def __init__(self):
""" 你的 APPID AK SK """
APP_ID = '16947698'
API_KEY = 'fN9yStlTEv1zkWoMDMQU7YKT'
SECRET_KEY = 'fqk4FfDRZp7fjk1ngcTeeaKtgWZxFh6H'
self.gesture_client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
self.gesture_contrast = {
"Ok": "1",
"Thumb_up": "4",
"Thumb_down": "5",
"Insult": "2",
"Six": "3",
"Five": "6",
"Fist": "7",
"Honour": "8",
}
# 0指的是摄像头的编号。如果你电脑上有两个摄像头的话，访问第2个摄像头就可以传入1。
self.capture = cv2.VideoCapture(0)
self.music_names = os.listdir('music') # 列表歌
self.music_source = [] # 音频播放路劲
self.current_music_no = 0 # 音乐
self.volume = 0.2 # 设置播放频道的音量
def __init__(self):
APP_ID = '18721308'
API_KEY = 'lNQGdBNazTPv8LpSP4x0GQlI'
SECRET_KEY = 'nW8grONY777n4I2KvpOVuKGDNiY03omI'
self.client_face = AipFace(APP_ID, API_KEY, SECRET_KEY)
self.client_body = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
self.image_type = "BASE64"
filepath = "/Pictures/image.jpg"
msg = reception_image()
self.guest = Guest()
# self.name = None
# self.age = None
# self.image = None
# self.gender = None
# self.drink = None
self.options_body = {}
self.options_body["type"] = "gender,upper_color,upper_wear_fg"
self.options_face = {}
self.options_face["face_field"] = "age,gender"
self.options_face["max_face_num"] = 3
self.options_face["face_type"] = "LIVE"
#发布器
self.roi_pub = rospy.Publisher('/image/roi',RegionOfInterest,queue_size=1)
self.objpos_pub = rospy.Publisher('/image/object_position2d',String,queue_size=1)
self.control_pub = rospy.Pubscriber("/control", reception, queue_size=1)
self.speech_pub = rospy.Pubscriber('/speech/check_door',reception_image,self.find_people)
#订阅器
self.control_sub = rospy.Subscriber("/control", reception, self.controlCallback)
self.ROI = RegionOfInterest()
def init_body_detection():
# baidu clond AI detection project https://console.bce.baidu.com
app_id = "18480308"
api_key = "r1ddkBzIGucxEwCkRArbrZGn"
secret_key = "7ZCAHQaVWvuKP2MCKRxbdgiL3eMbGbhy"
client = AipBodyAnalysis(app_id, api_key, secret_key)
client.setConnectionTimeoutInMillis(4000)
client.setSocketTimeoutInMillis(7000)
options = {"type": "gender,age"}
def detective(image):
try:
r = client.bodyAttr(image, options)
if r["person_num"] == 0:
Log.logger.info("image contain no person")
return [], "no_body"
for person in r['person_info']:
if person['attributes']['gender']['name'] == "男性":
Log.logger.info("male has been detected, discard")
return [], "male"
if person['attributes']['gender']['score'] < 0.6:
Log.logger.info("not that much like a girl discard")
return [], "neutral"
if person['attributes']['age']['name'] == "幼儿":
Log.logger.info("children has been detected, discard")
return [], "children"
except Exception as e:
Log.logger.warning("image can't be processed {}".format(e))
return [], "error"
return [r], "girl"
return detective
def bdcut(path):
try:
pic = Image.open(path)
if pic.mode == "P": pic = pic.convert('RGB') # 有些图片有P通道，base编码后会出问题
(wf,hf) = pic.size
BD_VIP='否'
BD_AI_client = AipBodyAnalysis('替换appid','替换apikey','替换secrekey')
with open(path, 'rb') as fp:
x_nose = int(BD_AI_client.bodyAnalysis(fp.read())["person_info"][0]['body_parts']['nose']['x']) # 返回鼻子横坐标
if BD_VIP == '否':
time.sleep(0.4) # 免费用户QPS=2
else:
time.sleep( 1/int(1.1*BD_VIP) )
if x_nose + 1/3*hf > wf: # 判断鼻子在图整体的位置
x_left = wf-2/3*hf # 以右为边
elif x_nose - 1/3*hf < 0:
x_left = 0 # 以左为边
else:
x_left = x_nose-1/3*hf # 以鼻子为中线向两边扩展
fixed_pic = pic.crop((x_left,0,x_left+2/3*hf,hf))
fixed_pic.save(path.replace('fanart','poster'), quality=95)
print('[+]百度AI裁剪操作成功')
except:
imagecut=1
print('[-] '+ path +' AI 分析失败，跳过 AI 直接裁剪。\n')
def __init__(self):
self.app_id = rospy.get_param("~app_id")
self.api_key = rospy.get_param("~api_key")
self.secret_key = rospy.get_param("~secret_key")
self.client = AipBodyAnalysis(self.app_id, self.api_key,
self.secret_key)
self.bridge = CvBridge()
def gesture_recognition():
gesture_client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
frame = telloGetFrame(Drone)
cv2.imshow('frame', frame)
cv2.imwrite("{}.png".format(img_count), frame)
image = get_file_content("{}.png".format(img_count))
gesture = gesture_client.gesture(image) #AipBodyAnalysis内部函数
print(gesture)
def __init__(self, configPath, configSection): keyInfo = fu.readConfig(configPath, configSection) self.appid = keyInfo['appid'] self.api_key = keyInfo['api_key'] self.secret_key = keyInfo['secret_key'] self.client = AipBodyAnalysis(self.appid, self.api_key, self.secret_key) self.filename = None self.picture = None self.picture_size = None self.picture_format = None
def analyse_people(self, filePath):
client = AipBodyAnalysis(self.APP_ID, self.API_KEY, self.SECRET_KEY)
""" 读取图片 """
with open(filePath, 'rb') as fp:
data = client.bodyAttr(fp.read())
data = str(data)
res = re.findall(r"'(.*?)': {'score': (0.\d+), 'name': '(.*?)'}", data, re.S)
del res[0]
for r in res:
print("{:—<20}特征:{:—<15}精准度:{}".format(r[0],r[2], r[1]))
""" 如果有可选参数 """
def __init__(self):
self.qe = queue
self.q = self.qe.Queue(maxsize=5)
""" 你的人流量统计 APPID AK SK """
self.APP_ID = '16193424'
self.API_KEY = 'eqZCDofIR6FXWaMHr5bszls6'
self.SECRET_KEY = 'CIlH54Ro1HvpZwQR4nQbetQEcnPqWbUQ'
self.aipBodyAnalysis = AipBodyAnalysis(self.APP_ID, self.API_KEY,
self.SECRET_KEY)
# self.aipFace = AipFace(Aself.PP_ID, self.API_KEY, self.SECRET_KEY)
self.cap = cv2.VideoCapture("http://49.90.255.4:10001/8.ts")
def detection(self):
clients = AipBodyAnalysis(self.APP_ID, self.API_KEY, self.SECRET_KEY)
image = self.get_file_content('test.jpg')
options = {}
# """ 带参数调用人体检测与属性识别 """
res = clients.bodyAttr(image, options)
data = res['person_info'][0]['attributes']
news = {}
for k, v in data.items():
news[k] = v['name']
pprint(news)
def body_seg(filename="./pic/test.jpg", savefilename="./pic/fore.jpg"):
APP_ID = '19037846'
API_KEY = 'pi8i47A8jGBH1VZDr8ioqgfC'
SECRET_KEY = 'qwcqweVfjf9pX2fB6MykU15u6XszXko4'
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
image = get_file(filename)
options = {}
options["type"] = "foreground"
res = client.bodySeg(image, options)
foreground = base64.b64decode(res["foreground"])
with open(savefilename, "wb") as f:
f.write(foreground)
def pose_codelab(content, pose):
#百度API通行证（获取方法见https://ai.baidu.com）
APP_ID = '21219492'
API_KEY = 'jC6Z4Fa9jTs6wtpUTkoyGVMV'
SECRET_KEY = 'pbGBVFu41ZZRWHhtPEqUbGTaEekaKfqc'
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY) #输入ID和密钥建立连接
video_capture = cv2.VideoCapture(0)
while True:
ret, frame = video_capture.read() #读取摄像头数据
#处理图片格式并发送给云端API
frame_b = cv2.imencode(".jpg", frame)[1].tobytes()
gesture_info = client.gesture(frame_b)
#处理识别结果（API会将识别到的人脸和手势全部返回）
if gesture_info['result']:
result = gesture_info['result']
num = gesture_info['result_num']
for i in range(num):
classname = result[i]['classname'] #识别的手势/人脸类别
#识别框坐标
left = result[i]['left']
top = result[i]['top']
width = result[i]['width']
height = result[i]['height']
#绘制识别框
cv2.rectangle(frame, (left, top), (left + width, top + height),
(0, 0, 255), 2)
if (classname == 'Face'):
cv2.putText(frame, 'Face', (left, top + 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 1)
else:
cv2.putText(frame, '{}'.format(classname),
(left, top + 10), cv2.FONT_HERSHEY_SIMPLEX,
0.5, (255, 255, 0), 1)
pose.send_message_to_scratch(classname) #发送识别结果到scratch
cv2.imshow('Video', frame)
time.sleep(0.15) #防止QPS溢出
# Hit 'q' on the keyboard to quit!
if cv2.waitKey(100) & 0xFF == ord('q'):
break
# time.sleep(5)
#
# Release handle to the webcam
video_capture.release()
cv2.destroyAllWindows()
def fanHuiTuPianGuanDianX_Y(url): #从百度AI获取到图片关键点返回值，参数为图片路径
""" 你的 APPID AK SK """
APP_ID = '22952436'
API_KEY = 'a5UrzVfjQHyuK0GSCXk8QoQH'
SECRET_KEY = '8wguEEmbNTnMfAOOOigMr1cM1SZXvq1c'
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
def get_file_content(filePath):
with open(filePath, 'rb') as fp:
return fp.read()
image = get_file_content(url)
return client.bodyAnalysis(image)
def bodypart(filename):
# APP_ID = 'd90755ad2f2047dbabb12ad0adaa0b03'
# API_KEY = 'b7b0f4d01f7f4aef9b5453f6558c23b1'
# SECRET_KEY = '6ad666162ef24213b5bde7bdd904fcbe'
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
# """ 读取图片 """
image = get_file_content(filename)
# """ 调用人体关键点识别 """
para = client.bodyAnalysis(image)
# print(para)
# time.sleep(2)
return para
def index(fileName):
APP_ID = ''
API_KEY = ''
SECRET_KEY = ''
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
image = get_file_content(fileName)
""" 调用手势识别 """
res = client.gesture(image)
if 'error_code' in res:
print(res['error_msg'])
try:
classname = res['result'][0]['classname']
print(classname)
return classname
except Exception as err:
print('手势识别失败')
def picscoket(self,a,q):
APP_ID = ·····
API_KEY = ····
SECRET_KEY = ·····
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
while True:
if q.qsize() >= 1:
pic = q.get()
image = self.get_file_content(pic)
client.bodyNum(image)
options = {}
options["area"] = "0,0,100,100,200,200"
options["show"] = "false"
client.bodyNum(image, options)
num = client.bodyNum(image, options)
testnum = json.dumps(num)
testnum2 = json.loads(testnum)
testnum3 = testnum2['person_num']
db = pymysql.connect('localhost', 'root', 'root', 'camera')
cursor = db.cursor()
ye = now = datetime.datetime.now()
ye = ye.strftime('%y')
mo = now = datetime.datetime.now()
mo = mo.strftime('%m')
da = now = datetime.datetime.now()
da = da.strftime('%d')
sql = "INSERT INTO num(year ,person_num,month,day) VALUES ( '%s', '%s','%s','%s')" % (ye, testnum3, mo, da)
try:
# 执行sql语句
cursor.execute(sql)
# 提交到数据库执行
db.commit()
except:
# 如果发生错误则回滚
db.rollback()
# 关闭数据库连接
db.close()
print(testnum3)
else:
print('为空')
time.sleep(5)
def AutoCutout(path):
APP_ID = '19815134'
API_KEY = 'i7yBb3Fx3e4ZMILo8nHsrZQT'
SECRET_KEY = 'wuEXaPYbz1RXlAdDYYRj49tlPoNZdqfW'
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
imgfile = path
ori_img = cv2.imread(imgfile)
height, width, _ = ori_img.shape
with open(imgfile, 'rb') as fp:
img_info = fp.read()
seg_res = client.bodySeg(img_info)
labelmap = base64.b64decode(seg_res['labelmap'])
nparr = np.fromstring(labelmap, np.uint8)
labelimg = cv2.imdecode(nparr, 1)
labelimg = cv2.resize(labelimg, (width, height), interpolation=cv2.INTER_NEAREST)
new_img = np.where(labelimg == 1, 255, labelimg)
result = cv2.bitwise_and(ori_img, new_img)
cv2.imwrite(path, result)
def Seg_img(jpg_path, crop_path, save_path):
'''
调用API 分割人像图片
:param jpg_path: 原图像
:param crop_path: 裁剪之后图像
:param save_path: 生成 mask 存放路径
:return:
'''
# 通过百度控制台申请得到的 AK 和 SK；
APP_ID = "23633750"
API_KEY = 'uqnHjMZfChbDHvPqWgjeZHCR'
SECRET_KEY = 'KIKTgD5Dh0EGyqn74Zqq8wHWB39uKaS3'
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
# 文件夹
jpg_file = os.listdir(jpg_path)
# 要保存的文件夹
for i in jpg_file:
open_file = os.path.join(jpg_path, i)
save_file = os.path.join(save_path, i)
if not os.path.exists(save_file): #文件不存在时，进行下步操作
img = cv2.imread(open_file) # 获取图像尺寸
height, width, _ = img.shape
if crop_path: # 若Crop_path 不为 None,则不进行裁剪
crop_file = os.path.join(crop_path, i)
img = img[100:-1, 300:-400] #图片太大，对图像进行裁剪
cv2.imwrite(crop_file, img)
image = get_file_content(crop_file)
else:
image = get_file_content(open_file)
res = client.bodySeg(image) #调用百度API 对人像进行分割
labelmap = base64.b64decode(res['labelmap'])
labelimg = np.frombuffer(labelmap, np.uint8) # 转化为np数组 0-255
labelimg = cv2.imdecode(labelimg, 1)
labelimg = cv2.resize(labelimg, (width, height),
interpolation=cv2.INTER_NEAREST)
img_new = np.where(labelimg == 1, 255, labelimg) # 将 1 转化为 255
cv2.imwrite(save_file, img_new)
print(save_file, 'save successfully')
def parseimage(self, image):
filename = 'images/gesture.png'
cv2.imwrite(filename, image)
myimage = self.get_file_content(filename)
client = AipBodyAnalysis(self.APP_ID, self.API_KEY, self.SECRET_KEY)
result = client.gesture(myimage)
print(result)
if result["result_num"] > 0:
data = result['result']
print(data[0]["classname"])
if data[0]['classname'] == ('Heart_single' or 'Heart_1'
or 'Heart_2' or 'Heart_3'):
self.robotpi_movement.move_left()
if data[0]['classname'] == 'Fist':
self.robotpi_movement.wave_hands()
if data[0]['classname'] == 'Rock':
self.robotpi_movement.play_sound(2, 16)
else:
print("暂无结果")
self.robotpi_movement.play_sound(2, 4)
def __init__(self):
self.time = time.time()
APP_ID = '18889374'
API_KEY = 'pUNweNaSK4rWz57vGs9KpuW1'
SECRET_KEY = 'ru5LqWM0lrcVYBh9cjd32fy951nagqcA'
self.image_type = "BASE64"
self.client_face = AipFace(APP_ID, API_KEY, SECRET_KEY)
self.client_body = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
self.client_body.setConnectionTimeoutInMillis(2000)
self.client_body.setSocketTimeoutInMillis(2000)
self.client_face.setConnectionTimeoutInMillis(2000)
self.client_face.setSocketTimeoutInMillis(2000)
self.bridge = CvBridge()
self.ispub = False
##############人类数据
self.filepath = "/home/qian/catkin_ws/src/fare_src/kamerider_image/kamerider_image_api/imgfile/"
##############跟踪数据
self.roi = None
self.depth_array = None
self.target_pos = Pose()
##############话题名称
# 接收器与发布器
self.check_gender = rospy.get_param('~check_gender', 'False')
if (type(self.check_gender) == type('text')):
self.check_gender = False
##############发布器
self.img_pub = rospy.Publisher("/image/test", Image, queue_size=1)
self.roi_pub = rospy.Publisher("roi", RegionOfInterest, queue_size=1)
self.img_sub = rospy.Subscriber("/usb_cam/image_raw",
Image,
self.imgCallback,
queue_size=1)
self.word_pub = rospy.Publisher("/xfwords", String, queue_size=1)
self.face_pub = rospy.Publisher("/start_recognize_faces",
String,
queue_size=1)
print("============================================================")
def face_center(filename, model):
app_id = config.getInstance().conf.get("face", "appid")
api_key = config.getInstance().conf.get("face", "key")
app_secret = config.getInstance().conf.get("face", "secret")
client = AipBodyAnalysis(app_id, api_key, app_secret)
with open(filename, 'rb') as fp:
img = fp.read()
result = client.bodyAnalysis(img)
if 'error_code' in result:
raise ValueError(result['error_msg'])
print('[+]Found person ' + str(result['person_num']))
# 中心点取鼻子x坐标
maxRight = 0
maxTop = 0
for person_info in result["person_info"]:
x = int(person_info['body_parts']['nose']['x'])
top = int(person_info['location']['top'])
if x > maxRight:
maxRight = x
maxTop = top
return maxRight, maxTop
def __init__(self):
APP_ID = '18721308'
API_KEY = 'lNQGdBNazTPv8LpSP4x0GQlI'
SECRET_KEY = 'nW8grONY777n4I2KvpOVuKGDNiY03omI'
self.client_face = AipFace(APP_ID, API_KEY, SECRET_KEY)
self.client_body = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
self.image_type = "BASE64"
msg = reception_image()
self.guest = Guest()
# self.name = None
# self.age = None
# self.image = None
# self.gender = None
# self.drink = None
self.options_body = {}
self.options_body["type"] = "gender,upper_color,upper_wear_fg"
self.options_face = {}
self.options_face["face_field"] = "age,gender"
self.options_face["max_face_num"] = 3
self.options_face["face_type"] = "LIVE"
#ros params
self.sub_image_raw_topic_name = None
self.sub_destination_topic_name = None
self.pub_gender_recognition_topic_name = None
self.pub_object_position2d = None
# self.depth_img = np.array((480,640))
self.get_params()
#发布器
self.objpos_pub = rospy.Publisher('/image/object_position2d',
String,
queue_size=1)
#订阅器
self.control_sub = rospy.Subscriber("/control", reception,
self.controlCallback)
self.speech_sub = rospy.Subscriber('/speech/check_door', String,
self.find_people)
def gestureRecog(self):
APP_ID = '16534881'
API_KEY = 'DSG6hUBgBVt61Ms1XXnYuEPm'
SECRET_KEY = 'W4nkl6xYmOnRjntg53fDMuxQXvqemNI0'
a = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
cap=cv2.VideoCapture(0)
while 1:
ret,image=cap.read()
cv2.imshow("capture", image)
if cv2.waitKey(100)&0xff==ord("q"):
cv2.imwrite("test.jpg", image)
break
cap.release()
cv2.destroyAllWindows()
filePath = "test.jpg"
options = {}
options["top_num"] = 5
result=a.gesture(self.get_file_content(filePath),options)
print(result)
k=result["result"][0]["classname"]
if k=="Insult":
self.port_reset()
if k=="ILY":
self.Slider_3.setValue(500)
time.sleep(0.5)
self.Slider_3.setValue(1500)
else:
return
def __init__(self):
self.time = time.time()
APP_ID = '18889374'
API_KEY = 'pUNweNaSK4rWz57vGs9KpuW1'
SECRET_KEY = 'ru5LqWM0lrcVYBh9cjd32fy951nagqcA'
self.imageType = "BASE64"
self.client_face = AipFace(APP_ID, API_KEY, SECRET_KEY)
self.client_body = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
self.bridge = CvBridge()
##############人类数据
self.filepath = "/home/dell/img/"
self.option_face = {}
self.option_body = {}
self.option_face["face_field"] = "age,gender,glasses,race"
self.option_face["max_face_num"] = 1
self.option_body["type"] = "upper_wear,upper_color"
##############跟踪数据
self.roi = None
##############话题名称
# 接收器与发布器
self.sub_image_name = rospy.get_param('~image_raw_topic_name',
'/usb_cam/image_raw')
# 发布器
self.pub_pos_name = rospy.get_param('~object_view_topic_name', 'roi')
self.pub_img_name = rospy.get_param('~image_test_topic_name',
'/image/test')
self.pub_fet_name = rospy.get_param('~feature_topic_name',
'/image/feature')
##############发布器
self.img_pub = rospy.Publisher(self.pub_img_name, Image)
self.roi_pub = rospy.Publisher(self.pub_pos_name, RegionOfInterest)
self.fet_pub = rospy.Publisher(self.pub_fet_name, Description)
self.img_sub = rospy.Subscriber(self.sub_image_name, Image,
self.imgCallback)
print("============================================================")
def cut_picture(src):
# 在百度云中申请，每天各接口有 500 次调用限制.
APP_ID = '16628525'
API_KEY = '5ioBzjijPln33f7mPzyProbc'
SECRET_KEY = 'FR4URtsr2Q77r6RvNyld4swls1Eik5Pu'
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
# 读取待分割人像图片
imgfile = src
ori_img = cv2.imread(imgfile)
height, width, _ = ori_img.shape
with open(imgfile, 'rb') as fp:
img_info = fp.read()
# print("img_info:", img_info)
seg_res = client.bodySeg(img_info)
labelmap = base64.b64decode(seg_res['labelmap'])
nparr = np.fromstring(labelmap, np.uint8)
labelimg = cv2.imdecode(nparr, 1)
labelimg = cv2.resize(labelimg, (width, height),
interpolation=cv2.INTER_NEAREST)
new_img = np.where(labelimg == 1, 255, labelimg)
# maskfile = imgfile.replace('.jpg', '_mask.png')
maskfile_dir = './static/image/cut/' + \
imgfile.split('/')[-1].split('.')[0]+'_mask.png'
cv2.imwrite(maskfile_dir, new_img)
# res_imgfile = imgfile.replace('.jpg', '_res.jpg')
result = cv2.bitwise_and(ori_img, new_img)
# 保存最终分割出的人像图片到原始图片所在目录
result_path = './static/image/cut/' + \
imgfile.split('/')[-1].split('.')[0]+'_res.jpg'
cv2.imwrite(result_path, result)
def bodyseg(filename):
# APP_ID = 'd90755ad2f2047dbabb12ad0adaa0b03'
# API_KEY = 'b7b0f4d01f7f4aef9b5453f6558c23b1'
# SECRET_KEY = '6ad666162ef24213b5bde7bdd904fcbe'
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
# """ 读取图片 """
image = get_file_content(filename)
res = client.bodySeg(image)
print(res)
labelmap = base64.b64decode(res['labelmap'])
# time.sleep(2)
nparr_labelmap = np.fromstring(labelmap, np.uint8)
labelmapimg = cv2.imdecode(nparr_labelmap, 1)
print(labelmapimg.shape)
im_new_labelmapimg = np.where(labelmapimg == 1, 255, labelmapimg)
# print(im_new_labelmapimg.shape)
# img=cv2.cvtColor(im_new_labelmapimg, cv2.COLOR_BGR2GRAY)
# return img.astype('uint8')
# cv2.imwrite('outline.png',im_new_labelmapimg)
return im_new_labelmapimg
from aip import AipBodyAnalysis
import json
import cv2 as cv
APP_ID ='11589803'
API_KEY ='K2WOMV1pCyI1IXIbvawDDRhu'
SECRET_KEY = 'VxQRvsETnYHsEZsWi9lGrLhhV5Q1slaX'
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
#读取照片
def get_file_content(filePath):
with open(filePath, 'rb') as fp:
return fp.read()
#绘制方块
def print_div(a,j):
img=cv.imread(a)
for i in range(j['person_num']):
cv.rectangle(img,(int(j['person_info'][i]['location']['left']),int(j['person_info'][i]['location']['top'])),
(int(j['person_info'][i]['location']['left']+j['person_info'][i]['location']['width']),int(j['person_info'][i]['location']['top']+j['person_info'][i]['location']['height'])),
(0,255,0),3)
cv.namedWindow("Image",cv.WINDOW_NORMAL)
cv.imshow("Image",img)
cv.waitKey(0)
cv.destroyAllWindows()
#选择功能
def select_power():
i=input('''
选择需要的功能
1.人体关键点识别
def check_image():
image = get_file_content('test1.jpg')
# ID setup
APP_ID = '19378067'
API_KEY = 'DAYZeonKGtfLoPXA3UFivyl7'
SECRET_KEY = 'mGt3Lomozy1G5tueq4Pu1kkQ4xwFhdC'
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
""" 调用人体关键点识别 """
keyword = client.bodyAttr(image)
print(keyword)
""" 打印json格式 """
print
json.dumps(keyword, sort_keys=True, indent=2)
print("person_num:%d" % (keyword['person_num']))
draw_image = cv2.imread('test1.jpg')
for i in range(0, keyword['person_num']):
# 识别人体的位置（x，y）
x1 = keyword['person_info'][i]['location']['left']
y1 = keyword['person_info'][i]['location']['top']
x2 = keyword['person_info'][i]['location']['width'] + x1
y2 = keyword['person_info'][i]['location']['height'] + y1
# 点位取整
round(x1)
round(x2)
round(y1)
round(y2)
# 打开图片并绘画出来人体框图
print("draw_image")
print("( %d , %d )" % (x1, y1))
print("( %d , %d )" % (x2, y2))
# 画出矩形
cv2.rectangle(draw_image, (int(x1), int(y1)), (int(x2), int(y2)),
(0, 255, 0), 4)
face_mask = keyword['person_info'][i]['attributes']['face_mask'][
'name']
mask1 = '无口罩'
mask2 = '戴口罩'
mask3 = '不确定'
if face_mask == mask1:
mask = "No mask"
if face_mask == mask2:
mask = "wear mask"
if face_mask == mask3:
mask = "uncertain"
print(face_mask)
person_name = 'person' + str(i) + mask
print(person_name)
# 标注文本
cv2.putText(draw_image, person_name, (int(x1), int(y1)),
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 3)
while (1):
cv2.imshow('person_detect', draw_image)
if cv2.waitKey(1) & 0xFF == ord('w'):
cv2.imwrite("test1.jpg", draw_image)
break
if cv2.getWindowProperty('person_detect', cv2.WND_PROP_AUTOSIZE) < 1:
break
cv2.destroyAllWindows()
def __init__(self, filePath):
target = configparser.ConfigParser()
target.read(filePath, encoding='utf-8-sig')
self.client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
else:
proxy_bus = {} # 请求dmm图片时传递的参数
# 初始化：jav网址，无论用户输不输人后面的斜杠 https://www.buscdn.work/
if not url_web.endswith('/'):
url_web += '/'
# 初始化：“是否重命名或创建独立文件夹”，还会受到“归类影片”影响。
if bool_classify: # 如果需要归类
if bool_classify_folder: # 并且是针对文件夹
bool_rename_folder = True # 那么必须重命名文件夹或者创建新的文件夹
else:
bool_rename_folder = False # 否则不会操作新文件夹
# 初始化 当前系统的路径分隔符 windows是“\”，linux和mac是“/”
sep = os.sep
# 准备工作：使用人体分析，我不清楚这是怎么和百度取得联系的，百度会怎样保持与javsdt的连接？
if bool_face:
client = AipBodyAnalysis(al_id, ai_ak, al_sk)
# 初始化：存放影片信息，用于给用户自定义各种命名
dict_nfo = {
'空格': ' ',
'车牌': 'ABC-123',
'标题': '无码标题',
'完整标题': '完整标题',
'导演': '无码导演',
'发行年月日': '1970-01-01',
'发行年份': '1970',
'月': '01',
'日': '01',
'片商': '无码片商',
'评分': '0',
'首个演员': '无码演员',
'全部演员': '无码演员',