VLadImirluren
commented
7 months ago Sure, here is our old config for ModelNet40. It does not support the current version of PCR, but you can edit it to make it support the released version. Also, you need to remove the decoder of PTv2 to do object classification, and you can refer
/pcr/model/point_transformer/point_transformer_cls.py:_base_ = [ '../_base_/datasets/modelnet40.py', '../_base_/schedulers/multi-step_sgd.py', '../_base_/tests/classification.py', '../_base_/default_runtime.py' ] train_gpu = [2, 3] batch_size = 16 batch_size_val = 16 metric = "allAcc" model = dict( type="pt2v2m2c", in_channels=6, num_classes=40, channels=(48, 96, 192, 384, 512), embed_depth=1, embed_num_samples=8, embed_group=4, enc_depths=(2, 2, 6, 2), dec_depths=(1, 1, 1, 1), down_stride=(4, 4, 4, 4), down_num_samples=(0.05, 0.1, 0.2, 0.4), # Gird Size attn_groups=(12, 24, 48, 64), attn_num_samples=(16, 16, 16, 16), attn_qkv_bias=True, mlp_channels_expend_ratio=1., drop_rate=0., attn_drop_rate=0., drop_path_rate=0.3, ) epochs = 100 start_epoch = 0 optimizer = dict(type='SGD', lr=0.05, momentum=0.9, weight_decay=0.0001, nesterov=True) scheduler = dict(type='MultiStepLR', milestones=[epochs * 0.6, epochs * 0.8], steps_per_epoch=1, gamma=0.1) # dataset settings dataset_type = "ModelNetDataset" data_root = "data/modelnet40_normal_resampled" cache_data = False names = ["airplane", "bathtub", "bed", "bench", "bookshelf", "bottle", "bowl", "car", "chair", "cone", "cup", "curtain", "desk", "door", "dresser", "flower_pot", "glass_box", "guitar", "keyboard", "lamp", "laptop", "mantel", "monitor", "night_stand", "person", "piano", "plant", "radio", "range_hood", "sink", "sofa", "stairs", "stool", "table", "tent", "toilet", "tv_stand", "vase", "wardrobe", "xbox"] data = dict( num_classes=40, ignore_label=-1, # dummy ignore names=names, train=dict( type=dataset_type, split="train", data_root=data_root, class_names=names, transform=[ dict(type="NormalizeCoord"), # dict(type="CenterShift", apply_z=True), # dict(type="RandomRotate", angle=[-1, 1], axis='z', center=[0, 0, 0], p=0.5), # dict(type="RandomRotate", angle=[-1/24, 1/24], axis='x', p=0.5), # dict(type="RandomRotate", angle=[-1/24, 1/24], axis='y', p=0.5), dict(type="RandomScale", scale=[0.9, 1.1]), dict(type="RandomShift", shift=[0.2, 0.2, 0.2]), # dict(type="RandomFlip", p=0.5), # dict(type="RandomJitter", sigma=0.005, clip=0.02), # dict(type="ElasticDistortion", distortion_params=[[0.2, 0.4], [0.8, 1.6]]), # dict(type="Voxelize", voxel_size=0.01, hash_type='fnv', mode='train'), # dict(type="SphereCrop", point_max=10000, mode='random'), # dict(type="CenterShift", apply_z=True), dict(type="ShufflePoint"), dict(type="ToTensor") ], loop=2, test_mode=False, ), val=dict( type=dataset_type, split="test", data_root=data_root, class_names=names, transform=[ dict(type="NormalizeCoord"), dict(type="ToTensor") ], loop=1, test_mode=False, ), test=dict( type=dataset_type, split="test", data_root=data_root, class_names=names, transform=[ dict(type="NormalizeCoord"), dict(type="ToTensor") ], loop=1, test_mode=True, test_cfg=dict( ) ), ) criteria = [ dict(type="CrossEntropyLoss", loss_weight=1.0, ignore_index=data["ignore_label"]) ]
Since I have just come into contact with this project, there are still many things that I am not familiar with..Could you please update this config file to the latest version of pointcept.Thanks~
Gofinge
Sure, here is our old config for ModelNet40. It does not support the current version of PCR, but you can edit it to make it support the released version. Also, you need to remove the decoder of PTv2 to do object classification, and you can refer
/pcr/model/point_transformer/point_transformer_cls.py: