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)