.rand(20)
g = np.random.rand(20)
b = np.random.rand(20)
alpha = np.random.rand(20)
writer.add_vertex_color(r, g, b)
writer.add_vertex_alpha(alpha)
# equivilantly
# add_vertex_rgba(r, g, b, alpha)

# vertex normal
writer.add_vertex_normal(np.ones(20), np.zeros(20), np.zeros(20))

# vertex index, and piece (group id)
writer.add_vertex_id()
writer.add_vertex_piece(np.ones(20))

# Add face index, and piece (group id)
# Indexing the existing faces in the writer and add this channel to face channels
writer.add_face_id()
# Set all the faces is in group 1
writer.add_face_piece(np.ones(12))
  • Export files
series_prefix = "example.ply"
series_prefix_ascii = "example_ascii.ply"
# Export a single file
# use ascii so you can read the content
writer.export_ascii(series_prefix_ascii)

# alternatively, use binary for a bit better performance
# writer.export(series_prefix)

# Export a sequence of files, ie in 10 frames
for frame in range(10):
    # write each frame as i.e. "example_000000.ply" in your current running folder
    writer.export_frame_ascii(frame, series_prefix_ascii)
    # alternatively, use binary
    # writer.export_frame(frame, series_prefix)

    # update location/color
    x = x + 0.1*np.random.rand(20)
    y = y + 0.1*np.random.rand(20)
    z = z + 0.1*np.random.rand(20)
    r = np.random.rand(20)
    g = np.random.rand(20)
    b = np.random.rand(20)
    alpha = np.random.rand(20)
    # re-fill
    writer = ti.PLYWriter(num_vertices=20, num_faces=12, face_type="quad")
    writer.add_vertex_pos(x, y, z)
    writer.add_faces(indices)
    writer.add_vertex_channel("vdata1", "double", vdata)
    writer.add_vertex_color(r, g, b)
    writer.add_vertex_alpha(alpha)
    writer.add_vertex_normal(np.ones(20), np.zeros(20), np.zeros(20))
    writer.add_vertex_id()
    writer.add_vertex_piece(np.ones(20))
    writer.add_face_id()
    writer.add_face_piece(np.ones(12))

Import ply files into Houdini and Blender

Houdini supports importing a series of ply files sharing the same prefix/post-fix. Our export_frame can achieve the requirement for you. In Houdini, click File->Import->Geometry and navigate to the folder containing your frame results, who should be collapsed into one single entry like example_$F6.ply (0-9). Double-click this entry to finish the importing process.

Blender requires an add-on called Stop-motion-OBJ to load the result sequences. A very detailed explanation video is provided by the author on how to install, enable, and use the add-on. Just keep in mind that significant changes in the workflow were made in their most recent test releases. To follow their instruction readme and video, please use v2.0.2.