python cv画检测框

在各类目标检测测试过程中，会对检测的结果进行可视化，将检测的结果画到图片上。以下是一个通用性实现。主要具备以下特性

1. 文字显示结果在各种分辨率图片上视觉显示效果一致

import xml.etree.ElementTree as ET
import os
from os import listdir, getcwd
from os.path import join
import shutil
import cv2 as cv

class BoxUtils():

    def __init__(self):
        #color define
        self.LIGHT_BLUE  = (0xED, 0x95, 0x64)
        self.GREEN  = (0x00, 0xFF, 0x00)
        self.RED = (0xFF, 0x00, 0x00)
        self.BLACK  = (0x00, 0x00, 0x00)

        #font size
        #定义文字像素值，像素值大小是相对于高度为base_SCREEN_HIGH的图片的。会根据实际图片的大小，将最终显示的文字
        #大小映射到对应base_SCREEN_HIGH上的像素值，以保证在不同分辨率的图片上文字显示大小是一致的。类似与android中的dp值的
        #设置
        self.base_FONT_SIZE  =36
        self.base_SCREEN_HIGH=1080
        self.LINE_WIDTH  = 1

    #根据图片高度，转化实际要显示的文字大小
    def get_draw_font_scale(self, pic_high):
        scal = float(self.base_FONT_SIZE) / self.base_SCREEN_HIGH
        realte_font_size =  int((pic_high * scal + 0.5))
        font_scale = float(realte_font_size)/self.base_FONT_SIZE
        return realte_font_size,font_scale


    def draw_detector_box1(self, image, detect_info, detected_rect, scalar):
        """
        args:
            image:
            detected_rect:[left, top, right, bottom], every value must be int
        """
        # print(detected_rect)
        cv.rectangle(image, (detected_rect[0],detected_rect[1]), (detected_rect[2],detected_rect[3]), scalar, self.LINE_WIDTH)
        rect_top = detected_rect[1]
        rect_left = detected_rect[0]
        
        font_size,font_scale = self.get_draw_font_scale(image.shape[0])
        # print(font_size, font_scale)，设置文字前后和上下间距
        offset_y = 1
        padding_x_scale = 0.5
        padding_x = int(font_size * font_scale * padding_x_scale)
        padding_y_scale = 0.1 
        padding_y = int(font_size * font_scale * padding_y_scale)

        if(len(detect_info)):
            thickness = 2
            text_size, baseline = cv.getTextSize(detect_info, cv.FONT_HERSHEY_SIMPLEX, font_scale, thickness)
            p1 = (detected_rect[0], detected_rect[1]- text_size[1])
            cv.rectangle(image, (p1[0] - 2//2, p1[1] - 2 - baseline-padding_y*2), (p1[0] + text_size[0] + padding_x*2, p1[1] + text_size[1]), self.RED, -1)
            cv.putText(image, detect_info, (p1[0]+padding_x, p1[1] + baseline+padding_y), cv.FONT_HERSHEY_SIMPLEX, font_scale, self.BLACK, 1, 8)

使用方法如下

img = cv.imread(r"./b.jpg")
img = cv.cvtColor(img, cv.COLOR_BGR2RGB)
detected_rect = [100,100,300, 300]
detect_info='class_name:0.89'
draw_image = img.copy()
draw_image = cv.GaussianBlur(draw_image,(21,21),0,0)
#使用方法如下
box_util = BoxUtils()
box_util.draw_detector_box1(draw_image, detect_info, detected_rect, box_util.RED)

# from PIL import Image
img_cv = Image.fromarray(draw_image)
img_cv
# from matplotlib import pyplot as plt
# plt.imshow(draw_image)
# cv.imwrite("ret.jpg", draw_image)

显示效果如下