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未曾验证：（据说只适合python 2）
https://www.cnblogs.com/datou-swag/articles/10671842.html
http://www.voidcn.com/article/p-hmuycojw-bms.html
http://www.voidcn.com/article/p-uewkhlef-bbc.html
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OpenCV 的 cv2.putText 方法中无法放置中文。
但是PIL 的 Image.Draw 的方法中有 draw.text 的方法是可以设置中文字体的。simsum.ttc 宋体。
OpenCV 读出的图像是np.ndarray 的图像格式。
PIL 读出的图像格式与上述有所不同。所以当图像从cv2 转到 PIL 操作时，两者的图像格式需要做一些变化。
#!/usr/bin/env python # !_*_ coding:utf-8 _*_ import face_recognition import cv2 import numpy as np from PIL import Image, ImageDraw, ImageFont def cv2ImgAddText(img, text, left, top, textColor=(0, 255, 0), textSize=20): if (isinstance(img, np.ndarray)): pil_img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB)) draw = ImageDraw.Draw(pil_img) # 字体默认在 C:WindowsFonts 下面，要鼠标右键查看属性 # fontStyle = ImageFont.truetype('simsun.ttc', textSize, encoding='utf-8') fontStyle = ImageFont.truetype('msyh.ttc', textSize, encoding='utf-8') draw.text((left, top), text, textColor, font=fontStyle) return cv2.cvtColor(np.asarray(pil_img), cv2.COLOR_RGB2BGR) face_image = face_recognition.load_image_file('imgs/qsz001.jpg') # face_recognition.load_image_file 读出的文件是RGB,而后面需要在cv2 上画框，cv2是BGR 的np.ndarray的数组文件 face_image = cv2.cvtColor(face_image, cv2.COLOR_RGB2BGR) face_locations = face_recognition.face_locations(face_image) for face_location in face_locations: print(face_location) top, right, bottom, left = face_location cv2.rectangle(face_image, (left, top), (right, bottom), (0, 255, 0), 2) face_image = cv2ImgAddText(face_image, "邱淑贞", left, bottom + 5, (255, 0, 0), 20) cv2.imshow("image", face_image) cv2.waitKey(0) cv2.destroyAllWindows()
注意 字体的路径：
字体默认在 C:WindowsFonts 下面，要鼠标右键查看属性
下面代码是经过测试的，能够正常运行。
#!/usr/bin/env python # !_*_ coding:utf-8 _*_ import numpy as np import freetype import copy import pdb """ ################################################## # tools # #------------------------------------------------# # draw chinese text using freetype on python3.7 # # 2020-04-12 # ################################################## https://www.pythonheidong.com/blog/article/327766/a72be84affd143fcc7f1/ """ class put_chinese_text(object): def __init__(self, ttf): self._face = freetype.Face(ttf) def draw_text(self, image, pos, text, text_size, 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 ''' 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 ypos = int(ascender) # if not isinstance(text, unicode): # text = text.decode('utf-8') img = self.draw_string(image, pos[0], pos[1] + 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 pen = freetype.Vector() pen.x = x_pos << 6 # div 64 pen.y = y_pos << 6 hscale = 1.0 matrix = freetype.Matrix(int(hscale) * 0x10000, int(0.2 * 0x10000), int(0.0 * 0x10000), int(1.1 * 0x10000)) cur_pen = freetype.Vector() pen_translate = freetype.Vector() image = copy.deepcopy(img) for cur_char in text: self._face.set_transform(matrix, pen_translate) 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 cur_pen.x = pen.x cur_pen.y = pen.y - slot.bitmap_top * 64 self.draw_ft_bitmap(image, bitmap, cur_pen, color) 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 = '美美的' # img = np.zeros([300,300,3]) img = cv2.imread('imgs/qsz001.jpg', cv2.IMREAD_COLOR) color_ = (0, 0, 255) # Green pos = (30, 30) text_size = 50 # ft = put_chinese_text('wqy-zenhei.ttc') ft = put_chinese_text('C:/Windows/Fonts/simkai.ttf') image = ft.draw_text(img, pos, line, text_size, color_) cv2.imshow('freetype', image) cv2.waitKey(0) cv2.destroyAllWindows()
My Code
#!/usr/bin/env python # !_*_ coding:utf-8 _*_ import cv2 import face_recognition import numpy as np from PIL import Image, ImageFont, ImageDraw import os def load_image(path): """ 读取已知的文件库，把所有人的 encodings 作为一个文件库，后续视频中的头像来与他做比较。 os.walk() 与 os.listdir() 都可以得到文件的filenames。 :param path: :return: """ for root, dirnames, filenames in os.walk(path): # print(root, dirnames, filenames) print("正在加载已知人员的图片信息......") facelib_encodings = [] for filename in filenames: file_path = os.path.join(root, filename) # print(file_path) face_image = face_recognition.load_image_file(file_path) # 因为文件库中的头像均是单人照，所以取索引【0】 facelib_encoding = face_recognition.face_encodings(face_image)[0] facelib_encodings.append(facelib_encoding) return facelib_encodings, filenames def cv2ImgAddText(img, text, left, top, textcolor, textsize=20): if (isinstance(img, np.ndarray)): pil_img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB)) draw = ImageDraw.Draw(pil_img) # 字体默认在 C:WindowsFonts 下面，要鼠标右键查看属性 # fontStyle = ImageFont.truetype('simsun.ttc', textSize, encoding='utf-8') fontStyle = ImageFont.truetype('simsun.ttc', textsize, encoding='utf-8') draw.text((left, top), text, textcolor, font=fontStyle) # 因为后面还需要调用cv2.imshow的函数，所以要把pil_img 转化的cv2的领域 RGB---->BGR cv2_image = cv2.cvtColor(np.asarray(pil_img), cv2.COLOR_RGB2BGR) return cv2_image # def cv2ImgAddText(img, text, left, top, textColor=(0, 255, 0), textSize=20): # if (isinstance(img, np.ndarray)): # pil_img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB)) # draw = ImageDraw.Draw(pil_img) # # 字体默认在 C:WindowsFonts 下面，要鼠标右键查看属性 # # fontStyle = ImageFont.truetype('simsun.ttc', textSize, encoding='utf-8') # fontStyle = ImageFont.truetype('msyh.ttc', textSize, encoding='utf-8') # draw.text((left, top), text, textColor, font=fontStyle) # return cv2.cvtColor(np.asarray(pil_img), cv2.COLOR_RGB2BGR) face_lib, filenames = load_image('facelib') # 下面摄像头开始抓取图片 capture = cv2.VideoCapture(0, cv2.CAP_DSHOW) while True: ret, frame = capture.read() # flip函数是使图像做镜像，由后面的参数决定 0：垂直翻转； 1：水平翻转； -1：水平，垂直均翻转 # frame = cv2.flip(frame, 1) # 把图像缩小至1/4，以便于后续分析，但是后续得到的坐标需要 *4 才是frame上真实的坐标 small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25) face_locations = face_recognition.face_locations(small_frame) face_encodings = face_recognition.face_encodings(small_frame, face_locations) names = [] # 上述得到的face_encodings,可能是单个人像，也有可能是多人的图像（摄像头中可能由多个人） for face_encoding in face_encodings: name = "未知人像" matches = face_recognition.compare_faces(face_lib, face_encoding, tolerance=0.5) # 如果有人匹配，要找出匹配的索引，以便于找到相应的 filename，然后取其姓名。 for item in matches: if item == True: index_num = matches.index(True) name = filenames[index_num].split(".")[0] names.append(name) print(names) for face_location, name in zip(face_locations, names): top, right, bottom, left = face_location top *= 4 right *= 4 bottom *= 4 left *= 4 # 利用cv2画矩形框 cv2.rectangle(frame, (left, top), (right, bottom), (0, 255, 0), 2) # print(name) # 利用PIL 写汉字 frame = cv2ImgAddText(frame, name, left, bottom + 5, (255, 255, 255), 25) cv2.imshow("video", frame) key = cv2.waitKey(50) if key & 0xFF == ord('q'): break cv2.destroyAllWindows() capture.release()