def install_lib_classic(obj, libs):
"""Install libraries."""
if not obj.is_classic:
raise RuntimeError('Cannot manage classic libs in retail game folder')
obj.manager_lib_classic.install(libs)
obj.manager_lib_classic.export()
Manager().process_libs()
def test_drop():
print("Dropping table", table_test)
database.actions.drop(table_test)
with ENGINE.connect():
table = Table(table_test, META, autoload=True, autoload_with=ENGINE)
if not table.exists(bind=None):
print('TABLE DROP SUCCESS!')
else:
print(
"Something went wrong. Please rerun in DEBUG mod. DROP FAILED")
manager = Manager()
@manager.command()
def test_all():
test_creation()
test_insert()
test_remap_without_changes()
os.execl(sys.executable, 'python', '-m', 'tests.database_test',
'remap_all')
@manager.command()
def remap_all():
test_remap_with_all_changes()
os.execl(sys.executable, 'python', '-m', 'tests.database_test',
def main():
camera = cv2.VideoCapture(
path.join(path.dirname(__file__), "samples/traffic.flv"))
# camera = cv2.VideoCapture(path.join(path.dirname(__file__), "samples/human.avi"))
# camera = cv2.VideoCapture(0)
# KNN background subtractor
bs = cv2.createBackgroundSubtractorKNN()
# MOG subtractor
# bs = cv2.bgsegm.createBackgroundSubtractorMOG(history = background_frame)
# bs.setHistory(history)
# GMG
# bs = cv2.bgsegm.createBackgroundSubtractorGMG(initializationFrames = history)
cv2.namedWindow("视窗")
human_manager = Manager()
frames = 0
while True:
print(" -------------------- FRAME %d --------------------" % frames)
grabbed, frame = camera.read()
if (grabbed is False):
print("failed to grab frame.")
break
fgmask = bs.apply(frame)
# this is just to let the background subtractor build a bit of history
if frames < background_frame:
frames += 1
continue
th = cv2.threshold(fgmask.copy(), 127, 255, cv2.THRESH_BINARY)[1]
th = cv2.erode(th,
cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3)),
iterations=2)
dilated = cv2.dilate(th,
cv2.getStructuringElement(cv2.MORPH_ELLIPSE,
(8, 3)),
iterations=2)
image, contours, _ = cv2.findContours(dilated, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
found_filtered = []
# 根据面积过滤一次
for contour in contours:
area = cv2.contourArea(contour)
print("面积 %f" % area)
if area > min_contour_area:
found_filtered.append(contour)
# for ridx, o in enumerate(contours):
# for qidx, i in enumerate(contours):
# # i 在 o 内
# if ridx != qidx and is_inside(cv2.boundingRect(o), cv2.boundingRect(i)):
# break
# else:
# found_filtered.append(i)
detected_objects = []
for contour in found_filtered:
draw_person(frame, contour)
track_window = cv2.boundingRect(contour)
detected_objects.append(DetectedObject(track_window))
print("找到 %d 个物体" % len(detected_objects))
human_manager.process_detect_objs(detected_objects)
frames += 1
cv2.putText(frame, "count: %d" % human_manager.get_num(),
(int(20), int(20)), font, 1, (255, 255, 0), 1)
cv2.imshow("surveillance", frame)
cv2.waitKey(0) # 暂停
if cv2.waitKey(110) & 0xff == 27:
break
camera.release()
def install_lib(obj, libs):
"""Install libraries."""
obj.manager_lib.install(libs)
obj.manager_lib.export()
Manager().process_libs()
def _manage():
print('Modifying addons to fit each other...')
Manager().process()
Manager().process_libs()
print('Done!')
netG = Generator()
netD = Discriminator()
netG.to(device)
netD.to(device)
# optimizer
optimizerG = Adam(netG.parameters(), lr=0.0002, betas=(0.5, 0.999))
optimizerD = Adam(netD.parameters(), lr=0.0002, betas=(0.5, 0.999))
schedulerG = lr_scheduler.ExponentialLR(optimizerG, gamma=0.9)
schedulerD = lr_scheduler.ExponentialLR(optimizerD, gamma=0.9)
# criterion
criterion = torch.nn.BCELoss()
# manager
manager = Manager(netG, netD, optimizerG, optimizerD, criterion, device)
# generate
generated_save_path = './generated'
num_generated_image = 5
# epochs
epochs = 500
# load
start_epoch = 1
if os.path.exists('./log/lastest_checkpoint.log'):
lastest_checkpoint = torch.load('./log/lastest_checkpoint.log')
lastest_saved_epoch = lastest_checkpoint['epoch']
netG.load_state_dict(torch.load('./log/G-weight-{:0>8}.log'.format(lastest_saved_epoch)))
netD.load_state_dict(torch.load('./log/D-weight-{:0>8}.log'.format(lastest_saved_epoch)))
def test_merge_namespace(self):
new_manager = Manager()
new_manager.add_command(Command(name='new_command'))
manager.merge(new_manager, namespace='new_namespace')
self.assertIn('new_namespace.new_command', manager.commands)
