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转自：github地址：https://github.com/tomoncle/face-detection-induction-course 目录 简介 摄像头实时运行 图片生成gif动图 简介在github看到的一个搞笑的小程序分享给大家，github地址：https://github.com/tomoncle/face-detection-induction-course 效果如下：
代码如下： 其中的人脸识别数据可以在此下载：https://jaist.dl.sourceforge.net/project/dclib/dlib/v18.10/shape_predictor_68_face_landmarks.dat.bz2 解压后与程序放在同一文件夹下即可。 程序运行后按q退出，按d加墨镜。 #!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2019/3/16 10:10 # @Author : tomoncle # @Site : https://github.com/tomoncle/face-detection-induction-course # @File : input_video_stream_paste_mask.py # @Software: PyCharm import cv2 import numpy as np from PIL import Image from imutils import face_utils, resize from time import sleep try: from dlib import get_frontal_face_detector, shape_predictor except ImportError: raise class DynamicStreamMaskService(object): """ 动态黏贴面具服务 """ def __init__(self, saved=False): self.saved = saved # 是否保存图片 self.listener = True # 启动参数 self.video_capture = cv2.VideoCapture(0) # 调用本地摄像头 self.doing = False # 是否进行面部面具 self.speed = 0.4 # 面具移动速度 self.detector = get_frontal_face_detector() # 面部识别器 self.predictor = shape_predictor("shape_predictor_68_face_landmarks.dat") # 面部分析器 self.fps = 4 # 面具存在时间基础时间 self.animation_time = 0 # 动画周期初始值 self.duration = self.fps * 4 # 动画周期最大值 self.fixed_time = 4 # 画图之后，停留时间 self.max_width = 500 # 图像大小 self.deal, self.text, self.cigarette = None, None, None # 面具对象 def read_data(self): """ 从摄像头获取视频流，并转换为一帧一帧的图像 :return: 返回一帧一帧的图像信息 """ _, data = self.video_capture.read() return data def save_data(self, draw_img): """ 保存图片到本地 :param draw_img: :return: """ if not self.saved: return draw_img.save("images\\%05d.png" % self.animation_time) def init_mask(self): """ 加载面具 :return: """ self.console("加载面具...") self.deal, self.text, self.cigarette = ( Image.open(x) for x in ["images\\deals.png", "images\\text.png", "images\\cigarette.png"] ) def get_glasses_info(self, face_shape, face_width): """ 获取当前面部的眼镜信息 :param face_shape: :param face_width: :return: """ left_eye = face_shape[36:42] right_eye = face_shape[42:48] left_eye_center = left_eye.mean(axis=0).astype("int") right_eye_center = right_eye.mean(axis=0).astype("int") y = left_eye_center[1] - right_eye_center[1] x = left_eye_center[0] - right_eye_center[0] eye_angle = np.rad2deg(np.arctan2(y, x)) deal = self.deal.resize( (face_width, int(face_width * self.deal.size[1] / self.deal.size[0])), resample=Image.LANCZOS) deal = deal.rotate(eye_angle, expand=True) deal = deal.transpose(Image.FLIP_TOP_BOTTOM) left_eye_x = left_eye[0, 0] - face_width // 4 left_eye_y = left_eye[0, 1] - face_width // 6 return {"image": deal, "pos": (left_eye_x, left_eye_y)} def get_cigarette_info(self, face_shape, face_width): """ 获取当前面部的烟卷信息 :param face_shape: :param face_width: :return: """ mouth = face_shape[49:68] mouth_center = mouth.mean(axis=0).astype("int") cigarette = self.cigarette.resize( (face_width, int(face_width * self.cigarette.size[1] / self.cigarette.size[0])), resample=Image.LANCZOS) x = mouth[0, 0] - face_width + int(16 * face_width / self.cigarette.size[0]) y = mouth_center[1] return {"image": cigarette, "pos": (x, y)} def orientation(self, rects, img_gray): """ 人脸定位 :return: """ faces = [] for rect in rects: face = {} face_shades_width = rect.right() - rect.left() predictor_shape = self.predictor(img_gray, rect) face_shape = face_utils.shape_to_np(predictor_shape) face['cigarette'] = self.get_cigarette_info(face_shape, face_shades_width) face['glasses'] = self.get_glasses_info(face_shape, face_shades_width) faces.append(face) return faces def start(self): """ 启动程序 :return: """ self.console("程序启动成功.") self.init_mask() while self.listener: frame = self.read_data() frame = resize(frame, width=self.max_width) img_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) rects = self.detector(img_gray, 0) faces = self.orientation(rects, img_gray) draw_img = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)) if self.doing: self.drawing(draw_img, faces) self.animation_time += self.speed self.save_data(draw_img) if self.animation_time > self.duration: self.doing = False self.animation_time = 0 else: frame = cv2.cvtColor(np.asarray(draw_img), cv2.COLOR_RGB2BGR) cv2.imshow("hello mask", frame) self.listener_keys() def listener_keys(self): """ 设置键盘监听事件 :return: """ key = cv2.waitKey(1) & 0xFF if key == ord("q"): self.listener = False self.console("程序退出") sleep(1) self.exit() if key == ord("d"): self.doing = not self.doing def exit(self): """ 程序退出 :return: """ self.video_capture.release() cv2.destroyAllWindows() def drawing(self, draw_img, faces): """ 画图 :param draw_img: :param faces: :return: """ for face in faces: if self.animation_time < self.duration - self.fixed_time: current_x = int(face["glasses"]["pos"][0]) current_y = int(face["glasses"]["pos"][1] * self.animation_time / (self.duration - self.fixed_time)) draw_img.paste(face["glasses"]["image"], (current_x, current_y), face["glasses"]["image"]) cigarette_x = int(face["cigarette"]["pos"][0]) cigarette_y = int(face["cigarette"]["pos"][1] * self.animation_time / (self.duration - self.fixed_time)) draw_img.paste(face["cigarette"]["image"], (cigarette_x, cigarette_y), face["cigarette"]["image"]) else: draw_img.paste(face["glasses"]["image"], face["glasses"]["pos"], face["glasses"]["image"]) draw_img.paste(face["cigarette"]["image"], face["cigarette"]["pos"], face["cigarette"]["image"]) draw_img.paste(self.text, (75, draw_img.height // 2 + 128), self.text) @classmethod def console(cls, s): print("{} !".format(s)) if __name__ == '__main__': ms = DynamicStreamMaskService() ms.start() 图片生成gif动图 #!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2019/3/13 14:47 # @Author : tomoncle # @Site : https://github.com/tomoncle/face-detection-induction-course # @File : input_static_pic_to_gif2.py # 参考信息：https://www.makeartwithpython.com/blog/deal-with-it-generator-face-recognition/ # 描述： # 程序从命令行参数获取图片信息，然后，它将使用Dlib中的人脸检测算法来查看是否有人脸存在。 # 如果有，它将为每个人脸创建一个结束位置，眼镜和烟卷会移动到那里结束。 # # 然后我们需要缩放和旋转我们的眼镜以适合每个人的脸。 # 我们将使用从Dlib的68点模型返回的点集来找到眼睛的中心，并为它们之间的空间旋转。 # # 在我们找到眼镜的最终位置和旋转后，我们可以为gif制作动画，眼镜从屏幕顶部进入。 # 我们将使用MoviePy和一个自定义的FaceDetect工具类绘制它。 # # 同理烟卷也是这样。 # # 应用程序的体系结构非常简单。我们首先接收图片，然后将其转换为灰度NumPy数组。 # 假如没有人脸，程序会自己退出，如果存在，我们就可以将检测到的人脸信息传递到人脸方向预测模型中。 # # 通过返回的脸部方向，我们可以选择眼睛，缩放和旋转我们的眼镜框架以适合人的面部大小。 # # 当然这个程序不仅仅只针对于一张人脸，可以检测多个人脸信息。 # # 最后，通过获取的人脸列表，我们可以使用MoviePy创建一个绘图，然后生成我们的动画gif。 import moviepy.editor as mpy import numpy as np from PIL import Image from imutils import face_utils try: from dlib import get_frontal_face_detector, shape_predictor except ImportError: raise class FaceDetect(object): def __init__(self, img_src, gif_path=None): self.gif_max_width = 500 self.duration = 4 self.image = self.load(img_src).convert('RGBA') self.img_gray = None self.rects = None self.deal = None self.text = None self.cigarette = None if not self.validate: print("没有检测到人脸，程序退出.") exit(1) self.init_mask() self.make_gif(gif_path=gif_path) @property def validate(self): """ 验证是否存在人脸，如果不存在返回False :return: """ if self.image.size[0] > self.gif_max_width: scaled_height = int(self.gif_max_width * self.image.size[1] / self.image.size[0]) self.image.thumbnail((self.gif_max_width, scaled_height)) self.img_gray = np.array(self.image.convert('L')) self.rects = self.detector(self.img_gray, 0) return len(self.rects) > 0 @classmethod def load(cls, img_src): """ 加载图片转为Image对象 :param img_src: :return: """ return Image.open(img_src) @property def detector(self): """ 检测是否有人脸 :return: """ return get_frontal_face_detector() @property def predictor(self): """ 预测我们的面部方向 :return: """ return shape_predictor('shape_predictor_68_face_landmarks.dat') def init_mask(self): """ 加载面具 :return: """ self.deal, self.text, self.cigarette = ( self.load(x) for x in ["images\\deals.png", "images\\text.png", "images\\cigarette.png"] ) def get_glasses_info(self, face_shape, face_width): """ 获取当前面部的眼镜信息 :param face_shape: :param face_width: :return: """ left_eye = face_shape[36:42] right_eye = face_shape[42:48] left_eye_center = left_eye.mean(axis=0).astype("int") right_eye_center = right_eye.mean(axis=0).astype("int") y = left_eye_center[1] - right_eye_center[1] x = left_eye_center[0] - right_eye_center[0] eye_angle = np.rad2deg(np.arctan2(y, x)) deal = self.deal.resize( (face_width, int(face_width * self.deal.size[1] / self.deal.size[0])), resample=Image.LANCZOS) deal = deal.rotate(eye_angle, expand=True) deal = deal.transpose(Image.FLIP_TOP_BOTTOM) left_eye_x = left_eye[0, 0] - face_width // 4 left_eye_y = left_eye[0, 1] - face_width // 6 return {"image": deal, "pos": (left_eye_x, left_eye_y)} def get_cigarette_info(self, face_shape, face_width): """ 获取当前面部的烟卷信息 :param face_shape: :param face_width: :return: """ mouth = face_shape[49:68] mouth_center = mouth.mean(axis=0).astype("int") cigarette = self.cigarette.resize( (face_width, int(face_width * self.cigarette.size[1] / self.cigarette.size[0])), resample=Image.LANCZOS) x = mouth[0, 0] - face_width + int(16 * face_width / self.cigarette.size[0]) y = mouth_center[1] return {"image": cigarette, "pos": (x, y)} def orientation(self): """ 人脸定位 :return: """ faces = [] for rect in self.rects: face = {} face_shades_width = rect.right() - rect.left() predictor_shape = self.predictor(self.img_gray, rect) face_shape = face_utils.shape_to_np(predictor_shape) face['cigarette'] = self.get_cigarette_info(face_shape, face_shades_width) face['glasses'] = self.get_glasses_info(face_shape, face_shades_width) faces.append(face) return faces def drawing(self, t): """ 动态画图 :param t: :return: """ draw_img = self.image.convert('RGBA') if t == 0: return np.asarray(draw_img) for face in self.orientation(): if t |
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