当前位置：首页 > news >正文

图像中部分RGB矩阵可视化

news 2025/8/5 1:10:14

图像中部分RGB可视化

今天室友有个需求就是模仿下面这张图画个示意图：

在这里插入图片描述

大致就是把图像中的一小部分区域的RGB值可视化了一下。他居然不知道该怎么画，我寻思这不直接秒了。

import cv2 as cv
import numpy as np
import matplotlib.pyplot as pltclass Plotter:def __init__(self, img):self.img = imgself.range = None# 三个图的位置self.loc = [[0.01, 0.325, 0.35, 0.35],[0.375, 0.375, 0.25, 0.25],[0.71, 0.355, 0.29, 0.29],]self.dloc = [0.02, 0.02]  # 表格间距self.facecolor = plt.get_cmap("Accent")(range(3))  # 表格颜色def plot_img(self, fig):img_range = self.rangeaxes = fig.add_axes(self.loc[0])axes.imshow(self.img, aspect="auto")axes.add_patch(plt.Rectangle((img_range[0], img_range[2]),img_range[1] - img_range[0],img_range[3] - img_range[2],fill=False,edgecolor="red",linewidth=2,))axes.axis("off")def plot_table(self, fig, table):loc = self.loc[2]dloc = self.dlocfacecolor = self.facecolorfor i in range(table.shape[2]):axes = fig.add_axes([loc[0] - dloc[0] * i, loc[1] - dloc[1] * i, loc[2], loc[3]],)axes.table(cellText=table[:, :, i],loc="center",cellColours=np.full((table.shape[0], table.shape[1], 4),facecolor[i],dtype=self.facecolor[0].dtype,),bbox=[0, 0, 1, 1],)axes.axis("off")def plot_range_img(self, fig, range_img):axes = fig.add_axes(self.loc[1])axes.imshow(range_img, aspect="auto")axes.set_xticks([])axes.set_yticks([])spines = ["left", "right", "bottom", "top"]for spine in spines:axes.spines[spine].set_color("r")def plot_path(self, axes, x1, x2):x = np.linspace(x1[0], x2[0], 100)y = np.linspace(x1[1], x2[1], 100)axes.set_xlim(0, 1)axes.set_ylim(0, 1)axes.plot(x, y, "r--")def range_points_on_img(self):img_range = self.rangeloc = self.loc[0]luloc = loc[0] + img_range[0] / self.img.shape[0] * loc[2]# axes坐标系y轴方向相反ldloc = loc[1] + (self.img.shape[1] - img_range[2]) / self.img.shape[1] * loc[3]dx = (img_range[1] - img_range[0]) / self.img.shape[0] * loc[2]dy = (img_range[3] - img_range[2]) / self.img.shape[1] * loc[3]return [(luloc + dx, ldloc - dy), (luloc + dx, ldloc)]def plot_img2range(self, axes):img_points = self.range_points_on_img()range_points = [(self.loc[1][0], self.loc[1][1]),(self.loc[1][0], self.loc[1][1] + self.loc[1][3]),]print(img_points)self.plot_path(axes, img_points[0], range_points[0])self.plot_path(axes, img_points[1], range_points[1])def plot_range2table(self, axes):range_points = [(self.loc[1][0] + self.loc[1][2], self.loc[1][1]),(self.loc[1][0] + self.loc[1][2], self.loc[1][1] + self.loc[1][3]),]table_points = [(self.loc[2][0] - self.dloc[0] * 2, self.loc[2][1] - self.dloc[1] * 2),(self.loc[2][0] - self.dloc[0] * 2,self.loc[2][1] + self.loc[2][3] - self.dloc[1] * 2,),]self.plot_path(axes, range_points[0], table_points[0])self.plot_path(axes, range_points[1], table_points[1])def plot_line(self, fig):axes = fig.add_axes([0, 0, 1, 1])self.plot_img2range(axes)self.plot_range2table(axes)axes.axis("off")def plot(self, img_range):self.range = img_rangerange_img = self.img[img_range[0] : img_range[1], img_range[2] : img_range[3], :]fig = plt.figure()self.plot_img(fig)self.plot_range_img(fig, range_img)self.plot_table(fig, range_img)self.plot_line(fig)plt.show()if __name__ == "__main__":img_path = "lena_color_512.tif"img = cv.imread(img_path, cv.IMREAD_UNCHANGED)img = cv.cvtColor(img, cv.COLOR_BGR2RGB)p = Plotter(img)p.plot([255, 265, 255, 265])