pip install dlib
pip install imutils

pip install dlib 에러발생 pip install cmake Visual Studio 설치시 Windows용 C++ CMake 도구가 체크되어 있는지 확인한다.

import dlib, cv2, os
from imutils import face_utils
import numpy as np
import matplotlib.pyplot as plt

# Load Models
detector = dlib.cnn_face_detection_model_v1('assets/data/dogHeadDetector.dat')
predictor = dlib.shape_predictor('assets/data/landmarkDetector.dat')

# Load Dog Image
img_path = 'assets/images/18.jpg'
filename, ext = os.path.splitext(os.path.basename(img_path))
img = cv2.imread(img_path)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
# img = cv2.resize(img, dsize=None, fx=0.5, fy=0.5)

plt.figure(figsize=(16, 16))
plt.imshow(img)

# Detect Faces
dets = detector(img, upsample_num_times=1)

print(dets)

img_result = img.copy()

for i, d in enumerate(dets):
 print("Detection {}: Left: {} Top: {} Right: {} Bottom: {} Confidence: {}".format(i, d.rect.left(), d.rect.top(),
                                                                                   d.rect.right(), d.rect.bottom(),
                                                                                   d.confidence))

 x1, y1 = d.rect.left(), d.rect.top()
 x2, y2 = d.rect.right(), d.rect.bottom()

 cv2.rectangle(img_result, pt1=(x1, y1), pt2=(x2, y2), thickness=2, color=(255, 0, 0), lineType=cv2.LINE_AA)

plt.figure(figsize=(16, 16))
plt.imshow(img_result)

# Detect Landmarks
shapes = []

for i, d in enumerate(dets):
 shape = predictor(img, d.rect)
 shape = face_utils.shape_to_np(shape)

 for i, p in enumerate(shape):
   shapes.append(shape)
   cv2.circle(img_result, center=tuple(p), radius=3, color=(0, 0, 255), thickness=-1, lineType=cv2.LINE_AA)
   cv2.putText(img_result, str(i), tuple(p), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1, cv2.LINE_AA)

img_out = cv2.cvtColor(img_result, cv2.COLOR_RGB2BGR)
cv2.imwrite('assets/images//%s_out%s' % (filename, ext), img_out)
plt.figure(figsize=(16, 16))
plt.imshow(img_result)

# Overlay Reindeer Horns and Nose
from math import atan2, degrees

# overlay function
def overlay_transparent(background_img, img_to_overlay_t, x, y, overlay_size=None):
 img_to_overlay_t = cv2.cvtColor(img_to_overlay_t, cv2.COLOR_BGRA2RGBA)
 bg_img = background_img.copy()
 # convert 3 channels to 4 channels
 if bg_img.shape[2] == 3:
   bg_img = cv2.cvtColor(bg_img, cv2.COLOR_RGB2RGBA)

 if overlay_size is not None:
   img_to_overlay_t = cv2.resize(img_to_overlay_t.copy(), overlay_size)

 b, g, r, a = cv2.split(img_to_overlay_t)

 mask = cv2.medianBlur(a, 5)

 h, w, _ = img_to_overlay_t.shape
 roi = bg_img[int(y-h/2):int(y+h/2), int(x-w/2):int(x+w/2)]

 img1_bg = cv2.bitwise_and(roi.copy(), roi.copy(), mask=cv2.bitwise_not(mask))
 img2_fg = cv2.bitwise_and(img_to_overlay_t, img_to_overlay_t, mask=mask)

 bg_img[int(y-h/2):int(y+h/2), int(x-w/2):int(x+w/2)] = cv2.add(img1_bg, img2_fg)

 # convert 4 channels to 4 channels
 bg_img = cv2.cvtColor(bg_img, cv2.COLOR_RGBA2RGB)

 return bg_img

def angle_between(p1, p2):
 xDiff = p2[0] - p1[0]
 yDiff = p2[1] - p1[1]
 return degrees(atan2(yDiff, xDiff))


img_result2 = img.copy()

horns = cv2.imread('assets/images/horns2.png', cv2.IMREAD_UNCHANGED)
horns_h, horns_w = horns.shape[:2]

nose = cv2.imread('assets/images/nose.png', cv2.IMREAD_UNCHANGED)

for shape in shapes:
 horns_center = np.mean([shape[4], shape[1]], axis=0) // [1, 1.3]
 horns_size = np.linalg.norm(shape[4] - shape[1]) * 3

 nose_center = shape[3]
 nose_size = horns_size // 4

 angle = -angle_between(shape[4], shape[1])
 M = cv2.getRotationMatrix2D((horns_w, horns_h), angle, 1)
 rotated_horns = cv2.warpAffine(horns, M, (horns_w, horns_h))

 img_result2 = overlay_transparent(img_result2, nose, nose_center[0], nose_center[1],
                                   overlay_size=(int(nose_size), int(nose_size)))
 try:
     img_result2 = overlay_transparent(img_result2, rotated_horns, horns_center[0], horns_center[1],
                                       overlay_size=(int(horns_size), int(horns_h * horns_size / horns_w)))
 except:
     print('failed overlay image')

img_out2 = cv2.cvtColor(img_result2, cv2.COLOR_RGB2BGR)
cv2.imwrite('assets/images/%s_out2%s' % (filename, ext), img_out2)
plt.figure(figsize=(16, 16))
plt.imshow(img_result2)

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