N0 = 2048 N1 = 1000 N2 = 500 N3 = 100 num_classes = len(classes) init_lr = 0.0001 num_epochs = 3 problem_type = 'm0' criterion = loss_m0(1.0) # DATA # datasets real_data = MultibinImages(augmented_path, 'real', problem_type, kmeans_file) render_data = MultibinImages(render_path, 'render', problem_type, kmeans_file) test_data = Pascal3dAll(pascal3d_path, 'test') # setup data loaders real_loader = DataLoader(real_data, batch_size=4, shuffle=True, num_workers=num_workers, pin_memory=True, collate_fn=my_collate) render_loader = DataLoader(render_data, batch_size=4, shuffle=True, num_workers=num_workers, pin_memory=True, collate_fn=my_collate) test_loader = DataLoader(test_data, batch_size=32, collate_fn=my_collate) print('Real: {0} \t Render: {1} \t Test: {2}'.format(len(real_loader),
ndim = 4 num_classes = len(classes) if not args.multires: criterion = RelaXedProbabilisticLossQ(1.0, kmeans_file, geodesic_loss(reduce=False).cuda()) else: criterion = RelaXedProbabilisticMultiresLossQ( 1.0, kmeans_file, geodesic_loss(reduce=False).cuda()) # DATA # datasets real_data = XPBDGeneratorQ(args.augmented_path, 'real', kmeans_file) render_data = XPBDGeneratorQ(args.render_path, 'render', kmeans_file) test_data = Pascal3dAll(args.pascal3d_path, 'test', 'quaternion') # setup data loaders real_loader = DataLoader(real_data, batch_size=args.num_workers, shuffle=True, num_workers=args.num_workers, pin_memory=True, collate_fn=my_collate) render_loader = DataLoader(render_data, batch_size=args.num_workers, shuffle=True, num_workers=args.num_workers, pin_memory=True, collate_fn=my_collate) test_loader = DataLoader(test_data, batch_size=32, collate_fn=my_collate) print('Real: {0} \t Render: {1} \t Test: {2}'.format(len(real_loader),
kmeans = pickle.load(open(kmeans_file, 'rb')) kmeans_dict = kmeans.cluster_centers_ num_clusters = kmeans.n_clusters # relevant variables ndim = 3 num_classes = len(classes) criterion1 = SimpleLoss(args.alpha) criterion2 = GeodesicLoss(args.alpha, kmeans_file, geodesic_loss().cuda()) # DATA # datasets real_data = GBDGenerator(args.augmented_path, 'real', kmeans_file) render_data = GBDGenerator(args.render_path, 'render', kmeans_file) test_data = Pascal3dAll(args.pascal3d_path, 'val') # setup data loaders real_loader = DataLoader(real_data, batch_size=args.num_workers, shuffle=True, num_workers=args.num_workers, pin_memory=True, collate_fn=my_collate) render_loader = DataLoader(render_data, batch_size=args.num_workers, shuffle=True, num_workers=args.num_workers, pin_memory=True, collate_fn=my_collate) test_loader = DataLoader(test_data, batch_size=32, collate_fn=my_collate) print('Real: {0} \t Render: {1} \t Test: {2}'.format(len(real_loader),
kmeans = pickle.load(open(kmeans_file, 'rb')) kmeans_dict = kmeans.cluster_centers_ num_clusters = kmeans.n_clusters # relevant variables ndim = 3 num_classes = len(classes) criterion1 = SimpleLoss(args.alpha) criterion2 = GeodesicLoss(args.alpha, kmeans_file, geodesic_loss().cuda()) # DATA # datasets real_data = GBDGenerator(args.augmented_path, 'real', kmeans_file) render_data = GBDGenerator(args.render_path, 'render', kmeans_file) test_data = Pascal3dAll(args.pascal3d_path, 'test') # setup data loaders real_loader = DataLoader(real_data, batch_size=args.num_workers, shuffle=True, num_workers=args.num_workers, pin_memory=True, collate_fn=my_collate) render_loader = DataLoader(render_data, batch_size=args.num_workers, shuffle=True, num_workers=args.num_workers, pin_memory=True, collate_fn=my_collate) test_loader = DataLoader(test_data, batch_size=32, collate_fn=my_collate) print('Real: {0} \t Render: {1} \t Test: {2}'.format(len(real_loader), len(render_loader), len(test_loader))) if np.isinf(args.max_iterations): max_iterations = min(len(real_loader), len(render_loader)) else: max_iterations = args.max_iterations # my_model if not args.multires: model = OneBinDeltaModel(args.feature_network, num_classes, num_clusters, args.N0, args.N1, args.N2, ndim) else:
# relevant variables num_workers = 4 N0 = 2048 N1 = 1000 N2 = 500 num_classes = len(classes) init_lr = 0.0001 num_epochs = 3 num_clusters = kmeans.n_clusters kmeans_dict = kmeans.cluster_centers_ # DATA # datasets real_data = GBDGenerator(augmented_path, 'real', kmeans_file) render_data = GBDGenerator(render_path, 'render', kmeans_file) test_data = Pascal3dAll(pascal3d_path, 'val') # setup data loaders real_loader = DataLoader(real_data, batch_size=4, shuffle=True, num_workers=num_workers, pin_memory=True, collate_fn=my_collate) render_loader = DataLoader(render_data, batch_size=4, shuffle=True, num_workers=num_workers, pin_memory=True, collate_fn=my_collate) test_loader = DataLoader(test_data, batch_size=32, collate_fn=my_collate) print('Real: {0} \t Render: {1} \t Test: {2}'.format(len(real_loader),