如何从 matplotlib 中的图像数组制作视频？

Posted 2023-02-19

【中文标题】如何从 matplotlib 中的图像数组制作视频？

【英文标题】：How can I make a video from array of images in matplotlib?

【发布时间】：2016-04-30 18:44:25

【问题描述】：

我有几张图片展示了事物是如何随时间变化的。我使用以下代码将它们可视化为同一图上的许多图像：

import matplotlib.pyplot as plt
import matplotlib.cm as cm

img = [] # some array of images
fig = plt.figure()
for i in xrange(6):
    fig.add_subplot(2, 3, i + 1)
    plt.imshow(img[i], cmap=cm.Greys_r)

plt.show()

并得到类似：

这没关系，但我宁愿为它们制作动画以获取something like this video。如何使用 python 实现这一点，最好（不一定）使用 matplotlib

【问题讨论】：

您附加的视频链接已损坏！你能解决这个问题吗？

【参考方案1】：

这是一个可复制粘贴的功能，如果您正在处理长视频并使用流式迭代器（来自here），则非常方便

from typing import Iterator, Optional, Tuple
from pathlib import Path

import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np


def write_animation(
    itr: Iterator[np.array],
    out_file: Path,
    dpi: int = 50,
    fps: int = 30,
    title: str = "Animation",
    comment: Optional[str] = None,
    writer: str = "ffmpeg",
) -> None:
    """Function that writes an animation from a stream of input tensors.

    Args:
        itr: The image iterator, yielding images with shape (H, W, C).
        out_file: The path to the output file.
        dpi: Dots per inch for output image.
        fps: Frames per second for the video.
        title: Title for the video metadata.
        comment: Comment for the video metadata.
        writer: The Matplotlib animation writer to use (if you use the
            default one, make sure you have `ffmpeg` installed on your
            system).
    """

    first_img = next(itr)
    height, width, _ = first_img.shape
    fig, ax = plt.subplots(figsize=(width / dpi, height / dpi))

    # Ensures that there's no extra space around the image.
    fig.subplots_adjust(
        left=0,
        bottom=0,
        right=1,
        top=1,
        wspace=None,
        hspace=None,
    )

    # Creates the writer with the given metadata.
    Writer = mpl.animation.writers[writer]
    metadata = 
        "title": title,
        "artist": __name__,
        "comment": comment,
    
    mpl_writer = Writer(
        fps=fps,
        metadata=k: v for k, v in metadata.items() if v is not None,
    )

    with mpl_writer.saving(fig, out_file, dpi=dpi):
        im = ax.imshow(first_img, interpolation="nearest")
        mpl_writer.grab_frame()

        for img in itr:
            im.set_data(img)
            mpl_writer.grab_frame()

【参考方案2】：

另一种解决方案是使用matplotlib.animation 中的AnimationArtist，如animated image demo 中所述。适应您的示例将是

import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.animation as animation

img = [] # some array of images
frames = [] # for storing the generated images
fig = plt.figure()
for i in xrange(6):
    frames.append([plt.imshow(img[i], cmap=cm.Greys_r,animated=True)])

ani = animation.ArtistAnimation(fig, frames, interval=50, blit=True,
                                repeat_delay=1000)
# ani.save('movie.mp4')
plt.show()

【讨论】：

这里的ims是什么？

@PyWalker2797 一个错字。现在应该修好了。

【参考方案3】：

您可以使用 Agg 接口从 matplotlib 导出图像。

查看这些示例：

Agg Buffer to Array CanvasAgg demo

这是您的完整代码：

# imports
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import cv2

# Use Agg backend for canvas
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas

# create OpenCV video writer
video = cv2.VideoWriter('video.mp4', cv2.VideoWriter_fourcc('A','V','C','1'), 1, (mat.shape[0],mat.shape[1]))

# loop over your images
for i in xrange(len(img)):

    fig = plt.figure()
    plt.imshow(img[i], cmap=cm.Greys_r)

    # put pixel buffer in numpy array
    canvas = FigureCanvas(fig)
    canvas.draw()
    mat = np.array(canvas.renderer._renderer)
    mat = cv2.cvtColor(mat, cv2.COLOR_RGB2BGR)

    # write frame to video
    video.write(mat)

# close video writer
cv2.destroyAllWindows()
video.release()

【参考方案4】：

您可以尝试延迟按顺序绘制图像（帧）。如果您有很多帧，那么在 plt.pause() 函数中减少帧之间的等待时间可能是有意义的。

# need this line if you're using jupyter notebooks
%matplotlib notebook

x = [] # Some array of images
fig = plt.figure()
viewer = fig.add_subplot(111)
plt.ion() # Turns interactive mode on (probably unnecessary)
fig.show() # Initially shows the figure

for i in range(len(x)):
    viewer.clear() # Clears the previous image
    viewer.imshow(x[i]) # Loads the new image
    plt.pause(.1) # Delay in seconds
    fig.canvas.draw() # Draws the image to the screen

【讨论】：

除了提供代码之外，最好能解释一下解决方案并添加一些细节。

【参考方案5】：

我实现了一个适合您和新手的便捷脚本。试试看here。

你的例子：

imagelist = YOUR-IMAGE-LIST
def redraw_fn(f, axes):
    img = imagelist[f]
    if not redraw_fn.initialized:
        redraw_fn.im = axes.imshow(img, animated=True)
        redraw_fn.initialized = True
    else:
        redraw_fn.im.set_array(img)
redraw_fn.initialized = False

videofig(len(imagelist), redraw_fn, play_fps=30)

【参考方案6】：

我自己的未来是这样的：

def generate_video(img):
    for i in xrange(len(img)):
        plt.imshow(img[i], cmap=cm.Greys_r)
        plt.savefig(folder + "/file%02d.png" % i)

    os.chdir("your_folder")
    subprocess.call([
        'ffmpeg', '-framerate', '8', '-i', 'file%02d.png', '-r', '30', '-pix_fmt', 'yuv420p',
        'video_name.mp4'
    ])
    for file_name in glob.glob("*.png"):
        os.remove(file_name)

【参考方案7】：

例如，您可以使用plt.savefig("file%d.png" % i) 将图像导出为 png，然后使用 ffmpeg 生成视频。

Here you find help to generate video from images