Page 372 - MDP2020-3

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| 인천전자마이스터고등학교 ·············································································································

# 카메라로 부터 사진 한장 읽어 오기
ret, faceFrame = cap.read()

# 사진에서 얼굴 검출 , 얼굴이 검출되었다면
if face_extractor(faceFrame) is not None:

count += 1
face = cv2.resize(face_extractor(faceFrame), (200, 200))

face = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)

file_name_path = face_dirs + name + '/user' + str(count) + '.jpg'
cv2.imwrite(file_name_path, face)

cv2.putText(face, str(count), (50, 50), cv2.FONT_HERSHEY_COMPLEX, 1,
(0, 255, 0), 2)
cv2.imshow('Face Cropper', face)
else:
print("얼굴이 검출되지 않았습니다")

pass
if count == 100:
break
cap.release()
cv2.destroyAllWindows()

print(str(count) + "장의 사진 수집을 완료했습니다")

def train(pName):
data_path = 'faces/' + pName + '/'

# 파일만 리스트로 만듬
face_pics = [f for f in listdir(data_path) if isfile(join(data_path, f))]

Training_Data, Labels = [], []

for i, files in enumerate(face_pics):
image_path = data_path + face_pics[i]
images = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
# 이미지가 아니면 패스
if images is None:

continue
Training_Data.append(np.asarray(images, dtype=np.uint8))
Labels.append(i)
if len(Labels) == 0: