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| """ | |
| :: | |
| Face averager | |
| Usage: | |
| averager.py --images=<images_folder> [--blur] [--plot] | |
| [--background=(black|transparent|average)] | |
| [--width=<width>] [--height=<height>] | |
| [--out=<filename>] [--destimg=<filename>] | |
| Options: | |
| -h, --help Show this screen. | |
| --images=<folder> Folder to images (.jpg, .jpeg, .png) | |
| --blur Flag to blur edges of image [default: False] | |
| --width=<width> Custom width of the images/video [default: 500] | |
| --height=<height> Custom height of the images/video [default: 600] | |
| --out=<filename> Filename to save the average face [default: result.png] | |
| --destimg=<filename> Destination face image to overlay average face | |
| --plot Flag to display the average face [default: False] | |
| --background=<bg> Background of image to be one of (black|transparent|average) [default: black] | |
| --version Show version. | |
| """ | |
| from docopt import docopt | |
| import os | |
| import cv2 | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| import matplotlib.image as mpimg | |
| from facemorpher import locator | |
| from facemorpher import aligner | |
| from facemorpher import warper | |
| from facemorpher import blender | |
| from facemorpher import plotter | |
| def list_imgpaths(imgfolder): | |
| for fname in os.listdir(imgfolder): | |
| if (fname.lower().endswith('.jpg') or | |
| fname.lower().endswith('.png') or | |
| fname.lower().endswith('.jpeg')): | |
| yield os.path.join(imgfolder, fname) | |
| def sharpen(img): | |
| blured = cv2.GaussianBlur(img, (0, 0), 2.5) | |
| return cv2.addWeighted(img, 1.4, blured, -0.4, 0) | |
| def load_image_points(path, size): | |
| img = cv2.imread(path) | |
| points = locator.face_points(img) | |
| if len(points) == 0: | |
| print('No face in %s' % path) | |
| return None, None | |
| else: | |
| return aligner.resize_align(img, points, size) | |
| def averager(imgpaths, dest_filename=None, width=500, height=600, background='black', | |
| blur_edges=False, out_filename='result.png', plot=False): | |
| size = (height, width) | |
| images = [] | |
| point_set = [] | |
| for path in imgpaths: | |
| img, points = load_image_points(path, size) | |
| if img is not None: | |
| images.append(img) | |
| point_set.append(points) | |
| if len(images) == 0: | |
| raise FileNotFoundError('Could not find any valid images.' + | |
| ' Supported formats are .jpg, .png, .jpeg') | |
| if dest_filename is not None: | |
| dest_img, dest_points = load_image_points(dest_filename, size) | |
| if dest_img is None or dest_points is None: | |
| raise Exception('No face or detected face points in dest img: ' + dest_filename) | |
| else: | |
| dest_img = np.zeros(images[0].shape, np.uint8) | |
| dest_points = locator.average_points(point_set) | |
| num_images = len(images) | |
| result_images = np.zeros(images[0].shape, np.float32) | |
| for i in range(num_images): | |
| result_images += warper.warp_image(images[i], point_set[i], | |
| dest_points, size, np.float32) | |
| result_image = np.uint8(result_images / num_images) | |
| face_indexes = np.nonzero(result_image) | |
| dest_img[face_indexes] = result_image[face_indexes] | |
| mask = blender.mask_from_points(size, dest_points) | |
| if blur_edges: | |
| blur_radius = 10 | |
| mask = cv2.blur(mask, (blur_radius, blur_radius)) | |
| if background in ('transparent', 'average'): | |
| dest_img = np.dstack((dest_img, mask)) | |
| if background == 'average': | |
| average_background = locator.average_points(images) | |
| dest_img = blender.overlay_image(dest_img, mask, average_background) | |
| print('Averaged {} images'.format(num_images)) | |
| plt = plotter.Plotter(plot, num_images=1, out_filename=out_filename) | |
| plt.save(dest_img) | |
| plt.plot_one(dest_img) | |
| plt.show() | |
| def main(): | |
| args = docopt(__doc__, version='Face Averager 1.0') | |
| try: | |
| averager(list_imgpaths(args['--images']), args['--destimg'], | |
| int(args['--width']), int(args['--height']), | |
| args['--background'], args['--blur'], args['--out'], args['--plot']) | |
| except Exception as e: | |
| print(e) | |
| if __name__ == "__main__": | |
| main() | |