python 解决OpenCV显示中文字符的方法汇总
作者:何时摆脱命运的束缚
因工作需要,要在图片中显示中文字符,并且要求速度足够快,在网上搜罗一番后,总结下几个解决方法,对python 解决OpenCV显示中文字符相关知识感兴趣的朋友一起看看吧
因工作需要,要在图片中显示中文字符,并且要求速度足够快,在网上搜罗一番后,总结下几个解决方法。
1.方法一:转PIL后使用PIL相关函数添加中文字符
from PIL import Image, ImageDraw, ImageFont import cv2 import numpy as np # cv2读取图片,名称不能有汉字 img = cv2.imread('pic1.jpeg') # cv2和PIL中颜色的hex码的储存顺序不同 cv2img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) pilimg = Image.fromarray(cv2img) # PIL图片上打印汉字 draw = ImageDraw.Draw(pilimg) # 图片上打印 #simsun 宋体 font = ImageFont.truetype("simsun.ttf", 40, encoding="utf-8") #位置,文字,颜色==红色,字体引入 draw.text((20, 20), "你好", (255, 0, 0), font=font) # PIL图片转cv2 图片 cv2charimg = cv2.cvtColor(np.array(pilimg), cv2.COLOR_RGB2BGR) cv2.imshow("img", cv2charimg) cv2.waitKey (0) cv2.destroyAllWindows()
存在的缺点:cv2->pil 中 Image.fromarray(img)存在耗时4~5ms
2.方法二:opencv重新编译带freetype
编译过程略。
import cv2 import numpy as np # 创建一个黑色的图像 img = np.zeros((300, 500, 3), dtype=np.uint8) # 中文文本 text = '你好,OpenCV!' # 设置字体相关参数 font_path = 'path/to/your/chinese/font.ttf' # 替换为你的中文字体文件路径 font_size = 24 font_color = (255, 255, 255) thickness = 2 # 使用 truetype 字体加载中文字体 font = cv2.freetype.createFreeType2() font.loadFontData(font_path) # 在图像上放置中文文本 position = (50, 150) font.putText(img, text, position, font_size, font_color, thickness=thickness) # 显示图像 cv2.imshow('Image with Chinese Text', img) cv2.waitKey(0) cv2.destroyAllWindows()
缺点:编译过程复杂繁琐,容易报一些列的错误,编译时确保已安装第三方库freetype和harfbuzz,并且配置编译参数时需打开freetype。
3.方法三:使用freetype-py
pip install freetype-py
ft.py
import numpy as np import freetype import copy import pdb import time class PutChineseText(object): def __init__(self, ttf, text_size): self._face = freetype.Face(ttf) hscale = 1.0 self.matrix = freetype.Matrix(int(hscale)*0x10000, int(0.2*0x10000),int(0.0*0x10000), int(1.1*0x10000)) self.cur_pen = freetype.Vector() self.pen_translate = freetype.Vector() self._face.set_transform(self.matrix, self.pen_translate) self._face.set_char_size(text_size * 64) metrics = self._face.size ascender = metrics.ascender/64.0 #descender = metrics.descender/64.0 #height = metrics.height/64.0 #linegap = height - ascender + descender self.ypos = int(ascender) self.pen = freetype.Vector() def draw_text(self, image, pos, text, text_color): ''' draw chinese(or not) text with ttf :param image: image(numpy.ndarray) to draw text :param pos: where to draw text :param text: the context, for chinese should be unicode type :param text_size: text size :param text_color:text color :return: image ''' # if not isinstance(text, unicode): # text = text.decode('utf-8') img = self.draw_string(image, pos[0], pos[1]+self.ypos, text, text_color) return img def draw_string(self, img, x_pos, y_pos, text, color): ''' draw string :param x_pos: text x-postion on img :param y_pos: text y-postion on img :param text: text (unicode) :param color: text color :return: image ''' prev_char = 0 self.pen.x = x_pos << 6 # div 64 self.pen.y = y_pos << 6 image = copy.deepcopy(img) for cur_char in text: self._face.load_char(cur_char) # kerning = self._face.get_kerning(prev_char, cur_char) # pen.x += kerning.x slot = self._face.glyph bitmap = slot.bitmap self.pen.x += 0 self.cur_pen.x = self.pen.x self.cur_pen.y = self.pen.y - slot.bitmap_top * 64 self.draw_ft_bitmap(image, bitmap, self.cur_pen, color) self.pen.x += slot.advance.x prev_char = cur_char return image def draw_ft_bitmap(self, img, bitmap, pen, color): ''' draw each char :param bitmap: bitmap :param pen: pen :param color: pen color e.g.(0,0,255) - red :return: image ''' x_pos = pen.x >> 6 y_pos = pen.y >> 6 cols = bitmap.width rows = bitmap.rows glyph_pixels = bitmap.buffer for row in range(rows): for col in range(cols): if glyph_pixels[row*cols + col] != 0: img[y_pos + row][x_pos + col][0] = color[0] img[y_pos + row][x_pos + col][1] = color[1] img[y_pos + row][x_pos + col][2] = color[2] if __name__ == '__main__': # just for test import cv2 line = '你好' img = np.zeros([300,300,3]) color_ = (0,255,0) # Green pos = (40, 40) text_size = 24 ft = PutChineseText('font/simsun.ttc',text_size=20) t1 = time.time() image = ft.draw_text(img, pos, line, color_) print(f'draw load . ({time.time() - t1:.3f}s)') cv2.imshow('ss', image) cv2.waitKey(0)
缺点:每个字符耗时在0.3~1ms左右,耗时略大。
4.方法四:使用OpenCV5.0
4.1 编译opencv5.x版本
编译过程较复杂,不推荐。
4.2 使用rolling版本
卸载原先安装的opencv
pip uninstall opencv-python pip uninstall opencv-contrib-python
安装rolling版本
pip install opencv-python-rolling pip install opencv-contrib-python-rolling
安装完毕后,cv2.putText即可支持中文字符。
缺点:5.0版本暂未正式发布,可能存在不稳定情况
优点:耗时几乎没有
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