如何使用脚本裁剪 GIF？

Question

有没有像这个页面一样在 python 中裁剪 gif 的脚本：https://www.iloveimg.com/crop-image ？

前段时间，我找到了Image Cropping using Python，但问题是你需要用光标绘制矩形。

我需要一个像 https://www.iloveimg.com/crop-image 这样的 GUI，它有一个可以移动到任何我想要的地方的矩形：

看到https://www.iloveimg.com/crop-image 将 GIF 裁剪成一个新的动画。而Image Cropping using Python 只裁剪 GIF 的第一帧。

我可以使用的一些模块是：

• Tkinter（最好）
• Pygame
• 枕头/PIL
• 其他

Answer 1

在阅读了一些教程后，我想出了这个解决方案：

import numpy as np
import matplotlib.pyplot as plt

from PIL import Image, ImageSequence
from matplotlib.widgets import RectangleSelector

class ImageCutter:
    def __init__(self, file):
        self.file = file
        self.img = Image.open(file)
        self.frames = [np.array(frame.copy().convert("RGB"))
                        for frame in ImageSequence.Iterator(self.img)]

        self.pos = np.array([0,0,0,0])


    def crop(self):
        self.pos = self.pos.astype(int)
        self.cropped_imgs =  [frame[self.pos[1]:self.pos[3], self.pos[0]:self.pos[2]]
                for frame in self.frames]
        self.save()

    def save(self):
        self.imgs_pil = [Image.fromarray(np.uint8(img))
                         for img in self.cropped_imgs]
        self.imgs_pil[0].save(self.file+"_cropped.gif",
                     save_all=True,
                     append_images=self.imgs_pil[1:],
                     duration=16,
                     loop=0)


data = ImageCutter("final.gif")

fig, ax = plt.subplots(1)
ax.axis("off")

plt.imshow(data.frames[0])

def onselect(eclick, erelease):
    "eclick and erelease are matplotlib events at press and release."
    data.pos = np.array([eclick.xdata, eclick.ydata, erelease.xdata, erelease.ydata])

def onrelease(event):
    data.crop()

cid = fig.canvas.mpl_connect('button_release_event', onrelease)
RS = RectangleSelector(ax, onselect, drawtype='box')

您将文件名放在ImageCutter 实例中，它将绘制第一帧，让您用鼠标选择一个框，该框定义了要裁剪的区域。定义区域后，单击图像中的某个位置，程序会将裁剪后的 gif 保存在您的工作文件夹中。

您可以使用自己的Rectangle代替小部件

Answer 2

由于这仍然是谷歌在 python 中裁剪 gif 的热门话题，因此可能值得更新。

如果我们像这样概括上面的方法，那么用法就更熟悉了：

import io
from dataclasses import dataclass
from pathlib import Path
from typing import List, Tuple, Union

import numpy as np
from PIL import Image, ImageSequence

Left, Upper, Right, Lower = int, int, int, int
Box = Tuple[Left, Upper, Right, Lower]
Frames = List[np.ndarray]
ImageArray = List[Image.Image]
File = Union[str, bytes, Path, io.BytesIO]


@dataclass
class MultiFrameImage:
    fp: File

    @property
    def im(self):
        return Image.open(self.fp)

    @property
    def frames(self) -> Frames:
        return [
            np.array(frame.copy().convert("RGB"))
            for frame in ImageSequence.Iterator(self.im)
        ]

    def crop_frames(self, box: Box) -> List[np.ndarray]:
        left, upper, right, lower = box
        return [frame[upper:lower, left:right] for frame in self.frames]

    def image_array_from_frames(self, frames: Frames) -> ImageArray:
        return [Image.fromarray(np.uint8(frame)) for frame in frames]

    def crop_to_buffer(self, box: Box, **kwargs) -> io.BytesIO:
        cropped_frames = self.crop_frames(box)
        cropped_images = self.image_array_from_frames(cropped_frames)
        buffer = io.BytesIO()
        cropped_images[0].save(
            buffer,
            save_all=True,
            format="GIF",
            append_images=cropped_images[1:],
            duration=16,
            loop=0,
            **kwargs
        )
        return buffer

    def crop(self, box: Box, **kwargs) -> Image.Image:
        return Image.open(self.crop_to_buffer(box, **kwargs))

这里的crop 方法将返回一个PIL 图像，就像Image.crop 一样。

用法如下：

image = MultiFrameImage(io.BytesIO(avatar_bytes))
buffer = image.crop_to_buffer((left, upper, right, lower))

# or if you need the image instead of the buffer
cropped_image = image.crop((left, upper, right, lower))

---

如果你赶时间，忽略这部分并复制上面的代码

另一种选择（只是为了好玩，我提出的第一个可能更干净）是从 PIL 猴子修补 open 函数并递归我们的 crop 方法，如下所示：

import io
from dataclasses import dataclass
from pathlib import Path
from typing import List, Tuple, Union, cast

import numpy as np
from PIL import Image, ImageSequence

Left, Upper, Right, Lower = int, int, int, int
Box = Tuple[Left, Upper, Right, Lower]
Frames = List[np.ndarray]
ImageArray = List[Image.Image]
File = Union[str, bytes, Path, io.BytesIO]


@dataclass
class MultiFrameImage:
    fp: File

    @property
    def im(self):
        return Image.open(self.fp)

    @property
    def frames(self) -> Frames:
        return [
            np.array(frame.copy().convert("RGB"))
            for frame in ImageSequence.Iterator(self.im)
        ]

    def crop_frames(self, box: Box) -> List[np.ndarray]:
        left, upper, right, lower = box
        return [frame[upper:lower, left:right] for frame in self.frames]

    def image_array_from_frames(self, frames: Frames) -> ImageArray:
        return [Image.fromarray(np.uint8(frame)) for frame in frames]

    def crop_to_buffer(self, box: Box, **kwargs) -> io.BytesIO:
        cropped_frames = self.crop_frames(box)
        cropped_images = self.image_array_from_frames(cropped_frames)
        buffer = io.BytesIO()
        cropped_images[0].save(
            buffer,
            save_all=True,
            format="GIF",
            append_images=cropped_images[1:],
            duration=16,
            loop=0,
            **kwargs
        )
        return buffer

    def crop(self, box: Box, **kwargs) -> "MultiFrameImage":
        return open_multiframe_image(self.crop_to_buffer(box, **kwargs))


class MonkeyPatchedMultiFrameImage(Image.Image, MultiFrameImage):
    pass


def open_multiframe_image(fp):
    multi_frame_im = MultiFrameImage(fp)
    im = multi_frame_im.im
    setattr(im, "frames", multi_frame_im.frames)
    setattr(im, "crop_frames", multi_frame_im.crop_frames)
    setattr(im, "image_array_from_frames", multi_frame_im.image_array_from_frames)
    setattr(im, "crop_to_buffer", multi_frame_im.crop_to_buffer)
    setattr(im, "crop", multi_frame_im.crop)
    return cast(MonkeyPatchedMultiFrameImage, im)

这给人一种我们实际上是在使用 PIL Image 类的错觉。这很危险，除非您打算同时覆盖所有其他 Image 方法。对于大多数用例，我给出的第一个代码块就足够了