def main(): s1 = OrderedStage(f2, size=2) s2 = OrderedStage(f3) s1.link(s2) p = Pipeline(s1) def f1(): for task in [1, 2, 3, 4, 5, None]: p.put(task) f1()
def main(): stage1 = OrderedStage(increment, 3) stage2 = OrderedStage(double, 3) pipe = Pipeline(stage1.link(stage2)) for number in range(10): pipe.put(number) pipe.put(None) for result in pipe.results(): print(result)
def main(): stage1 = OrderedStage(increment) stage2 = OrderedStage(double) stage3 = OrderedStage(echo) stage1.link(stage2) stage2.link(stage3) pipe = Pipeline(stage1) for number in range(10): pipe.put(number) pipe.put(None)
def main(): s1 = FilterStage( (OrderedStage(pass_thru), ), max_tasks=1, ) p1 = Pipeline(s1) p2 = Pipeline(OrderedStage(Pull(p1))) p2.put(True) for number in range(10): p1.put(number) time.sleep(0.010) p1.put(None) p2.put(None)
def main(): pipe = Pipeline(OrderedStage(echo, 2)) for number in range(12): pipe.put(number) time.sleep(0.010) pipe.put(None)
def main(): stage = FilterStage((OrderedStage(echo), ), max_tasks=2) pipe = Pipeline(stage) for number in range(12): pipe.put(number) time.sleep(0.010) pipe.put(None)
def main(): pipe = Pipeline(OrderedStage(yes, disable_result=True)) for number in range(10): pipe.put(number) pipe.put(None) for result in pipe.results(): print(result)
def extract_feat_from_FCL(): input_shape = (224, 224, 3) model = VGG16(weights='imagenet', input_shape=(input_shape[0], input_shape[1], input_shape[2]), pooling='max', include_top=True) t1 = time.time() layer_name = "fc2" intermediate_layer_model = Model( inputs=model.input, outputs=model.get_layer(layer_name).output) list = get_imlist("img_cut") stage1 = OrderedStage(send_batch) stage2 = OrderedStage(create_bag_of_window) stage1.link(stage2) pipe = Pipeline(stage1) batch_size = 1 total_batch = math.ceil(len(list) / batch_size) for p in range(total_batch): v = list[p * batch_size:(p + 1) * batch_size] print("Batch number %s" % p) pipe.put(v) pipe.put(None) for result in pipe.results(): t0 = time.time() print("Predicting...") feature_tensor = intermediate_layer_model.predict( np.vstack((r for r in result))) t1 = time.time() print("time to predict : %ss" % (t1 - t0)) # gc.collect() print(feature_tensor.shape) del result # feature_tensor = intermediate_layer_model.predict_generator(generator=generator_, steps=1, max_queue_size=1) t2 = time.time() print("Total time to predict: " + str(t2 - t1)) print(feature_tensor.shape) return feature_tensor
def main(): stage = OrderedStage(yes, 4, disable_result=True) pipe = Pipeline(stage) for number in range(10): pipe.put(number) pipe.put(None) count = 0 for _ in pipe.results(): count += 1 print(count)
def main(): stage1 = Stage(Accumulator) stage2 = OrderedStage(echo, 50) stage1.link(stage2) pipe = Pipeline(stage1) size = 1000 prices = np.linspace(0, np.pi * 10, size) prices = np.sin(prices) + 1 for price in prices: pipe.put(price) pipe.put(None)
def process(): list = get_imlist("img_cut/") stage1 = OrderedStage(send_batch) stage2 = OrderedStage(create_bag_of_window) stage3 = OrderedStage(last_stage) stage1.link(stage2) stage2.link(stage3) pipe = Pipeline(stage1) batch_size = 20 total_batch = math.ceil(len(list) / batch_size) for p in range(total_batch): v = list[p * batch_size:(p + 1) * batch_size] print("Batch number %s" % p) pipe.put(v) pipe.put(None)
from mpipe import OrderedStage, Pipeline def increment(value): return value + 1 def double(value): return value * 2 stage1 = OrderedStage(increment, 3) stage2 = OrderedStage(double, 3) pipe = Pipeline(stage1.link(stage2)) for number in range(10): pipe.put(number) pipe.put(None) for result in pipe.results(): print(result)
from mpipe import OrderedStage, Pipeline def increment(value): return value + 1 def double(value): return value * 2 stage1 = OrderedStage(increment) stage2 = OrderedStage(double) stage1.link(stage2) pipe = Pipeline(stage1) for number in range(10): pipe.put(number) pipe.put(None) for result in pipe.results(): print(result)
from mpipe import OrderedStage, UnorderedStage, Pipeline def increment(value): return value + 1 def double(value): return value * 2 stage1 = UnorderedStage(increment, 3) stage2 = OrderedStage(double, 3) stage1.link(stage2) pipe = Pipeline(stage1) for number in range(10): pipe.put(number) pipe.put(None) for result in pipe.results(): print(result)
"""Solution for http://stackoverflow.com/questions/8277715""" from mpipe import OrderedStage, Pipeline def f2(value): return value * 2 def f3(value): print(value) s1 = OrderedStage(f2, size=2) s2 = OrderedStage(f3) s1.link(s2) p = Pipeline(s1) def f1(): for task in [1,2,3,4,5,None]: p.put(task) f1()
from mpipe import OrderedStage, UnorderedStage, Pipeline def increment(value): return value + 1 def double(value): return value * 2 stage1 = OrderedStage(increment, 3) stage2 = UnorderedStage(double, 3) stage1.link(stage2) pipe = Pipeline(stage1) for number in range(10): pipe.put(number) pipe.put(None) for result in pipe.results(): print(result)
from mpipe import OrderedWorker, Stage, OrderedStage, Pipeline last10 = deque() junk = 'http://ws.cdyne.com/delayedstockquote/delayedstockquote.asmx/GetQuote?StockSymbol=fac&LicenseKey=0' j = 'http://www.google.com/ig/api?stock=AAPL' class Accumulator(OrderedWorker): def doTask(self, price): if last10: if price < min(last10): self.putResult(price) last10.append(price) if len(last10) > 10: last10.popleft() def echo(value): print('value = {0}'.format(value)) stage1 = Stage(Accumulator) stage2 = OrderedStage(echo, 50) stage1.link(stage2) pipe = Pipeline(stage1) SIZE = 1000 prices = np.linspace(0, np.pi*10, SIZE) prices = np.sin(prices) + 1 for price in prices: pipe.put(price) pipe.put(None)
import time from mpipe import OrderedStage, FilterStage, Pipeline def echo(value): print(value) time.sleep(0.013) return value stage = FilterStage((OrderedStage(echo), ), max_tasks=2) pipe = Pipeline(stage) for number in range(12): pipe.put(number) time.sleep(0.010) pipe.put(None)
from mpipe import OrderedStage, Pipeline def increment(value): return value + 1 def double(value): return value * 2 def echo(value): print(value) stage1 = OrderedStage(increment) stage2 = OrderedStage(double) stage3 = OrderedStage(echo) stage1.link(stage2) stage2.link(stage3) pipe = Pipeline(stage1) for number in range(10): pipe.put(number) pipe.put(None)
results = np.zeros((1280, 800)) # prefilled array i = 0 counter = 0 feature_detect = False #t_end = time.time()+1 #while(time.time()<t_end): # try: for i in range(max_frames): frame = camera.capture(encoding="raw") ls[i] = frame.as_array.reshape(1280, 800) print(i) t.start() background = ls[0] current = ls[1] stage1 = OrderedStage(increment, ls_shape[0] * ls_shape[1]) pipe = Pipeline(stage1) for i in range(ls_shape[0]): for j in range(ls_shape[1]): pipe.put(background[i][j], current[i][j]) pipe.put(None) for result in pipe.results(): counter += results if (counter > pix_threshold): feature_detect = True t.stop() camera.close_camera() if (feature_detect): for i in range(max_frames):
from mpipe import OrderedStage, FilterStage, Pipeline import time def echo(value): print(value) time.sleep(0.0125) return value pipe1 = Pipeline(FilterStage((OrderedStage(echo), ), max_tasks=2)) def pull(task): for result in pipe1.results(): pass pipe2 = Pipeline(OrderedStage(pull)) pipe2.put(True) pipe2.put(None) for number in range(10): pipe1.put(number) time.sleep(0.0100) pipe1.put(None)
import time from mpipe import OrderedStage, FilterStage, Pipeline def passthru(value): time.sleep(0.013) return value s1 = FilterStage( (OrderedStage(passthru), ), max_tasks=1, cache_results=True, ) p1 = Pipeline(s1) def pull(task): for task, result in p1.results(): if result: print('{0} {1}'.format(task, result[0])) p2 = Pipeline(OrderedStage(pull)) p2.put(True) for number in range(10): p1.put(number) time.sleep(0.010) p1.put(None)
from mpipe import OrderedStage, Pipeline def yes(value): return value pipe = Pipeline(OrderedStage(yes, disable_result=True)) for number in range(10): pipe.put(number) pipe.put(None) for result in pipe.results(): print(result)
from mpipe import OrderedStage, Pipeline def yes(value): return value stage = OrderedStage(yes, 4, disable_result=True) pipe = Pipeline(stage) for number in range(10): pipe.put(number) pipe.put(None) count = 0 for result in pipe.results(): count += 1 print(count)
import time from mpipe import OrderedStage, Pipeline def echo(value): print(value) time.sleep(0.013) return value pipe = Pipeline(OrderedStage(echo)) for number in range(12): pipe.put(number) time.sleep(0.010) pipe.put(None)
"""Solution for http://stackoverflow.com/questions/8277715""" from mpipe import OrderedStage, Pipeline def f2(value): return value * 2 def f3(value): print(value) s1 = OrderedStage(f2, size=2) s2 = OrderedStage(f3) s1.link(s2) p = Pipeline(s1) def f1(): for task in [1, 2, 3, 4, 5, None]: p.put(task) f1()