Download Volt_experiments/instance_segmentation/scenefun3d_volt_base/config.py from KadirYilmaz/Volt: direct link, hf CLI and curl.
- Browser
- Download file 10.9 kB
-
https://huggingface.co/KadirYilmaz/Volt/resolve/main/Volt_experiments/instance_segmentation/scenefun3d_volt_base/config.py
- Command line
-
hf download hf://KadirYilmaz/Volt/Volt_experiments/instance_segmentation/scenefun3d_volt_base/config.py
-
curl -L -o config.py https://huggingface.co/KadirYilmaz/Volt/resolve/main/Volt_experiments/instance_segmentation/scenefun3d_volt_base/config.py
10.9 kB
| weight = 'weights/volt-base-scannet200.pth' | |
| resume = False | |
| evaluate = True | |
| test_only = False | |
| seed = 29937722 | |
| save_path = 'exp/scenefun3d/2026-09-15_164017' | |
| num_worker = 128 | |
| batch_size = 16 | |
| gradient_accumulation_steps = 1 | |
| batch_size_val = None | |
| batch_size_test = None | |
| epoch = 1600 | |
| eval_epoch = 100 | |
| clip_grad = None | |
| use_ema = True | |
| ema_decay = 0.999 | |
| dataset_ratios = None | |
| sync_bn = False | |
| enable_amp = True | |
| amp_dtype = 'float16' | |
| empty_cache = False | |
| empty_cache_per_epoch = False | |
| find_unused_parameters = False | |
| enable_wandb = True | |
| wandb_project = 'Volt' | |
| wandb_key = None | |
| mix_prob = 0.85 | |
| param_dicts = None | |
| hooks = [ | |
| dict(type='CheckpointLoader'), | |
| dict(type='ModelHook'), | |
| dict(type='IterationTimer', warmup_iter=2), | |
| dict(type='InformationWriter'), | |
| dict(type='SemSegEvaluator'), | |
| dict(type='CheckpointSaver', save_freq=None), | |
| dict(type='PreciseEvaluator', test_last=False) | |
| ] | |
| train = dict(type='DefaultTrainer') | |
| test = dict(type='SceneFun3DTester', verbose=True) | |
| min_points = 10 | |
| knn = 32 | |
| knn_radius = 0.02 | |
| model = dict( | |
| type='DefaultSegmentorV2', | |
| num_classes=10, | |
| backbone_out_channels=256, | |
| backbone=dict( | |
| type='Volt', | |
| in_channels=6, | |
| embed_dim=768, | |
| depth=12, | |
| num_heads=12, | |
| mlp_ratio=4, | |
| init_values=None, | |
| qk_norm=True, | |
| drop_path=0.3, | |
| stride=5, | |
| kernel_size=5, | |
| increase_drop_path=True, | |
| up_mlp_dim=256), | |
| criteria=[ | |
| dict( | |
| type='CrossEntropyLoss', | |
| weight=[0.1, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], | |
| loss_weight=1.0, | |
| label_smoothing=0.1, | |
| ignore_index=-1), | |
| dict( | |
| type='LovaszLoss', | |
| mode='multiclass', | |
| loss_weight=1.0, | |
| ignore_index=-1) | |
| ]) | |
| optimizer = dict(type='AdamW', lr=0.0003, weight_decay=0.05) | |
| scheduler = dict( | |
| type='OneCycleLR', | |
| max_lr=0.0003, | |
| pct_start=0.05, | |
| anneal_strategy='cos', | |
| div_factor=10.0, | |
| final_div_factor=1000.0) | |
| dataset_type = 'SceneFun3DDataset' | |
| data_root = 'data/scenefun3d' | |
| data = dict( | |
| num_classes=10, | |
| ignore_index=-1, | |
| names=[ | |
| 'background', 'rotate', 'key_press', 'tip_push', 'hook_pull', | |
| 'pinch_pull', 'hook_turn', 'foot_push', 'plug_in', 'unplug' | |
| ], | |
| train=dict( | |
| type='SceneFun3DDataset', | |
| split='train', | |
| data_root='data/scenefun3d', | |
| transform=[ | |
| dict(type='SphereCrop', point_max=1000000, mode='random'), | |
| dict(type='CenterShift', apply_z=True), | |
| dict( | |
| type='RandomDropout', | |
| dropout_ratio=0.2, | |
| dropout_application_ratio=0.2), | |
| dict( | |
| type='RandomRotate', | |
| angle=[-1, 1], | |
| axis='z', | |
| center=[0, 0, 0], | |
| p=0.5), | |
| dict( | |
| type='RandomRotate', | |
| angle=[-0.015625, 0.015625], | |
| axis='x', | |
| p=0.5), | |
| dict( | |
| type='RandomRotate', | |
| angle=[-0.015625, 0.015625], | |
| axis='y', | |
| p=0.5), | |
| dict(type='RandomScale', scale=[0.9, 1.1]), | |
| 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='ChromaticAutoContrast', p=0.2, blend_factor=None), | |
| dict(type='ChromaticTranslation', p=0.95, ratio=0.05), | |
| dict(type='ChromaticJitter', p=0.95, std=0.05), | |
| dict( | |
| type='GridSample', | |
| grid_size=0.01, | |
| hash_type='fnv', | |
| mode='train', | |
| return_grid_coord=True), | |
| dict(type='SphereCrop', sample_rate=0.6, mode='random'), | |
| dict(type='CenterShift', apply_z=False), | |
| dict(type='NormalizeColor'), | |
| dict(type='ToTensor'), | |
| dict( | |
| type='Collect', | |
| keys=('coord', 'grid_coord', 'segment'), | |
| feat_keys=('color', 'normal')) | |
| ], | |
| test_mode=False, | |
| loop=16), | |
| val=dict( | |
| type='SceneFun3DDataset', | |
| split='val', | |
| data_root='data/scenefun3d', | |
| transform=[ | |
| dict(type='CenterShift', apply_z=True), | |
| dict(type='Copy', keys_dict=dict(segment='origin_segment')), | |
| dict( | |
| type='GridSample', | |
| grid_size=0.01, | |
| hash_type='fnv', | |
| mode='train', | |
| return_grid_coord=True, | |
| return_inverse=True), | |
| dict(type='CenterShift', apply_z=False), | |
| dict(type='NormalizeColor'), | |
| dict(type='ToTensor'), | |
| dict( | |
| type='Collect', | |
| keys=('coord', 'grid_coord', 'segment', 'origin_segment', | |
| 'inverse'), | |
| feat_keys=('color', 'normal')) | |
| ], | |
| test_mode=False), | |
| test=dict( | |
| type='SceneFun3DDataset', | |
| split='val', | |
| data_root='data/scenefun3d', | |
| transform=[ | |
| dict(type='Copy', keys_dict=dict(coord='origin_coord')), | |
| dict(type='CenterShift', apply_z=True), | |
| dict(type='NormalizeColor') | |
| ], | |
| test_mode=True, | |
| test_cfg=dict( | |
| voxelize=dict( | |
| type='GridSample', | |
| grid_size=0.01, | |
| hash_type='fnv', | |
| mode='test', | |
| return_grid_coord=True), | |
| crop=None, | |
| post_transform=[ | |
| dict(type='CenterShift', apply_z=False), | |
| dict(type='ToTensor'), | |
| dict( | |
| type='Collect', | |
| keys=('coord', 'grid_coord', 'index'), | |
| feat_keys=('color', 'normal')) | |
| ], | |
| aug_transform=[[{ | |
| 'type': 'RandomRotateTargetAngle', | |
| 'angle': [0], | |
| 'axis': 'z', | |
| 'center': [0, 0, 0], | |
| 'p': 1 | |
| }], | |
| [{ | |
| 'type': 'RandomRotateTargetAngle', | |
| 'angle': [0.5], | |
| 'axis': 'z', | |
| 'center': [0, 0, 0], | |
| 'p': 1 | |
| }], | |
| [{ | |
| 'type': 'RandomRotateTargetAngle', | |
| 'angle': [1], | |
| 'axis': 'z', | |
| 'center': [0, 0, 0], | |
| 'p': 1 | |
| }], | |
| [{ | |
| 'type': 'RandomRotateTargetAngle', | |
| 'angle': [1.5], | |
| 'axis': 'z', | |
| 'center': [0, 0, 0], | |
| 'p': 1 | |
| }], | |
| [{ | |
| 'type': 'RandomRotateTargetAngle', | |
| 'angle': [0], | |
| 'axis': 'z', | |
| 'center': [0, 0, 0], | |
| 'p': 1 | |
| }, { | |
| 'type': 'RandomScale', | |
| 'scale': [0.95, 0.95] | |
| }], | |
| [{ | |
| 'type': 'RandomRotateTargetAngle', | |
| 'angle': [0.5], | |
| 'axis': 'z', | |
| 'center': [0, 0, 0], | |
| 'p': 1 | |
| }, { | |
| 'type': 'RandomScale', | |
| 'scale': [0.95, 0.95] | |
| }], | |
| [{ | |
| 'type': 'RandomRotateTargetAngle', | |
| 'angle': [1], | |
| 'axis': 'z', | |
| 'center': [0, 0, 0], | |
| 'p': 1 | |
| }, { | |
| 'type': 'RandomScale', | |
| 'scale': [0.95, 0.95] | |
| }], | |
| [{ | |
| 'type': 'RandomRotateTargetAngle', | |
| 'angle': [1.5], | |
| 'axis': 'z', | |
| 'center': [0, 0, 0], | |
| 'p': 1 | |
| }, { | |
| 'type': 'RandomScale', | |
| 'scale': [0.95, 0.95] | |
| }], | |
| [{ | |
| 'type': 'RandomRotateTargetAngle', | |
| 'angle': [0], | |
| 'axis': 'z', | |
| 'center': [0, 0, 0], | |
| 'p': 1 | |
| }, { | |
| 'type': 'RandomScale', | |
| 'scale': [1.05, 1.05] | |
| }], | |
| [{ | |
| 'type': 'RandomRotateTargetAngle', | |
| 'angle': [0.5], | |
| 'axis': 'z', | |
| 'center': [0, 0, 0], | |
| 'p': 1 | |
| }, { | |
| 'type': 'RandomScale', | |
| 'scale': [1.05, 1.05] | |
| }], | |
| [{ | |
| 'type': 'RandomRotateTargetAngle', | |
| 'angle': [1], | |
| 'axis': 'z', | |
| 'center': [0, 0, 0], | |
| 'p': 1 | |
| }, { | |
| 'type': 'RandomScale', | |
| 'scale': [1.05, 1.05] | |
| }], | |
| [{ | |
| 'type': 'RandomRotateTargetAngle', | |
| 'angle': [1.5], | |
| 'axis': 'z', | |
| 'center': [0, 0, 0], | |
| 'p': 1 | |
| }, { | |
| 'type': 'RandomScale', | |
| 'scale': [1.05, 1.05] | |
| }], [{ | |
| 'type': 'RandomFlip', | |
| 'p': 1 | |
| }]]))) | |
| num_worker_per_gpu = 16 | |
| batch_size_per_gpu = 2 | |
| batch_size_val_per_gpu = 1 | |
| batch_size_test_per_gpu = 1 | |