第1关：人脸检测
python
复制代码
'''****************BEGIN****************'''
import face_recognition
image_path = './step1/image/children.jpg'
image = face_recognition.load_image_file(image_path)
face_locations = face_recognition.face_locations(image)
print(face_locations)
'''**************** END ****************'''
import cv2
for face_location in face_locations:
'''****************BEGIN****************'''
top, right, bottom, left = face_location
cv2.rectangle(image, (left, top), (right, bottom), (0, 255, 0), 2)
'''**************** END ****************'''
# 保存图片
image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
cv2.imwrite("./step1/out/children.jpg", image_rgb)
第2关：人脸特征点获取
python
复制代码
import face_recognition
'''****************BEGIN****************'''
# 获取人脸特征点
image = face_recognition.load_image_file("./step2/image/laugh.jpg")
face_landmarks_list = face_recognition.face_landmarks(image)
print(face_landmarks_list)
'''**************** END ****************'''
import cv2
# 绘制人脸特征点
for face_landmarks in face_landmarks_list:
'''****************BEGIN****************'''
for facial_feature in face_landmarks.keys():
for pt_pos in face_landmarks[facial_feature]:
cv2.circle(image, pt_pos, 1, (255, 0, 0), 2)
'''**************** END ****************'''
# 保存图片
image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
cv2.imwrite("./step2/out/laugh.jpg", image_rgb)
第3关：人脸识别
python
复制代码
import face_recognition
def recognition():
'''****************BEGIN****************'''
# 导入图片
known_image_path = "./step3/known_image/cyx1.jpg"
known_image_cyz = face_recognition.load_image_file(known_image_path)
unknown_image_1_path = "./step3/unknown_image/cyx2.jpg"
unknown_image_2_path = "./step3/unknown_image/wlh.jpg"
unknown_image_1 = face_recognition.load_image_file(unknown_image_1_path)
unknown_image_2 = face_recognition.load_image_file(unknown_image_2_path)
'''**************** END ****************'''
'''****************BEGIN****************'''
# 编码获取128维特征向量
cyz_encoding = face_recognition.face_encodings(known_image_cyz)[0]
unknown_encoding_1 = face_recognition.face_encodings(unknown_image_1)[0]
unknown_encoding_2 = face_recognition.face_encodings(unknown_image_2)[0]
'''**************** END ****************'''
'''****************BEGIN****************'''
# 比较特征向量值，识别人脸
face1_result = face_recognition.compare_faces([cyz_encoding], unknown_encoding_1, tolerance=0.5)
face2_result = face_recognition.compare_faces([cyz_encoding], unknown_encoding_2, tolerance=0.5)
'''**************** END ****************'''
return face1_result, face2_result
第4关：人脸识别绘制并展示
python
复制代码
import face_recognition
import cv2
'''****************BEGIN****************'''
# 加载已知图片
known_image_c_path = "./step4/known_image/Caocao.jpg"
known_image_xy_path = "./step4/known_image/XunYu.jpg"
known_image_smy_path = "./step4/known_image/SiMayi.jpg"
known_image_zch_path = "./step4/known_image/ZhangChunhua.jpg"
known_image_cc = face_recognition.load_image_file(known_image_c_path)
known_image_xy = face_recognition.load_image_file(known_image_xy_path)
known_image_smy = face_recognition.load_image_file(known_image_smy_path )
known_image_zch = face_recognition.load_image_file( known_image_zch_path)
'''**************** END ****************'''
'''****************BEGIN****************'''
# 对图片进行编码，获取128维特征向量
caocao_encoding = face_recognition.face_encodings(known_image_cc)[0]
xy_encoding = face_recognition.face_encodings(known_image_xy)[0]
zys_encoding = face_recognition.face_encodings(known_image_smy)[0]
cyz_encoding = face_recognition.face_encodings(known_image_zch)[0]
'''**************** END ****************'''
'''****************BEGIN****************'''
# 存为数组以便之后识别
known_faces = [
caocao_encoding,
xy_encoding,
zys_encoding,
cyz_encoding
]
'''**************** END ****************'''
'''****************BEGIN****************'''
# 加载待识别图片
unknown_image_1_path = "./step4/unknown_image/Caocao.jpg"
unknown_image_2_path = "./step4/unknown_image/Cuple.jpg"
unknown_image_3_path = "./step4/unknown_image/ZhangChunhua.jpg"
unknown_image_4_path = "./step4/unknown_image/XunYu.jpg"
unknown_image_5_path = './step4/unknown_image/A.jpg'
unknown_image_1 = face_recognition.load_image_file(unknown_image_1_path)
unknown_image_2 = face_recognition.load_image_file(unknown_image_2_path)
unknown_image_3 = face_recognition.load_image_file(unknown_image_3_path)
unknown_image_4 = face_recognition.load_image_file(unknown_image_4_path)
unknown_image_5 = face_recognition.load_image_file(unknown_image_5_path)
'''**************** END ****************'''
'''****************BEGIN****************'''
# 存为数组以遍历识别
unknown_faces = [
unknown_image_1,
unknown_image_2,
unknown_image_3,
unknown_image_4,
unknown_image_5
]
'''**************** END ****************'''
# 初始化一些变量
face_locations = []
face_encodings = []
face_names = []
frame_number = 0
for frame in unknown_faces:
face_names = []
'''****************BEGIN****************'''
face_locations = face_recognition.face_locations(frame)
# 对图片进行编码，获取128维特征向量
face_encodings = face_recognition.face_encodings(frame, face_locations)
'''**************** END ****************'''
for face_encoding in face_encodings:
'''****************BEGIN****************'''
# 识别图片中人脸是否匹配已知图片
match = face_recognition.compare_faces(
known_faces, face_encoding, tolerance=0.5)
'''**************** END ****************'''
'''****************BEGIN****************'''
name = None
if match[0]:
name = "Caocao"
elif match[1]:
name = "XunYu"
elif match[2]:
name = "SiMayi"
elif match[3]:
name = 'ZhangChunhua'
else:
name = 'Unknown'
'''**************** END ****************'''
face_names.append(name)
# 结果打上标签
for (top, right, bottom, left), name in zip(face_locations, face_names):
if not name:
continue
'''****************BEGIN****************'''
# 绘制脸部区域框
# 绘制脸部区域框
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
# 在脸部区域下面绘制人名
cv2.rectangle(frame, (left, bottom - 25),
(right, bottom), (0, 0, 255), cv2.FILLED)
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(frame, name, (left + 6, bottom - 6),
font, 0.5, (255, 255, 255), 1)
'''**************** END ****************'''
print(frame[left+6, bottom-6])
print(frame[left, bottom])
print(face_locations)
print(face_names)
# 保存图片
image_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
path = './step4/out/' + name + str(face_locations[0][0]) + '.jpg'
cv2.imwrite(path, image_rgb)