def __init__(self, **kwargs):
# the number of times the _get_command iterator has been run
self.iterations = 0
self.files_scanned = 0
self.files_optimised = 0
self.bytes_saved = 0
self.list_only = kwargs.get('list_only')
self.array_optimised_file = []
self.quiet = kwargs.get('quiet')
self.stdout = Scratch()
self.stderr = Scratch()
def __init__(self, **kwargs):
self.optimisers = {
#'PNG': OptimisePNG(**kwargs),
'JPEG': OptimiseJPG(**kwargs),
#'GIF': OptimiseGIF(**kwargs),
#'GIFGIF': OptimiseAnimatedGIF(**kwargs)
}
self.__files_scanned = 0
self.__start_time = time.time()
self.exclude = {}
for dir in kwargs.get('exclude'):
if len(dir) == 0:
continue
self.exclude[dir] = True
self.quiet = kwargs.get('quiet')
self.identify_mime = kwargs.get('identify_mime')
# setup tempfile for stdout and stderr
self.stdout = Scratch()
self.stderr = Scratch()
# 容差参数，主要用于让被抓物体固定不动后再去抓
ERROR = 0.005
MAX = 8
# 初始化
data = ''
lastdata = ''
ip_port = ('10.0.0.1', 9999) # 监听9999端口
sk = socket.socket(socket.AF_INET,socket.SOCK_DGRAM,0) # UDP协议
sk.bind(ip_port)
st = threading.Thread(target = listen, args = ())
st.start()
count = MAX
mutex = threading.Lock()
scratch = Scratch()
capture = cv2.VideoCapture(0)
ratio = real_width / img_width
cascade = cv2.CascadeClassifier('/Users/guliqi/Desktop/Classifier/xml/cascade.xml')
while True:
ret, frame = capture.read()
if data != '':
if data.upper() == b'COALA': # 抓考拉
gray = frame.cvtColor(frame, cv2.COLOR_BGR2GRAY)
kolas = cascade.detectMultiScale(gray, 2.4, 7)
objects = []
for (x, y, w, h) in kolas:
frame = cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
objects.append((x + w / 2, y + h / 2))
from scratch import Scratch
from scratch.translater import translate
sc = Scratch('Truth 21w4a.sb3')
print(translate(sc.analyze()['blockStat'], 'cn-lang.json'))
def setUp(self):
self.client = Scratch()
