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# USAGE | |
# python create_gif.py --config config.json --image images/me.jpg --output me.gif | |
# import the necessary packages | |
from imutils import face_utils | |
from imutils import paths | |
import numpy as np | |
import argparse | |
import imutils | |
import shutil | |
import json | |
import dlib | |
import cv2 | |
import sys | |
import os | |
def overlay_image(bg, fg, fgMask, coords): | |
(sH, sW) = fg.shape[:2] | |
(x, y) = coords | |
overlay = np.zeros(bg.shape, dtype="uint8") #黑色背景 | |
overlay[y:y + sH, x:x + sW] = fg | |
alpha = np.zeros(bg.shape[:2], dtype="uint8") | |
alpha[y:y + sH, x:x + sW] = fgMask | |
alpha = np.dstack([alpha] * 3) | |
output = alpha_blend(overlay, bg, alpha) | |
return output | |
def alpha_blend(fg, bg, alpha): | |
fg = fg.astype("float") | |
bg = bg.astype("float") | |
alpha = alpha.astype("float") / 255 | |
fg = cv2.multiply(alpha, fg) | |
bg = cv2.multiply(1 - alpha, bg) | |
output = cv2.add(fg, bg) | |
# return the output image | |
return output.astype("uint8") | |
def get_features(img_rd,*args): | |
# 输入: img_rd: 图像文件 | |
# 输出: pos_69to81: feature 69 to feature 81, 13 feature points in all, 40 points | |
detector1 = dlib.get_frontal_face_detector() | |
predictor1=dlib.shape_predictor("shape_predictor_81_face_landmarks.dat") | |
# read img file | |
img = cv2.imread(img_rd) | |
# 取灰度 | |
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) | |
# 计算 81 点坐标 | |
pos_81 = [] | |
rects = detector1(img_gray, 0) | |
landmarks = np.matrix([[p.x, p.y] for p in predictor1(img, rects[0]).parts()]) | |
for idx, point in enumerate(landmarks): | |
# 81点的坐标 | |
pos = (point[0, 0], point[0, 1]) | |
pos_81.append(pos) | |
get_pos=[] | |
get_pos.append((pos_81[args[0]][0],pos_81[args[0]][1])) | |
get_pos.append((pos_81[args[1]][0],pos_81[args[1]][1])) | |
return get_pos | |
def create_gif(inputPath, outputPath, delay, finalDelay, loop): | |
# grab all image paths in the input directory | |
imagePaths = sorted(list(paths.list_images(inputPath))) | |
# remove the last image path in the list | |
lastPath = imagePaths[-1] | |
imagePaths = imagePaths[:-1] | |
cmd = "convert -delay {} {} -delay {} {} -loop {} {}".format( | |
delay, " ".join(imagePaths), finalDelay, lastPath, loop, | |
outputPath) | |
os.system(cmd) | |
ap = argparse.ArgumentParser() | |
ap.add_argument("-c", "--config", required=True, | |
help="path to configuration file") | |
ap.add_argument("-i", "--image", required=True, | |
help="path to input image") | |
ap.add_argument("-o", "--output", required=True, | |
help="path to output GIF") | |
args = vars(ap.parse_args()) | |
config = json.loads(open(args["config"]).read()) | |
sg = cv2.imread(config["Crown"]) | |
sgMask = cv2.imread(config["Crown_mask"]) | |
shutil.rmtree(config["temp_dir"], ignore_errors=True) | |
os.makedirs(config["temp_dir"]) | |
print("[INFO] loading models...") | |
detector = cv2.dnn.readNetFromCaffe(config["face_detector_prototxt"], | |
config["face_detector_weights"]) | |
predictor = dlib.shape_predictor(config["landmark_predictor"]) | |
image = cv2.imread(args["image"]) | |
(H, W) = image.shape[:2] | |
blob = cv2.dnn.blobFromImage(cv2.resize(image, (300, 300)), 1.0, | |
(300, 300), (104.0, 177.0, 123.0)) | |
print("[INFO] computing object detections...") | |
detector.setInput(blob) | |
detections = detector.forward() | |
i = np.argmax(detections[0, 0, :, 2]) | |
confidence = detections[0, 0, i, 2] | |
if confidence < config["min_confidence"]: | |
print("[INFO] no reliable faces found") | |
sys.exit(0) | |
# compute the (x, y)-coordinates of the bounding box for the face | |
box = detections[0, 0, i, 3:7] * np.array([W, H, W, H]) | |
(startX, startY, endX, endY) = box.astype("int") | |
rect = dlib.rectangle(int(startX), int(startY), int(endX), int(endY)) | |
shape = predictor(image, rect) | |
shape = face_utils.shape_to_np(shape) | |
forehead=get_features(args["image"],76,73) | |
left_point=forehead[0] | |
right_point=forehead[1] | |
dY=left_point[1]-right_point[1] | |
dX=left_point[0]-right_point[0] | |
print("left_point:"+str(left_point[1])) | |
angle = np.degrees(np.arctan2(dY, dX)) - 180 | |
# rotate the sunglasses image by our computed angle, ensuring the | |
# sunglasses will align with how the head is tilted | |
sg = imutils.rotate_bound(sg, angle) | |
# sgW = int((shape[16].astype(int)[0] - shape[0].astype(int)[0])*1.40) | |
sgW=int((endX-startX)*1.2) | |
sg = imutils.resize(sg, width=sgW) | |
print("sgw"+str(shape[16])) | |
sgMask = cv2.cvtColor(sgMask, cv2.COLOR_BGR2GRAY) | |
sgMask = cv2.threshold(sgMask, 0, 255, cv2.THRESH_BINARY)[1] | |
sgMask = imutils.rotate_bound(sgMask, angle) | |
sgMask = imutils.resize(sgMask, width=sgW, inter=cv2.INTER_NEAREST) | |
steps = np.linspace(0, left_point[1], config["steps"], | |
dtype="int") | |
# start looping over the steps | |
for (i, y) in enumerate(steps): | |
shiftX = int(sg.shape[1] * 0.18) | |
shiftY = int(sg.shape[0]*0.80) | |
y = max(0, y-shiftY) | |
# add the sunglasses to the image | |
output = overlay_image(image, sg, sgMask, | |
(left_point[0]-shiftX, y)) | |
if i == len(steps) - 1: | |
dwi = cv2.imread(config["birthday"]) | |
dwiMask = cv2.imread(config["birthday_mask"]) | |
dwiMask = cv2.cvtColor(dwiMask, cv2.COLOR_BGR2GRAY) | |
dwiMask = cv2.threshold(dwiMask, 0, 255, | |
cv2.THRESH_BINARY)[1] | |
# resize both the text image and mask to be 80% the width of | |
# the output image | |
oW = int(W * 0.8) | |
dwi = imutils.resize(dwi, width=oW) | |
dwiMask = imutils.resize(dwiMask, width=oW, | |
inter=cv2.INTER_NEAREST) | |
# compute the coordinates of where the text will go on the | |
# output image and then add the text to the image | |
oX = int(W * 0.1) | |
oY = int(H * 0.7) | |
output = overlay_image(output, dwi, dwiMask, (oX, oY)) | |
# write the output image to our temporary directory | |
p = os.path.sep.join([config["temp_dir"], "{}.jpg".format( | |
str(i).zfill(8))]) | |
cv2.imwrite(p, output) | |
print("[INFO] creating GIF...") | |
create_gif(config["temp_dir"], args["output"], config["delay"], | |
config["final_delay"], config["loop"]) | |
# cleanup by deleting our temporary directory | |
print("[INFO] cleaning up...") | |
shutil.rmtree(config["temp_dir"], ignore_errors=True) | |