如何使用 PIL 將文件夾中的多個圖像裁剪為圓形？

Question

我有一個圖像文件夾，我想將它們裁剪成圓形。

這是原始圖像：

我想要的結果是這樣的：

我的代碼是：

import os
import glob
from PIL import Image, ImageDraw, ImageFilter
import numpy as np

def mask_circle_solid(pil_img, background_color, blur_radius, offset=0):
    background = Image.new(pil_img.mode, pil_img.size, background_color)

    offset = blur_radius * 2 + offset
    mask = Image.new("L", pil_img.size, 0)
    draw = ImageDraw.Draw(mask)
    draw.ellipse((offset, offset, pil_img.size[0] - offset, pil_img.size[1] - offset),         fill=255)
    mask = mask.filter(ImageFilter.GaussianBlur(blur_radius))

    return Image.composite(pil_img, background, mask)

def mask_circle_transparent(pil_img, blur_radius, offset=0):
    offset = blur_radius * 2 + offset
    mask = Image.new("L", pil_img.size, 0)
    draw = ImageDraw.Draw(mask)
    draw.ellipse((offset, offset, pil_img.size[0] - offset, pil_img.size[1] - offset), fill=255)
    mask = mask.filter(ImageFilter.GaussianBlur(blur_radius))

    result = pil_img.copy()
    result.putalpha(mask)

    return result

def crop_max_square(pil_img):
    return crop_center(pil_img, min(pil_img.size), min(pil_img.size))

def crop_center(pil_img, crop_width, crop_height):
    img_width, img_height = pil_img.size
    return pil_img.crop(((img_width - crop_width) // 2,
                     (img_height - crop_height) // 2,
                     (img_width + crop_width) // 2,
                     (img_height + crop_height) // 2))


im = []

for f in glob.iglob("./*.jpg"):
    im.append(np.asarray(Image.open(f)))
thumb_width = 150

im = np.array(im)

list_files = os.listdir(".")
list_files.sort()
list_files.remove("Test.py")
list_files.remove(".DS_Store")

for i in range(0,len(im)):
    im_square[i] = crop_max_square(im[i]).resize((thumb_width, thumb_width), Image.LANCZOS)
    im_thumb[i] = mask_circle_transparent(im_square[i], 4)
    im_thumb[i].save(list_files[i])

我已經使用了這篇文章中的函數：

使用 Python、Pillow 生成方形或圓形縮略圖

但我得到這個錯誤：

line 30, in crop_max_square
    return crop_center(pil_img, min(pil_img.size), min(pil_img.size))
TypeError: 'int' object is not iterable

Answer 1

我不確定您是否真的需要使用 numpy 來加載文件，但您可以執行 共享頁面的“批處理示例代碼”的操作：

import os
import glob
from PIL import Image, ImageDraw, ImageFilter


def mask_circle_solid(pil_img, background_color, blur_radius, offset=0):
    background = Image.new(pil_img.mode, pil_img.size, background_color)

    offset = blur_radius * 2 + offset
    mask = Image.new("L", pil_img.size, 0)
    draw = ImageDraw.Draw(mask)
    draw.ellipse((offset, offset, pil_img.size[0] - offset, pil_img.size[1] - offset), fill=255)
    mask = mask.filter(ImageFilter.GaussianBlur(blur_radius))

    return Image.composite(pil_img, background, mask)


def mask_circle_transparent(pil_img, blur_radius, offset=0):
    offset = blur_radius * 2 + offset
    mask = Image.new("L", pil_img.size, 0)
    draw = ImageDraw.Draw(mask)
    draw.ellipse((offset, offset, pil_img.size[0] - offset, pil_img.size[1] - offset), fill=255)
    mask = mask.filter(ImageFilter.GaussianBlur(blur_radius))

    result = pil_img.copy()
    result.putalpha(mask)

    return result


def crop_max_square(pil_img):
    return crop_center(pil_img, min(pil_img.size), min(pil_img.size))


def crop_center(pil_img, crop_width, crop_height):
    img_width, img_height = pil_img.size
    return pil_img.crop(((img_width - crop_width) // 2,
                         (img_height - crop_height) // 2,
                         (img_width + crop_width) // 2,
                         (img_height + crop_height) // 2))


im = []
jpgs_files_path = "./" # Replace the "./" path by the path where the .jpg images are.
files = glob.glob(os.path.join(jpgs_files_path, '*.jpg')) 
thumb_width = 150

for f in files:
    im = Image.open(f)
    im_thumb = crop_max_square(im).resize((thumb_width, thumb_width), Image.LANCZOS)
    im_thumb = mask_circle_transparent(im_thumb, 4)
    ftitle, fext = os.path.splitext(os.path.basename(f))
    im_thumb.save(os.path.join("./dstdir/", ftitle + '_thumbnail.png'), quality=95)

由於 JPG 不支持透明度，您需要丟棄 Alpha 通道或另存為支持透明度的內容，如 PNG。