Python 如何检测背景有噪的图像中的正方形

我们可以在这里采取两种全球方法:自始至终使用计算机视觉(可能不准确)，或者使用变通方法(更简单的方法).后者似乎更好.因此，首先，我们必须裁剪原始图像，以留下仅具有幼苗地块网格的图像.这可以使用任何简单的图像处理工具(即，在Mac上预览或在Windows上绘制):

很好，现在，我们必须识别不同的方块.如果我们注意到的话，我们有一个由偶数正方形组成的10x6网格，所以我们可以如下使用matplotlib:

import matplotlib.pyplot as plt
import matplotlib.patches as patches

def draw_seedling_squares(image_path, grid_size=(10, 6)):
    # Load the image
    img = plt.imread(image_path)
    
    # Create a new figure
    fig, ax = plt.subplots()
    ax.imshow(img)
    
    # Calculate the width and height of each square
    img_height, img_width, _ = img.shape
    square_width = img_width / grid_size[0]
    square_height = img_height / grid_size[1]
    
    # Draw squares above each seedling plot
    for i in range(grid_size[0]):
        for j in range(grid_size[1]):
            x = i * square_width
            y = j * square_height
            rect = patches.Rectangle((x, y), square_width, square_height, linewidth=1, edgecolor='r', facecolor='none')
            ax.add_patch(rect)
    
    # Show the image with squares
    plt.show()

draw_seedling_squares('cropped_image.jpeg')

这会产生:

非常准确！现在我们还剩一项任务:例如，将每个幼苗地块保存在名为screenshots的文件夹中.为此，我们可以对上面的代码进行以下修改:

import os
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as patches

def extract_and_save_seedling_plots(image_path, output_folder='screenshots', grid_size=(10, 6)):
    # Create the output folder if it doesn't exist
    if not os.path.exists(output_folder):
        os.makedirs(output_folder)
    
    # Load the image
    img = plt.imread(image_path)
    
    # Calculate the width and height of each seedling plot
    img_height, img_width, _ = img.shape
    plot_width = img_width / grid_size[0]
    plot_height = img_height / grid_size[1]
    
    # Extract and save each seedling plot as individual files
    for i in range(grid_size[0]):
        for j in range(grid_size[1]):
            x = i * plot_width
            y = j * plot_height
            
            # Define the bounding box for cropping
            bbox = (int(x), int(y), int(x + plot_width), int(y + plot_height))
            
            # Crop the seedling plot
            seedling_plot = img[bbox[1]:bbox[3], bbox[0]:bbox[2]]
            
            # Save the cropped seedling plot as an individual file
            filename = os.path.join(output_folder, f'seedling_plot_{i}_{j}.png')
            plt.imsave(filename, seedling_plot)

extract_and_save_seedling_plots('cropped_image.jpeg')

太好了！现在我们有了一个文件夹，其中包含60张裁剪图像，如下所示，对应于第一行:

希望这有帮助！愿密码与你同在……