import cv2 as cv
import numpy as np
model_bin = "D:/projects/opencv_tutorial/data/models/face_detector/opencv_face_detector_uint8.pb";
config_text = "D:/projects/opencv_tutorial/data/models/face_detector/opencv_face_detector.pbtxt";


def get_face(image, detect=True):
 if detect is not True:
 return image

 # 定义人脸ROI
 x = 0
 y = 0
 width = 0
 height = 0

 # 加载网络
 net = cv.dnn.readNetFromTensorflow(model_bin, config=config_text)
 h = image.shape[0]
 w = image.shape[1]

 # 人脸检测
 blobImage = cv.dnn.blobFromImage(image, 1.0, (300, 300), (104.0, 177.0, 123.0), False, False);
 net.setInput(blobImage)
 cvOut = net.forward()

 # Put efficiency information.
 t, _ = net.getPerfProfile()
 label = 'Inference time: %.2f ms' % (t * 1000.0 / cv.getTickFrequency())
 cv.putText(image, label, (0, 15), cv.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0))

 # 绘制检测矩形
 count = 0
 for detection in cvOut[0, 0, :, :]:
 score = float(detection[2])
 if score > 0.5:
 left = detection[3] * w
 top = detection[4] * h
 right = detection[5] * w
 bottom = detection[6] * h
 count += 1
 x = np.int32(left - 100)
 y = np.int32(top - 100)
 height = np.int32((bottom - top) + 200)
 width = np.int32((right - left) + 200)

 if x < 0:
 x = 0
 if y < 0:
 y = 0
 if x+width > w:
 width = w - x
 if y+height > h:
 height = h - y

 if count == 1:
 return image[y:y + height, x:x + width, :]
 else:
 return image


def generate_new_profile(flag_icon, avatar):
 mask = cv.inRange(icon, (210, 210, 210), (225, 225, 225))
 se = cv.getStructuringElement(cv.MORPH_RECT, (3, 3))
 mask = cv.morphologyEx(mask, cv.MORPH_CLOSE, se)
 cv.imwrite("D:/mask1.png", mask)
 # mask with gaussian
 mask = cv.GaussianBlur(mask, (5, 5), 0)
 cv.imshow("mask", mask)
 cv.imwrite("D:/mask2.png", mask)

 # blend
 h, w = mask.shape[:2]
 avatar = cv.resize(avatar, (w, h), interpolation=cv.INTER_CUBIC)
 cv.imshow("profile", avatar)
 result = np.zeros_like(avatar)
 for row in range(h):
 for col in range(w):
 pv = mask[row, col]
 w1 = pv / 255.0
 w2 = 1.0 - w1
 b1, g1, r1 = avatar[row, col]
 b2, g2, r2 = icon[row, col]
 b1 = b1 * w1 + b2 * w2
 g1 = g1 * w1 + g2 * w2
 r1 = r1 * w1 + r2 * w2
 result[row, col] = [np.int32(b1), np.int32(g1), np.int32(r1)]
 return result


if __name__ == "__main__":
 icon = cv.imread("D:/images/flag.png")
 src = cv.imread("D:/images/zhigang.png")
 cv.imshow("input", icon)
 cv.imshow("profile", src)
 avatar = get_face(src, False)
 result = generate_new_profile(icon, avatar)
 cv.imshow("result", result)
 cv.imwrite("D:/result.png", result)
 cv.waitKey(0)
 cv.destroyAllWindows()