When I ran the demo, the following error occurred：
Traceback (most recent call last):
File "./tools/test_images.py", line 122, in
dataset = get_dataset(args.dataset_name)
File "/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/factory.py", line 57, in get_dataset
return __setsname
File "/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/factory.py", line 28, in
datasets.YCBObject(split))
File "/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/ycb_object.py", line 75, in init
self._extents = self._extents_all[cfg.TRAIN.CLASSES]
IndexError: too many indices for array: array is 2-dimensional, but 21 were indexed
The following is the complete part：
(pose) ys@ys-System-Product-Name:~/PoseCNN-PyTorch-main$ ./experiments/scripts/demo.sh
- set -e
- export PYTHONUNBUFFERED=True
- PYTHONUNBUFFERED=True
- export CUDA_VISIBLE_DEVICES=0
- CUDA_VISIBLE_DEVICES=0
- ./tools/test_images.py --gpu 0 --imgdir data/demo/ --meta data/demo/meta.yml --color '*color.png' --network posecnn --pretrained data/checkpoints/ycb_object/vgg16_ycb_object_self_supervision_epoch_8.checkpoint.pth --dataset ycb_object_test --cfg experiments/cfgs/ycb_object.yml
ycb_video_train
ycb_video_val
ycb_video_keyframe
ycb_video_trainval
ycb_video_debug
ycb_object_train
ycb_object_test
ycb_self_supervision_train_1
ycb_self_supervision_train_2
ycb_self_supervision_train_3
ycb_self_supervision_train_4
ycb_self_supervision_train_5
ycb_self_supervision_test
ycb_self_supervision_all
ycb_self_supervision_train_block_median
ycb_self_supervision_train_block_median_azure
ycb_self_supervision_train_block_median_demo
ycb_self_supervision_train_block_median_azure_demo
ycb_self_supervision_train_table
ycb_self_supervision_debug
ycb_self_supervision_train_block
ycb_self_supervision_train_block_azure
ycb_self_supervision_train_block_big_sim
ycb_self_supervision_train_block_median_sim
ycb_self_supervision_train_block_small_sim
background_coco
background_rgbd
background_nvidia
background_table
background_isaac
background_texture
Called with args:
Namespace(background_name=None, cfg_file='experiments/cfgs/ycb_object.yml', codebook=None, color_name='*color.png', dataset_name='ycb_object_test', depth_name='*depth.png', gpu_id=0, imgdir='data/demo/', meta_file='data/demo/meta.yml', network_name='posecnn', pretrained='data/checkpoints/ycb_object/vgg16_ycb_object_self_supervision_epoch_8.checkpoint.pth', pretrained_encoder=None, randomize=False)
{'INTRINSICS': [618.0172729492188, 0.0, 312.376953125, 0.0, 618.0033569335938, 232.37530517578125, 0.0, 0.0, 1.0]}
Using config:
{'ANCHOR_RATIOS': (0.5, 1, 2),
'ANCHOR_SCALES': (8, 16, 32),
'BACKGROUND': '',
'CAD': '',
'DATA_PATH': '',
'EPS': 1e-14,
'EXP_DIR': 'ycb_object',
'FEATURE_STRIDE': 16,
'FLIP_X': False,
'FLOW_HEIGHT': 512,
'FLOW_WIDTH': 640,
'GPU_ID': 0,
'INPUT': 'COLOR',
'INTRINSICS': [618.0172729492188,
0.0,
312.376953125,
0.0,
618.0033569335938,
232.37530517578125,
0.0,
0.0,
1.0],
'MODE': 'TRAIN',
'NETWORK': 'VGG16',
'PIXEL_MEANS': array([[[102.9801, 115.9465, 122.7717]]]),
'POSE': '',
'RIG': '',
'RNG_SEED': 3,
'ROOT_DIR': '/home/ys/PoseCNN-PyTorch-main',
'TEST': {'ALIGN_Z_AXIS': False,
'BBOX_REG': True,
'BUILD_CODEBOOK': False,
'CHECK_SIZE': False,
'CLASSES': (0,
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
20,
21),
'DET_THRESHOLD': 0.2,
'GAN': False,
'GEN_DATA': False,
'GLOBAL_SEARCH': False,
'GRID_SIZE': 256,
'HOUGH_INLIER_THRESHOLD': 0.9,
'HOUGH_LABEL_THRESHOLD': 400,
'HOUGH_SKIP_PIXELS': 10,
'HOUGH_VOTING_THRESHOLD': 10,
'IMS_PER_BATCH': 1,
'ITERNUM': 4,
'MEAN_SHIFT': False,
'NMS': 0.3,
'NUM_LOST': 3,
'NUM_SDF_ITERATIONS_INIT': 100,
'NUM_SDF_ITERATIONS_TRACKING': 50,
'POSE_CODEBOOK': False,
'POSE_REFINE': True,
'POSE_REG': False,
'POSE_SDF': True,
'RANSAC': False,
'ROS_CAMERA': 'D435',
'RPN_NMS_THRESH': 0.7,
'RPN_POST_NMS_TOP_N': 300,
'RPN_PRE_NMS_TOP_N': 6000,
'SCALES_BASE': (1.0,),
'SDF_ROTATION_REG': 10.0,
'SDF_TRANSLATION_REG': 1000.0,
'SEGMENTATION': True,
'SINGLE_FRAME': True,
'SYMMETRY': (0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
1),
'SYNTHESIZE': True,
'VERTEX_REG_2D': False,
'VERTEX_REG_3D': False,
'VISUALIZE': True},
'TRAIN': {'ADAPT': False,
'ADAPT_NUM': 400,
'ADAPT_RATIO': 1,
'ADAPT_ROOT': '',
'ADAPT_WEIGHT': 0.1,
'ADD_NOISE': True,
'AFFINE': False,
'BATCH_SIZE': 128,
'BBOX_INSIDE_WEIGHTS': (1.0, 1.0, 1.0, 1.0),
'BBOX_NORMALIZE_MEANS': (0.0, 0.0, 0.0, 0.0),
'BBOX_NORMALIZE_STDS': (0.1, 0.1, 0.2, 0.2),
'BBOX_NORMALIZE_TARGETS': True,
'BBOX_NORMALIZE_TARGETS_PRECOMPUTED': True,
'BETA': 0.999,
'BG_THRESH_HI': 0.5,
'BG_THRESH_LO': 0.1,
'BOOSTRAP_PIXELS': 20,
'BOX_W': 1.0,
'CHROMATIC': True,
'CLASSES': (0,
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
20,
21),
'DISPLAY': 20,
'FG_FRACTION': 0.25,
'FG_THRESH': 0.5,
'FG_THRESH_POSE': 0.5,
'FREEZE_LAYERS': True,
'GAMMA': 0.1,
'GAN': False,
'GPUNUM': 1,
'GRID_SIZE': 256,
'HARD_ANGLE': 5.0,
'HARD_LABEL_SAMPLING': 0.0,
'HARD_LABEL_THRESHOLD': 0.9,
'HAS_RPN': True,
'HEATUP': 4,
'HOUGH_INLIER_THRESHOLD': 0.9,
'HOUGH_LABEL_THRESHOLD': 100,
'HOUGH_SKIP_PIXELS': 10,
'HOUGH_VOTING_THRESHOLD': 10,
'IMS_PER_BATCH': 2,
'ITERNUM': 4,
'ITERS': 0,
'LABEL_W': 1.0,
'LEARNING_RATE': 0.001,
'MATCHING': False,
'MAX_ITERS_PER_EPOCH': 1000000,
'MILESTONES': (3,),
'MOMENTUM': 0.9,
'NOISE_LEVEL': 0.05,
'NUM_STEPS': 5,
'NUM_UNITS': 64,
'OPTIMIZER': 'MOMENTUM',
'POSE_REG': True,
'POSE_W': 1.0,
'RPN_BATCHSIZE': 256,
'RPN_BBOX_INSIDE_WEIGHTS': (1.0, 1.0, 1.0, 1.0),
'RPN_CLOBBER_POSITIVES': False,
'RPN_FG_FRACTION': 0.5,
'RPN_NEGATIVE_OVERLAP': 0.3,
'RPN_NMS_THRESH': 0.7,
'RPN_POSITIVE_OVERLAP': 0.7,
'RPN_POSITIVE_WEIGHT': -1.0,
'RPN_POST_NMS_TOP_N': 2000,
'RPN_PRE_NMS_TOP_N': 12000,
'SCALES_BASE': (1.0,),
'SEGMENTATION': True,
'SINGLE_FRAME': False,
'SLIM': False,
'SNAPSHOT_EPOCHS': 1,
'SNAPSHOT_INFIX': 'ycb_object',
'SNAPSHOT_PREFIX': 'vgg16',
'SYMMETRY': (0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
1),
'SYMSIZE': 0,
'SYNITER': 0,
'SYNNUM': 40000,
'SYNROOT': '/home/yuxiang/Projects/Deep_Pose/data/LOV/data_syn/',
'SYNTHESIZE': True,
'SYN_BACKGROUND_AFFINE': False,
'SYN_BACKGROUND_CONSTANT_PROB': 0.1,
'SYN_BACKGROUND_SPECIFIC': True,
'SYN_BACKGROUND_SUBTRACT_MEAN': True,
'SYN_BOUND': 0.3,
'SYN_CLASS_INDEX': 1,
'SYN_CROP': False,
'SYN_CROP_SIZE': 224,
'SYN_HEIGHT': 480,
'SYN_MAX_OBJECT': 8,
'SYN_MIN_OBJECT': 5,
'SYN_ONLINE': False,
'SYN_RATIO': 5,
'SYN_SAMPLE_DISTRACTOR': True,
'SYN_SAMPLE_OBJECT': True,
'SYN_SAMPLE_POSE': False,
'SYN_STD_ROTATION': 15,
'SYN_STD_TRANSLATION': 0.05,
'SYN_TABLE_PROB': 0.8,
'SYN_TFAR': 1.6,
'SYN_TNEAR': 0.5,
'SYN_WIDTH': 640,
'TRAINABLE': True,
'UNIFORM_POSE_INTERVAL': 15,
'USE_FLIPPED': False,
'USE_GT': False,
'VERTEX_REG': True,
'VERTEX_REG_DELTA': False,
'VERTEX_W': 1.0,
'VERTEX_W_INSIDE': 10.0,
'VISUALIZE': False,
'WEIGHT_DECAY': 0.0001},
'USE_GPU_NMS': True,
'gpu_id': 0,
'instance_id': 0}
GPU device 0
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/002_master_chef_can/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/003_cracker_box/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/004_sugar_box/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/005_tomato_soup_can/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/006_mustard_bottle/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/007_tuna_fish_can/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/008_pudding_box/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/009_gelatin_box/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/010_potted_meat_can/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/011_banana/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/019_pitcher_base/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/021_bleach_cleanser/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/024_bowl/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/025_mug/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/035_power_drill/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/036_wood_block/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/037_scissors/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/040_large_marker/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/051_large_clamp/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/052_extra_large_clamp/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/061_foam_brick/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/holiday_cup1/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/holiday_cup2/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/sanning_mug/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/001_chips_can/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_red_big/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_green_big/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_blue_big/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_yellow_big/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_red_small/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_green_small/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_blue_small/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_yellow_small/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_red_median/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_green_median/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_blue_median/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_yellow_median/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/fusion_duplo_dude/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/cabinet_handle/points.xyz
Traceback (most recent call last):
File "./tools/test_images.py", line 122, in
dataset = get_dataset(args.dataset_name)
File "/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/factory.py", line 57, in get_dataset
return __setsname
File "/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/factory.py", line 28, in
datasets.YCBObject(split))
File "/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/ycb_object.py", line 75, in init
self._extents = self._extents_all[cfg.TRAIN.CLASSES]
IndexError: too many indices for array: array is 2-dimensional, but 21 were indexed
real 0m3.996s
user 0m3.744s
sys 0m1.939s
When I ran the demo, the following error occurred：
Traceback (most recent call last):
File "./tools/test_images.py", line 122, in
dataset = get_dataset(args.dataset_name)
File "/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/factory.py", line 57, in get_dataset
return __setsname
File "/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/factory.py", line 28, in
datasets.YCBObject(split))
File "/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/ycb_object.py", line 75, in init
self._extents = self._extents_all[cfg.TRAIN.CLASSES]
IndexError: too many indices for array: array is 2-dimensional, but 21 were indexed
The following is the complete part：
(pose) ys@ys-System-Product-Name:~/PoseCNN-PyTorch-main$ ./experiments/scripts/demo.sh
ycb_video_train
ycb_video_val
ycb_video_keyframe
ycb_video_trainval
ycb_video_debug
ycb_object_train
ycb_object_test
ycb_self_supervision_train_1
ycb_self_supervision_train_2
ycb_self_supervision_train_3
ycb_self_supervision_train_4
ycb_self_supervision_train_5
ycb_self_supervision_test
ycb_self_supervision_all
ycb_self_supervision_train_block_median
ycb_self_supervision_train_block_median_azure
ycb_self_supervision_train_block_median_demo
ycb_self_supervision_train_block_median_azure_demo
ycb_self_supervision_train_table
ycb_self_supervision_debug
ycb_self_supervision_train_block
ycb_self_supervision_train_block_azure
ycb_self_supervision_train_block_big_sim
ycb_self_supervision_train_block_median_sim
ycb_self_supervision_train_block_small_sim
background_coco
background_rgbd
background_nvidia
background_table
background_isaac
background_texture
Called with args:
Namespace(background_name=None, cfg_file='experiments/cfgs/ycb_object.yml', codebook=None, color_name='*color.png', dataset_name='ycb_object_test', depth_name='*depth.png', gpu_id=0, imgdir='data/demo/', meta_file='data/demo/meta.yml', network_name='posecnn', pretrained='data/checkpoints/ycb_object/vgg16_ycb_object_self_supervision_epoch_8.checkpoint.pth', pretrained_encoder=None, randomize=False)
{'INTRINSICS': [618.0172729492188, 0.0, 312.376953125, 0.0, 618.0033569335938, 232.37530517578125, 0.0, 0.0, 1.0]}
Using config:
{'ANCHOR_RATIOS': (0.5, 1, 2),
'ANCHOR_SCALES': (8, 16, 32),
'BACKGROUND': '',
'CAD': '',
'DATA_PATH': '',
'EPS': 1e-14,
'EXP_DIR': 'ycb_object',
'FEATURE_STRIDE': 16,
'FLIP_X': False,
'FLOW_HEIGHT': 512,
'FLOW_WIDTH': 640,
'GPU_ID': 0,
'INPUT': 'COLOR',
'INTRINSICS': [618.0172729492188,
0.0,
312.376953125,
0.0,
618.0033569335938,
232.37530517578125,
0.0,
0.0,
1.0],
'MODE': 'TRAIN',
'NETWORK': 'VGG16',
'PIXEL_MEANS': array([[[102.9801, 115.9465, 122.7717]]]),
'POSE': '',
'RIG': '',
'RNG_SEED': 3,
'ROOT_DIR': '/home/ys/PoseCNN-PyTorch-main',
'TEST': {'ALIGN_Z_AXIS': False,
'BBOX_REG': True,
'BUILD_CODEBOOK': False,
'CHECK_SIZE': False,
'CLASSES': (0,
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
20,
21),
'DET_THRESHOLD': 0.2,
'GAN': False,
'GEN_DATA': False,
'GLOBAL_SEARCH': False,
'GRID_SIZE': 256,
'HOUGH_INLIER_THRESHOLD': 0.9,
'HOUGH_LABEL_THRESHOLD': 400,
'HOUGH_SKIP_PIXELS': 10,
'HOUGH_VOTING_THRESHOLD': 10,
'IMS_PER_BATCH': 1,
'ITERNUM': 4,
'MEAN_SHIFT': False,
'NMS': 0.3,
'NUM_LOST': 3,
'NUM_SDF_ITERATIONS_INIT': 100,
'NUM_SDF_ITERATIONS_TRACKING': 50,
'POSE_CODEBOOK': False,
'POSE_REFINE': True,
'POSE_REG': False,
'POSE_SDF': True,
'RANSAC': False,
'ROS_CAMERA': 'D435',
'RPN_NMS_THRESH': 0.7,
'RPN_POST_NMS_TOP_N': 300,
'RPN_PRE_NMS_TOP_N': 6000,
'SCALES_BASE': (1.0,),
'SDF_ROTATION_REG': 10.0,
'SDF_TRANSLATION_REG': 1000.0,
'SEGMENTATION': True,
'SINGLE_FRAME': True,
'SYMMETRY': (0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
1),
'SYNTHESIZE': True,
'VERTEX_REG_2D': False,
'VERTEX_REG_3D': False,
'VISUALIZE': True},
'TRAIN': {'ADAPT': False,
'ADAPT_NUM': 400,
'ADAPT_RATIO': 1,
'ADAPT_ROOT': '',
'ADAPT_WEIGHT': 0.1,
'ADD_NOISE': True,
'AFFINE': False,
'BATCH_SIZE': 128,
'BBOX_INSIDE_WEIGHTS': (1.0, 1.0, 1.0, 1.0),
'BBOX_NORMALIZE_MEANS': (0.0, 0.0, 0.0, 0.0),
'BBOX_NORMALIZE_STDS': (0.1, 0.1, 0.2, 0.2),
'BBOX_NORMALIZE_TARGETS': True,
'BBOX_NORMALIZE_TARGETS_PRECOMPUTED': True,
'BETA': 0.999,
'BG_THRESH_HI': 0.5,
'BG_THRESH_LO': 0.1,
'BOOSTRAP_PIXELS': 20,
'BOX_W': 1.0,
'CHROMATIC': True,
'CLASSES': (0,
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
20,
21),
'DISPLAY': 20,
'FG_FRACTION': 0.25,
'FG_THRESH': 0.5,
'FG_THRESH_POSE': 0.5,
'FREEZE_LAYERS': True,
'GAMMA': 0.1,
'GAN': False,
'GPUNUM': 1,
'GRID_SIZE': 256,
'HARD_ANGLE': 5.0,
'HARD_LABEL_SAMPLING': 0.0,
'HARD_LABEL_THRESHOLD': 0.9,
'HAS_RPN': True,
'HEATUP': 4,
'HOUGH_INLIER_THRESHOLD': 0.9,
'HOUGH_LABEL_THRESHOLD': 100,
'HOUGH_SKIP_PIXELS': 10,
'HOUGH_VOTING_THRESHOLD': 10,
'IMS_PER_BATCH': 2,
'ITERNUM': 4,
'ITERS': 0,
'LABEL_W': 1.0,
'LEARNING_RATE': 0.001,
'MATCHING': False,
'MAX_ITERS_PER_EPOCH': 1000000,
'MILESTONES': (3,),
'MOMENTUM': 0.9,
'NOISE_LEVEL': 0.05,
'NUM_STEPS': 5,
'NUM_UNITS': 64,
'OPTIMIZER': 'MOMENTUM',
'POSE_REG': True,
'POSE_W': 1.0,
'RPN_BATCHSIZE': 256,
'RPN_BBOX_INSIDE_WEIGHTS': (1.0, 1.0, 1.0, 1.0),
'RPN_CLOBBER_POSITIVES': False,
'RPN_FG_FRACTION': 0.5,
'RPN_NEGATIVE_OVERLAP': 0.3,
'RPN_NMS_THRESH': 0.7,
'RPN_POSITIVE_OVERLAP': 0.7,
'RPN_POSITIVE_WEIGHT': -1.0,
'RPN_POST_NMS_TOP_N': 2000,
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'SYNROOT': '/home/yuxiang/Projects/Deep_Pose/data/LOV/data_syn/',
'SYNTHESIZE': True,
'SYN_BACKGROUND_AFFINE': False,
'SYN_BACKGROUND_CONSTANT_PROB': 0.1,
'SYN_BACKGROUND_SPECIFIC': True,
'SYN_BACKGROUND_SUBTRACT_MEAN': True,
'SYN_BOUND': 0.3,
'SYN_CLASS_INDEX': 1,
'SYN_CROP': False,
'SYN_CROP_SIZE': 224,
'SYN_HEIGHT': 480,
'SYN_MAX_OBJECT': 8,
'SYN_MIN_OBJECT': 5,
'SYN_ONLINE': False,
'SYN_RATIO': 5,
'SYN_SAMPLE_DISTRACTOR': True,
'SYN_SAMPLE_OBJECT': True,
'SYN_SAMPLE_POSE': False,
'SYN_STD_ROTATION': 15,
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GPU device 0
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/002_master_chef_can/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/003_cracker_box/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/004_sugar_box/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/005_tomato_soup_can/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/006_mustard_bottle/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/007_tuna_fish_can/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/008_pudding_box/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/009_gelatin_box/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/010_potted_meat_can/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/011_banana/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/019_pitcher_base/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/021_bleach_cleanser/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/024_bowl/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/025_mug/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/035_power_drill/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/036_wood_block/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/037_scissors/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/040_large_marker/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/051_large_clamp/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/052_extra_large_clamp/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/061_foam_brick/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/holiday_cup1/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/holiday_cup2/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/sanning_mug/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/001_chips_can/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_red_big/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_green_big/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_blue_big/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_yellow_big/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_red_small/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_green_small/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_blue_small/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_yellow_small/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_red_median/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_green_median/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_blue_median/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/block_yellow_median/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/fusion_duplo_dude/points.xyz
/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/../../data/models/cabinet_handle/points.xyz
Traceback (most recent call last):
File "./tools/test_images.py", line 122, in
dataset = get_dataset(args.dataset_name)
File "/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/factory.py", line 57, in get_dataset
return __setsname
File "/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/factory.py", line 28, in
datasets.YCBObject(split))
File "/home/ys/PoseCNN-PyTorch-main/tools/../lib/datasets/ycb_object.py", line 75, in init
self._extents = self._extents_all[cfg.TRAIN.CLASSES]
IndexError: too many indices for array: array is 2-dimensional, but 21 were indexed
real 0m3.996s
user 0m3.744s
sys 0m1.939s