How to use Python to color gradient images

How to use Python to perform color gradient on pictures

Introduction:
In image processing, color gradient is a common technique. By gradually transitioning one color to another, you can make your image look more vivid and attractive. This article will introduce how to use Python to color gradient images and provide relevant code examples.

1. Loading pictures
   First, we need to load a picture to be processed. In Python, you can use the PIL library (an extension of the Pillow library) to process images. The following is a code example for loading an image:

from PIL import Image

# 加载图片
image = Image.open("input.jpg")

2. Get the pixel data of the image
   The image is composed of many pixels, and each pixel contains color information. We need to get the pixel data of the image in order to process it. The following is a code example for obtaining image pixel data:

# 获取图片的宽高
width, height = image.size

# 获取所有像素数据
pixels = image.load()

3. Perform color gradient processing on pixels
   For each pixel, we can achieve color gradient by modifying its RGB value. RGB values ​​represent the intensity of the three color channels of red, green, and blue. We can adjust the RGB values ​​as needed to achieve a color gradient effect. The following is a code example for color gradient processing of pixels:

# 定义起始颜色和结束颜色
start_color = (255, 0, 0)  # 红色
end_color = (0, 255, 0)  # 绿色

# 遍历所有像素
for x in range(width):
    for y in range(height):
        # 获取当前像素的RGB值
        current_color = pixels[x, y]

        # 计算渐变过程中的颜色
        red = int(start_color[0] + (end_color[0] - start_color[0]) * (x / width))
        green = int(start_color[1] + (end_color[1] - start_color[1]) * (x / width))
        blue = int(start_color[2] + (end_color[2] - start_color[2]) * (x / width))

        # 设置当前像素的颜色
        pixels[x, y] = (red, green, blue)

In the above code, we use linear interpolation method to calculate the color during the gradient process. The value of the red channel gradually decreases from the red value of the starting color, the value of the green channel gradually increases from the green value of the starting color, and the value of the blue channel remains unchanged. By continuously adjusting the RGB values, we can achieve a color gradient effect.

4. Save the processed image
   After color gradient processing, we need to save the processed image. The following is a code example for saving the processed image:

# 保存处理后的图片
image.save("output.jpg")

The complete code example is as follows:

from PIL import Image

# 加载图片
image = Image.open("input.jpg")

# 获取图片的宽高
width, height = image.size

# 获取所有像素数据
pixels = image.load()

# 定义起始颜色和结束颜色
start_color = (255, 0, 0)  # 红色
end_color = (0, 255, 0)  # 绿色

# 遍历所有像素
for x in range(width):
    for y in range(height):
        # 获取当前像素的RGB值
        current_color = pixels[x, y]

        # 计算渐变过程中的颜色
        red = int(start_color[0] + (end_color[0] - start_color[0]) * (x / width))
        green = int(start_color[1] + (end_color[1] - start_color[1]) * (x / width))
        blue = int(start_color[2] + (end_color[2] - start_color[2]) * (x / width))

        # 设置当前像素的颜色
        pixels[x, y] = (red, green, blue)

# 保存处理后的图片
image.save("output.jpg")

Summary:
This article introduces how to use Python to perform color gradient processing on images , and provides relevant code examples. By adjusting the color of each pixel, the color gradient effect of the image can be achieved. Readers can customize the starting color, ending color and gradient method according to their own needs to achieve different styles of color gradient effects.

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