Python queue.empty方法代碼示例

# 需要導入模塊: import queue [as 別名]
# 或者: from queue import empty [as 別名]
def decode(queue, log_probs, decoder, index2label):
    while not queue.empty():
        try:
            video = queue.get(timeout = 3)
            score, labels, segments = decoder.decode( log_probs[video] )
            # save result
            with open('results/' + video, 'w') as f:
                f.write( '### Recognized sequence: ###\n' )
                f.write( ' '.join( [index2label[s.label] for s in segments] ) + '\n' )
                f.write( '### Score: ###\n' + str(score) + '\n')
                f.write( '### Frame level recognition: ###\n')
                f.write( ' '.join( [index2label[l] for l in labels] ) + '\n' )
        except queue.Empty:
            pass


### read label2index mapping and index2label mapping ########################### 

# 需要導入模塊: import queue [as 別名]
# 或者: from queue import empty [as 別名]
def monte_carlo_grammar(dataset, mean_lengths, index2label, max_paths = 1000):
    monte_carlo_grammar = []
    sil_length = mean_lengths[0]
    while len(monte_carlo_grammar) < max_paths:
        for video in dataset.videos():
            action_set = dataset.action_set[video] - set([0]) # exclude SIL
            seq = []
            while sum( [ mean_lengths[label] for label in seq ] ) + 2 * sil_length < dataset.length(video):
                seq.append( random.choice(list(action_set)) )
            if len(seq) == 0: # omit empty sequences
                continue
            monte_carlo_grammar.append('SIL ' + ' '.join( [index2label[idx] for idx in seq] ) + ' SIL')
    random.shuffle(monte_carlo_grammar)
    return monte_carlo_grammar[0:max_paths]


################################################################################
### TRAINING                                                                 ###
################################################################################ 

# 需要導入模塊: import queue [as 別名]
# 或者: from queue import empty [as 別名]
def decode(queue, log_probs, decoder, index2label):
    while not queue.empty():
        try:
            video = queue.get(timeout = 3)
            score, labels, segments = decoder.decode( log_probs[video] )
            # save result
            with open('results/' + video, 'w') as f:
                f.write( '### Recognized sequence: ###\n' )
                f.write( ' '.join( [index2label[s.label] for s in segments] ) + '\n' )
                f.write( '### Score: ###\n' + str(score) + '\n')
                f.write( '### Frame level recognition: ###\n')
                f.write( ' '.join( [index2label[l] for l in labels] ) + '\n' )
        except queue.Empty:
            pass



################################################################################
### MAIN                                                                     ###
################################################################################ 

# 需要導入模塊: import queue [as 別名]
# 或者: from queue import empty [as 別名]
def mySubscriber(queue):
  while not queue.empty():
    item = queue.get()
    if item is None:
      break
    print("{} removed {} from the queue".format(threading.current_thread(), item))
    queue.task_done()
    time.sleep(1) 

# 需要導入模塊: import queue [as 別名]
# 或者: from queue import empty [as 別名]
def mySubscriber(queue):
  while not queue.empty():
    item = queue.get()
    if item is None:
      break
    print("{} removed {} from the queue".format(threading.current_thread(), item))
    queue.task_done() 

# 需要導入模塊: import queue [as 別名]
# 或者: from queue import empty [as 別名]
def mySubscriber(queue):
  time.sleep(1)
  while not queue.empty():
    item = queue.get()
    if item is None:
      break
    print("{} removed {} from the queue".format(threading.current_thread(), item))
    queue.task_done() 

# 需要導入模塊: import queue [as 別名]
# 或者: from queue import empty [as 別名]
def worker(c):
    thread = threading.currentThread()
    if queue.empty():
        return
    json_file = queue.get()
    config = json_file.replace(".json","")
    c.run(config)
    worker(c)
    queue.task_done()
    logging.debug('Done') 

# 需要導入模塊: import queue [as 別名]
# 或者: from queue import empty [as 別名]
def time_connection(self, server, queue):
        s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
        try:
            s.connect(server)
            print("Conncted to " + str(server))
            if queue.empty:
                queue.put(server)
            s.close()
        except:
            print(str(server) + "does not respond") 

# 需要導入模塊: import queue [as 別名]
# 或者: from queue import empty [as 別名]
def async_write(buffer=[]):
    item = queue.get()
    buffer.append(item)
    if len(buffer) > 500 or queue.empty():
        log.debug('Processing {} queue items.'.format(len(buffer)))
        with db.transaction():
            write_buffer(buffer)
        buffer.clear() 

# 需要導入模塊: import queue [as 別名]
# 或者: from queue import empty [as 別名]
def decode(queue, log_probs, decoder, index2label):
    while not queue.empty():
        try:
            video = queue.get(timeout = 3)
            score, labels, segments = decoder.decode( log_probs[video] )
            # save result
            with open('results/' + video, 'w') as f:
                f.write( '### Recognized sequence: ###\n' )
                f.write( ' '.join( [index2label[s.label] for s in segments] ) + '\n' )
                f.write( '### Score: ###\n' + str(score) + '\n')
                f.write( '### Frame level recognition: ###\n')
                f.write( ' '.join( [index2label[l] for l in labels] ) + '\n' )
        except queue.Empty:
            pass 

# 需要導入模塊: import queue [as 別名]
# 或者: from queue import empty [as 別名]
def stn_decode(queue, log_probs, decoder, index2label, window, step):
    while not queue.empty():
        try:
            video = queue.get(timeout = 3)
            score, labels, segments = decoder.decode( log_probs[video])
#             cum_segments = np.array([segment.length for segment in segments])
#             cum_segments = np.cumsum(cum_segments)
#             print('segments', cum_segments)
#             print('labels', len(labels))
#             labels = np.array(labels)
            trancript = [s.label for s in segments]
#             print('trancript', trancript)
            stn_score, stn_labels, stn_segments = decoder.stn_decode( log_probs[video], segments, trancript, window, step)
#             stn_labels2 =  [s.label for s in stn_segments]
#             print('stn_labels2', stn_labels2)
#             print('stn_labels', len(stn_labels))
#             cum_segments = np.array([stn_segment.length for stn_segment in stn_segments])
#             cum_segments = np.cumsum(cum_segments)
#             print('stn_segments', cum_segments)
            # save result
            with open('results/' + video, 'w') as f:
                f.write( '### Recognized sequence: ###\n' )
                f.write( ' '.join( [index2label[s.label] for s in stn_segments] ) + '\n' )
                f.write( '### Score: ###\n' + str(stn_score) + '\n')
                f.write( '### Frame level recognition: ###\n')
                f.write( ' '.join( [index2label[l] for l in stn_labels] ) + '\n' )
        except queue.Empty:
            pass


### read label2index mapping and index2label mapping ########################### 

# 需要導入模塊: import queue [as 別名]
# 或者: from queue import empty [as 別名]
def _dequeue(self, queue):
        """Removes queue entries till an alive reference was found.
        The referenced image holder will be returned in this case.
        Otherwise if there wasn't found any alive reference
        None will be returned.

        Args:
            queue (queue.Queue): the queue to operate on

        Returns:
            tuple of (ImageHolder, tuple of (width: int, height: int),
                      PostLoadImageProcessor):
                an queued image holder or None, upper bound size or None,
                the post load image processor or None
        """
        holder_reference = None
        image_holder = None
        upper_bound_size = None
        post_load_processor = None

        while not queue.empty():
            holder_reference, upper_bound_size, post_load_processor = \
                queue.get_nowait()
            image_holder = holder_reference and holder_reference()
            if (holder_reference is None or
                    image_holder is not None):
                break

        return image_holder, upper_bound_size, post_load_processor 

# 需要導入模塊: import queue [as 別名]
# 或者: from queue import empty [as 別名]
def __wait_for_main_work(self):
        """Waits till all queued high priority entries were processed."""
        if not self.__queue.empty():
            with self.__waiter_low_priority:
                if not self.__queue.empty():
                    self.__waiter_low_priority.wait() 

# 需要導入模塊: import queue [as 別名]
# 或者: from queue import empty [as 別名]
def __notify_main_work_done(self):
        """Notifies waiting threads that
        all queued high priority entries were processed.
        """
        if self.__queue.empty():
            with self.__waiter_low_priority:
                if self.__queue.empty():
                    self.__waiter_low_priority.notify_all()