Python PIL 中是否可以实现负 X 倾斜而不进行裁剪？

Question

我正在努力使用以下代码使用 X 倾斜来转换图像

from PIL import Image

def x_skew_image(input_path, output_path, skew_factor):
    # Open the input image
    input_image = Image.open(input_path)

    # Get the image dimensions
    width, height = input_image.size

    # Calculate the new width after skewing
    new_width = int(width + abs(skew_factor) * height)

    # Create a new image with the calculated width and the same height
    output_image = Image.new("RGB", (new_width, height))

    # Apply the skew transformation
    for y in range(height):
        x_offset = int(skew_factor * y)
        for x in range(width):
            if 0 <= x + x_offset < new_width:
                output_image.putpixel((x + x_offset, y), input_image.getpixel((x, y)))

    # Save the skewed image
    output_image.save(output_path)

# Replace these paths and skew_factor as needed
input_path = r'input_path'  # Replace with the path to your input image
output_path = r'output_path'  # Replace with the desired output path
skew_factor = -0.4  # Adjust the skew factor as needed

x_skew_image(input_path, output_path, skew_factor)

但是，当尝试使用负 X 倾斜（将 skew_factor 更改为负值）时，我遇到了问题，并且图像似乎被裁剪了。我该如何修改代码来解决这个问题？

Answer 1

如果您将其更改为这样，您的代码就可以工作：

#!/usr/bin/env python3

from PIL import Image

def x_skew_image(input_path, output_path, skew_factor):
    # Open the input image
    input_image = Image.open(input_path)

    # Get the image dimensions
    width, height = input_image.size

    # Calculate the new width after skewing
    new_width = int(width + abs(skew_factor) * height)

    # Create a new image with the calculated width and the same height
    output_image = Image.new("RGB", (new_width, height))

    # Apply the skew transformation
    for y in range(height):
        x_offset = int(skew_factor * y)
        if skew_factor < 0:
            x_offset = int(-skew_factor * (height - y))
            
        for x in range(width):
            new_x = x + x_offset
            if (new_x >= 0 ) and (new_x < new_width):
                output_image.putpixel((new_x, y), input_image.getpixel((x, y)))

    # Save the skewed image
    output_image.save(output_path)

# Replace these paths and skew_factor as needed
input_path = 'CrazyCat.jpg'
output_path = 'result.jpg'
skew_factor = -0.4  # Adjust the skew factor as needed

x_skew_image(input_path, output_path, skew_factor)

与

skew_factor=0.4

：

与

skew_factor=-0.4

：

---

但是，我真的建议 AGAINST 使用

for

循环在 Python 中进行图像处理 - 它们很慢并且容易出错。与使用即时且更简单的内置仿射变换方法相比，运行代码时存在明显的延迟：

#!/usr/bin/env python3

from PIL import Image

input_path  = 'CrazyCat.jpg'
output_path = 'result.jpg'

im = Image.open(input_path)
w , h = im.size

shear_factor = 0.4
new_width = int(w + abs(shear_factor)*h)
if shear_factor > 0:
   res = im.transform((new_width,h), Image.AFFINE, (1, shear_factor, -shear_factor*h, 0, 1, 0))
else:
   res = im.transform((new_width,h), Image.AFFINE, (1, shear_factor, 0, 0, 1, 0))

res.save('result.jpg')