def mlhw6p17():
trainD = readTrainData()
testD = readTestData()
# training
forest = randomForest(trainD)
# testing
result = testEachTreeInForest(forest,testD)
eouts = map(lambda r:r["err"],result)
eouts.sort()
print "histogram"
his = histogram(eouts)
# Show histogram
for key in his:
print "[%3d%%,%3d%%) |%s %d (%.0f%%)" % (key,key+1,"|"*his[key],his[key],float(his[key])*100/len(eouts))
for i in xrange(len(forest)):
ein = testForest(forest[0:i+1],trainD)
eout = testForest(forest[0:i+1],testD)
ein = ein["err"]
eout = eout["err"]
print "%d,%.4f,%.4f" % (i+1,ein,eout)
def mlhw6p16():
trainD = readTrainData()
testD = readTestData()
dt = CART(trainD)
travel(dt)
eintest = testing(dt, trainD)
print eintest
eouttest = testing(dt, testD)
print eouttest
def mlhw6p16():
trainD = readTrainData()
testD = readTestData()
dt = CART(trainD)
travel(dt)
eintest = testing(dt,trainD)
print eintest
eouttest = testing(dt,testD)
print eouttest
def mlhw6p10():
trainD = readTrainData()
testD = readTestData()
G, U = adaboost(trainD, 300)
print "testing..."
# P10/11
for i in range(1, 300):
ein = adaboostTest(trainD, G[0:i])
eout = adaboostTest(testD, G[0:i])
print "%03d,%.6f,%.6f" % (i, ein, eout)
def mlhw6p10():
trainD = readTrainData()
testD = readTestData()
G,U = adaboost(trainD,300)
print "testing..."
# P10/11
for i in range(1,300):
ein = adaboostTest(trainD,G[0:i])
eout = adaboostTest(testD,G[0:i])
print "%03d,%.6f,%.6f" % (i,ein,eout)
def main(argv=None):
q_in = Queue()
q_cam = Queue()
q_pred = Queue()
processes = []
p_inference = Process(target=run_inference, args=(q_in, q_cam, q_pred))
p_gui = Process(target=run_gui, args=(q_cam, q_pred))
if FLAGS.mode == "stream":
p_inference.start()
processes.append(p_inference)
p_gui.start()
processes.append(p_gui)
cap = cv2.VideoCapture(0)
while (True):
# Capture frame-by-frame
_, frame = cap.read()
if FLAGS.resize_image:
frame = cv2.resize(frame,
(FLAGS.image_width, FLAGS.image_height))
q_in.put(frame)
cap.release()
cv2.destroyAllWindows()
for p in processes:
p.join()
elif FLAGS.mode == 'video':
video_path = os.path.join(dir_path, FLAGS.path_to_video_input)
if not os.path.exists(video_path):
raise Exception(
"Error: unable to find video on provided path - %s" %
FLAGS.path_to_video_input)
p_inference.start()
processes.append(p_inference)
cap = cv2.VideoCapture(FLAGS.path_to_video_input)
total_frames = cap.get(cv2.CAP_PROP_FRAME_COUNT)
video_fps = cap.get(cv2.CAP_PROP_FPS)
print('Input video FPS: %d' % video_fps)
fourcc = cv2.VideoWriter_fourcc(*'DIVX')
if FLAGS.resize_image:
out_video = cv2.VideoWriter(
os.path.join(dir_path, FLAGS.path_to_video_output), fourcc,
video_fps, (FLAGS.image_width, FLAGS.image_height))
else:
image_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
image_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
out_video = cv2.VideoWriter(
os.path.join(dir_path, FLAGS.path_to_video_output), fourcc,
video_fps, (image_width, image_height))
frames_processed = 0
time_start = time.time()
while (cap.isOpened()):
ret, frame = cap.read()
if ret:
if FLAGS.resize_image:
frame = cv2.resize(frame,
(FLAGS.image_width, FLAGS.image_height))
q_in.put(frame)
time_start = time.time()
elif time.time() - time_start > 5:
break
while q_in.qsize() > 100:
sleep(0.2)
if not q_pred.empty():
frames_processed += 1
pred = q_pred.get()
out_video.write(pred)
print('Progress: %f %%' %
(100 * frames_processed / total_frames))
out_video.release()
elif FLAGS.mode == "test":
print('Loading test images...')
test_images_orig, file_names = utils.readTestData(
FLAGS.test_dir_input, FLAGS.input_size)
p_inference.start()
processes.append(p_inference)
for i in range(len(file_names)):
image = test_images_orig[i]
fname = file_names[i]
if FLAGS.resize_image:
image = cv2.resize(image,
(FLAGS.image_width, FLAGS.image_height))
q_in.put(image)
pred = q_pred.get(block=True)
cv2.imwrite(
os.path.join(FLAGS.test_dir_output, fname) + '.png', pred)
print('Image processed: %s' % fname)
else:
raise Exception('Error: unknown value for argument mode')
for p in processes:
p.terminate()
