def takePhoto():
disp.font(disp.FONT_DejaVu40)
disp.clear()
disp.text(30, 110, 'Pose Please!', disp.WHITE)
utime.sleep(2)
disp.clear()
disp.text(40, 110, 'Ready GO!', disp.WHITE)
utime.sleep(1)
disp.clear()
i = 0
while (i < 15):
frame = ucamera.capture()
if frame != None:
disp.image(0, 0, frame, 0)
if (i < 5):
disp.text(150, 110, '3', disp.RED)
elif (i > 5 and i < 10):
disp.text(150, 110, '2', disp.RED)
elif (i > 10 and i < 15):
disp.text(150, 110, '1', disp.RED)
i += 1
utime.sleep(2)
disp.clear()
disp.text(60, 110, 'KaCha...', disp.WHITE)
# 上传拍摄的照片
image = oss.uploadContent(ACCESS_KEY, ACCESS_SECRET, OSS_ENDPOINT,
OSS_BUCKET, frame, "oss/face.jpg")
utime.sleep(2)
# 清除屏幕内容
disp.clear()
disp.text(20, 110, 'Upload Done!', disp.WHITE)
utime.sleep(2)
return image
def recognizePlateLicenceThread():
# 引用全局变量
global detected, plateNumber
# 创建AI对象
ai = uai.AI(uai.AI_ENGINE_ALIYUN, ACCESS_KEY, ACCESS_SECRET)
while True:
if frame != None:
# 上传图片到OSS
image = oss.uploadContent(ACCESS_KEY, ACCESS_SECRET, OSS_ENDPOINT,
OSS_BUCKET, frame, "oss/test.jpg")
if image != None:
# 进行车牌识别
resp = ai.recognizeLicensePlate(image)
# 解析识别结果
if (resp != None):
i = 0
while (i < len(resp)):
print(resp)
plateNumber = resp[i]['plateNumber']
plateType = resp[i]['plateType']
confidence = resp[i]['confidence']
plateTypeConfidence = resp[i]['plateTypeConfidence']
x = resp[i]['x']
y = resp[i]['y']
w = resp[i]['w']
h = resp[i]['h']
# 当得分 > 0.6，表示识别成功
if confidence > 0.6:
detected = True
# 休眠识别线程，切换到显示线程
utime.sleep(2)
else:
detected = False
i += 1
else:
detected = False
def main():
# 创建lcd display对象
global disp
disp = display.TFT()
disp.font(disp.FONT_Default)
# 连接网络
connect_wifi(SSID, PWD)
# 初始化摄像头, UART Rx PIN=33, TX PIN=32，M5STACK-CORE2上对应PORTA
ucamera.init('uart', 33, 32)
# 拍照上传人脸比对图片到OSS
compareFaceImage = takePhoto()
if (compareFaceImage == None):
print('take photo fail, please restart!')
disp.text(10, 110, 'Take Photo Fail, restart!', disp.WHITE)
return
# 创建AI对象
ai = uai.AI(uai.AI_ENGINE_ALIYUN, ACCESS_KEY, ACCESS_SECRET)
while True:
# 抓取一帧图像
frame = ucamera.capture()
if (frame != None):
# 显示图像
disp.image(0, 0, frame, 0)
# 设置显示字体
disp.font(disp.FONT_DejaVu18)
# 显示文字
disp.text(10, 30, 'Recognizing face...', disp.WHITE)
# 上传图片到OSS
image = oss.uploadContent(ACCESS_KEY, ACCESS_SECRET, OSS_ENDPOINT,
OSS_BUCKET, frame, "oss/test.jpg")
print('content: %s' % image)
if image != None:
# 抓取一帧图像
frame = ucamera.capture()
# 显示图像
disp.image(0, 0, frame, 0)
# 显示文字
disp.text(10, 30, 'Recognizing face...', disp.WHITE)
# 人脸识别
resp = ai.compareFace(image, compareFaceImage)
print(resp)
if (resp != None):
# 解析识别结果
confidence = resp['confidence']
x = resp['x']
y = resp['y']
w = resp['w']
h = resp['h']
# 置信度 > 60，表示识别成功
if confidence > 60:
# 清除屏幕内容
disp.clear()
# 设置文字字体
disp.font(disp.FONT_DejaVu40)
# 显示识别结果
disp.text(40, 90, 'Recognize', disp.RED)
disp.text(30, 130, 'successfully!', disp.RED)
print('Recognize successfully!!!')
utime.sleep(2)
# 释放当前帧内存
del frame
def main():
# 创建lcd display对象
global disp
disp = display.TFT()
disp.font(disp.FONT_Default)
# 连接网络
connect_wifi(SSID, PWD)
# 初始化摄像头, UART Rx PIN=33, TX PIN=32，M5STACK-CORE2上对应PORTA
ucamera.init('uart', 33, 32)
# 创建AI对象
ai = uai.AI(uai.AI_ENGINE_ALIYUN, ACCESS_KEY, ACCESS_SECRET)
while True:
# 抓取一帧图像
frame = ucamera.capture()
if (frame != None):
# 显示图像
disp.image(0, 0, frame, 0)
# 设置显示字体
disp.font(disp.FONT_DejaVu18)
# 显示文字
disp.text(10, 30, 'Recognizing face...', disp.WHITE)
# 上传图片到OSS
image = oss.uploadContent(ACCESS_KEY, ACCESS_SECRET, OSS_ENDPOINT,
OSS_BUCKET, frame, "oss/test.jpg")
print('content: %s' % image)
if image != None:
# 抓取一帧图像
frame = ucamera.capture()
# 显示图像
disp.image(0, 0, frame, 0)
# 显示文字
disp.text(10, 30, 'Detecting Pedestrian...', disp.WHITE)
# 人体检测
resp = ai.detectPedestrian(image)
print(resp)
if (resp != None):
i = 0
# 解析识别结果
while (i < len(resp)):
type = resp[i]['type']
score = resp[i]['score']
x = resp[i]['x']
y = resp[i]['y']
w = resp[i]['w']
h = resp[i]['h']
# 当得分 > 0.6，表示识别成功
if score > 0.6:
# 清除屏幕内容
disp.clear()
# 设置文字字体
disp.font(disp.FONT_DejaVu40)
# 显示识别结果
disp.text(30, 90, 'Pedestrian', disp.RED)
disp.text(30, 130, 'Detected!!!', disp.RED)
print('Pedestrian Detected!!!')
utime.sleep(2)
i += 1
# 释放当前帧内容
del frame
def main():
# 创建lcd display对象
global disp
disp = display.TFT()
disp.font(disp.FONT_Default)
# 连接网络
connect_wifi(SSID, PWD)
# 初始化摄像头, UART Rx PIN=33, TX PIN=32，M5STACK-CORE2上对应PORTA
ucamera.init('uart', 33, 32)
# 创建AI对象
ai = uai.AI(uai.AI_ENGINE_ALIYUN, ACCESS_KEY, ACCESS_SECRET)
while True:
# 抓取一帧图像
frame = ucamera.capture()
if (frame != None):
# 显示图像
disp.image(0, 0, frame, 0)
# 设置显示字体
disp.font(disp.FONT_DejaVu18)
# 显示文字
disp.text(10, 30, 'Recognizing face...', disp.WHITE)
# 上传图片到OSS
image = oss.uploadContent(ACCESS_KEY, ACCESS_SECRET, OSS_ENDPOINT,
OSS_BUCKET, frame, "oss/test.jpg")
print('content: %s' % image)
#image = 'http://viapi-test.oss-cn-shanghai.aliyuncs.com/viapi-3.0domepic/imagerecog/DetectFruits/DetectFruits1.jpg'
if image != None:
frame = ucamera.capture()
disp.image(0, 0, frame, 0)
disp.text(10, 30, 'Detecting Fruits...', disp.WHITE)
# 水果识别
resp = ai.detectFruits(image)
print(resp)
if (resp != None):
i = 0
# 解析识别结果
while (i < len(resp)):
name = resp[i]['name']
score = resp[i]['score']
x = resp[i]['x']
y = resp[i]['y']
w = resp[i]['w']
h = resp[i]['h']
# 当得分 > 0.6，表示识别成功
if score > 0.6:
name = translateName(name)
# 清除屏幕内容
disp.clear()
# 设置文字字体
disp.font(disp.FONT_DejaVu40)
# 显示识别结果
disp.text(40, 80, name, disp.RED)
disp.text(40, 120, 'Deteted!!!', disp.RED)
utime.sleep(2)
i += 1
# 释放当前帧内存
del frame
def main():
# 创建lcd display对象
global disp
disp = display.TFT()
disp.font(disp.FONT_Default)
# 连接网络
connect_wifi(SSID, PWD)
# 初始化摄像头, UART Rx PIN=33, TX PIN=32，M5STACK-CORE2上对应PORTA
ucamera.init('uart', 33, 32)
# 创建AI对象
ai = uai.AI(uai.AI_ENGINE_ALIYUN, ACCESS_KEY, ACCESS_SECRET)
while True:
# 抓取一帧图像
frame = ucamera.capture()
if (frame != None):
# 显示图像
disp.image(0, 0, frame, 0)
# 设置显示字体
disp.font(disp.FONT_DejaVu18)
# 显示文字
disp.text(10, 30, 'Recognizing face...', disp.WHITE)
# 上传图片到OSS
image = oss.uploadContent(ACCESS_KEY, ACCESS_SECRET, OSS_ENDPOINT, OSS_BUCKET, frame, "oss/test.jpg")
print('content: %s' %image)
#image = 'http://viapi-test.oss-cn-shanghai.aliyuncs.com/viapi-3.0domepic/imagerecog/DetectFruits/DetectFruits1.jpg'
if image != None:
frame = ucamera.capture()
disp.image(0, 0, frame, 0)
disp.text(0, 30, 'Recognizing License Plate...', disp.WHITE)
# 车牌识别
resp = ai.recognizeLicensePlate(image)
print(resp)
if (resp != None):
i = 0
# 解析识别结果
while (i < len(resp)):
plateNumber = resp[i]['plateNumber']
plateType = resp[i]['plateType']
confidence = resp[i]['confidence']
plateTypeConfidence = resp[i]['plateTypeConfidence']
x = resp[i]['x']
y = resp[i]['y']
w = resp[i]['w']
h = resp[i]['h']
# 当置信度 > 0.6，表示识别成功
if confidence > 0.6:
# 清除屏幕内容
disp.clear()
# 设置文字字体
disp.font(disp.FONT_DejaVu40)
# 显示识别的车牌号
disp.text(25, 90, plateNumber, disp.RED)
disp.text(25, 130, 'Deteted!!!', disp.RED)
utime.sleep(2)
else:
print('Recognizing license plate...')
i += 1
else:
print('Recognizing license plate...')
# 释放当前帧内存
del frame