(posecnn) r****@r****-MS-7D42:~/3dTracking/PoseCNN-PyTorch$ ./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)
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/fcn/config.py:377: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
yaml_cfg = edict(yaml.load(f))
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/fcn/config.py:386: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
yaml_cfg = edict(yaml.load(f))
{'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/r****/3dTracking/PoseCNN-PyTorch',
'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/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/002_master_chef_can/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/003_cracker_box/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/004_sugar_box/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/005_tomato_soup_can/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/006_mustard_bottle/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/007_tuna_fish_can/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/008_pudding_box/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/009_gelatin_box/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/010_potted_meat_can/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/011_banana/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/019_pitcher_base/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/021_bleach_cleanser/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/024_bowl/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/025_mug/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/035_power_drill/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/036_wood_block/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/037_scissors/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/040_large_marker/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/051_large_clamp/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/052_extra_large_clamp/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/061_foam_brick/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/holiday_cup1/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/holiday_cup2/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/sanning_mug/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/001_chips_can/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/block_red_big/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/block_green_big/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/block_blue_big/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/block_yellow_big/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/block_red_small/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/block_green_small/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/block_blue_small/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/block_yellow_small/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/block_red_median/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/block_green_median/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/block_blue_median/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/block_yellow_median/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/fusion_duplo_dude/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/cabinet_handle/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/002_master_chef_can/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/003_cracker_box/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/004_sugar_box/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/005_tomato_soup_can/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/006_mustard_bottle/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/007_tuna_fish_can/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/008_pudding_box/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/009_gelatin_box/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/010_potted_meat_can/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/011_banana/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/019_pitcher_base/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/021_bleach_cleanser/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/024_bowl/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/025_mug/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/035_power_drill/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/036_wood_block/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/037_scissors/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/040_large_marker/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/052_extra_large_clamp/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/061_foam_brick/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/002_master_chef_can/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/003_cracker_box/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/004_sugar_box/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/005_tomato_soup_can/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/006_mustard_bottle/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/007_tuna_fish_can/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/008_pudding_box/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/009_gelatin_box/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/010_potted_meat_can/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/011_banana/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/019_pitcher_base/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/021_bleach_cleanser/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/024_bowl/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/025_mug/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/035_power_drill/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/036_wood_block/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/037_scissors/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/040_large_marker/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/052_extra_large_clamp/points.xyz
/home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/061_foam_brick/points.xyz
[[618.01727295 0. 312.37695312]
[ 0. 618.00335693 232.37530518]
[ 0. 0. 1. ]]
=> using pre-trained network 'data/checkpoints/ycb_object/vgg16_ycb_object_self_supervision_epoch_8.checkpoint.pth'
ModuleList(
(0): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(1): ReLU(inplace=True)
(2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(3): ReLU(inplace=True)
(4): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(5): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(6): ReLU(inplace=True)
(7): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(8): ReLU(inplace=True)
(9): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(10): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(11): ReLU(inplace=True)
(12): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(13): ReLU(inplace=True)
(14): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(15): ReLU(inplace=True)
(16): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(17): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(18): ReLU(inplace=True)
(19): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(20): ReLU(inplace=True)
(21): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(22): ReLU(inplace=True)
(23): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
(24): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(25): ReLU(inplace=True)
(26): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(27): ReLU(inplace=True)
(28): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
(29): ReLU(inplace=True)
)
Sequential(
(0): Linear(in_features=25088, out_features=4096, bias=True)
(1): ReLU(inplace=True)
(2): Dropout(p=0.5, inplace=False)
(3): Linear(in_features=4096, out_features=4096, bias=True)
(4): ReLU(inplace=True)
(5): Dropout(p=0.5, inplace=False)
)
model keys
=================================================
features.0.weight
features.0.bias
features.2.weight
features.2.bias
features.5.weight
features.5.bias
features.7.weight
features.7.bias
features.10.weight
features.10.bias
features.12.weight
features.12.bias
features.14.weight
features.14.bias
features.17.weight
features.17.bias
features.19.weight
features.19.bias
features.21.weight
features.21.bias
features.24.weight
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features.26.weight
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classifier.0.weight
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conv_vertex_score.weight
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fc8.0.weight
fc8.0.bias
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fc10.weight
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=================================================
data keys
=================================================
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features.0.bias
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conv_vertex_score.weight
conv_vertex_score.bias
fc8.0.weight
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fc9.weight
fc9.bias
fc10.weight
fc10.bias
=================================================
load the following keys from the pretrained model
=================================================
features.0.weight
features.0.bias
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features.2.bias
features.5.weight
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fc8.0.weight
fc8.0.bias
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fc10.weight
fc10.bias
=================================================
loading 3D models
libEGL warning: DRI2: failed to create dri screen
libEGL warning: DRI2: failed to create dri screen
Unable to initialize EGL
Command '['/home/r****/3dTracking/PoseCNN-PyTorch/tools/../ycb_render/build/test_device', '1']' returned non-zero exit status 1.
number of devices found 3
Loaded EGL 1.5 after reload.
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/002_master_chef_can/textured_simple.obj time:0.439
buffer time:0.453
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/003_cracker_box/textured_simple.obj time:0.412
buffer time:0.472
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/004_sugar_box/textured_simple.obj time:0.429
buffer time:0.492
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/005_tomato_soup_can/textured_simple.obj time:0.407
buffer time:0.447
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/006_mustard_bottle/textured_simple.obj time:0.429
buffer time:0.404
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/007_tuna_fish_can/textured_simple.obj time:0.422
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load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/008_pudding_box/textured_simple.obj time:0.428
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load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/009_gelatin_box/textured_simple.obj time:0.408
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load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/010_potted_meat_can/textured_simple.obj time:0.430
buffer time:0.444
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/011_banana/textured_simple.obj time:0.437
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load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/019_pitcher_base/textured_simple.obj time:0.435
buffer time:0.387
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/021_bleach_cleanser/textured_simple.obj time:0.413
buffer time:0.463
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/024_bowl/textured_simple.obj time:0.444
buffer time:0.350
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/025_mug/textured_simple.obj time:0.436
buffer time:0.396
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/035_power_drill/textured_simple.obj time:0.426
buffer time:0.399
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/036_wood_block/textured_simple.obj time:0.407
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load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/037_scissors/textured_simple.obj time:0.425
buffer time:0.351
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/040_large_marker/textured_simple.obj time:0.424
buffer time:0.336
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/052_extra_large_clamp/textured_simple.obj time:0.427
buffer time:0.404
load mesh /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/061_foam_brick/textured_simple.obj time:0.407
buffer time:0.389
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loading SDFs
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/002_master_chef_can/textured_simple_low_res.pth ...
minimal coordinate = (-8.2592, -8.0720, -10.3652) cm
maximal coordinate = (8.0408, 8.2280, 9.7348) cm
torch.Size([163, 163, 201])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/003_cracker_box/textured_simple_low_res.pth ...
minimal coordinate = (-6.6441, -11.3689, -14.1580) cm
maximal coordinate = (6.5559, 11.0311, 13.2420) cm
torch.Size([132, 224, 274])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/004_sugar_box/textured_simple_low_res.pth ...
minimal coordinate = (-5.3929, -7.8438, -12.2366) cm
maximal coordinate = (5.6071, 7.6562, 11.4634) cm
torch.Size([110, 155, 237])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/005_tomato_soup_can/textured_simple_low_res.pth ...
minimal coordinate = (-6.4208, -6.2324, -8.9334) cm
maximal coordinate = (6.3792, 6.5676, 7.3666) cm
torch.Size([128, 128, 163])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/006_mustard_bottle/textured_simple_low_res.pth ...
minimal coordinate = (-7.9815, -6.5766, -11.3861) cm
maximal coordinate = (7.8185, 6.1234, 13.8139) cm
torch.Size([158, 127, 252])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/007_tuna_fish_can/textured_simple_low_res.pth ...
minimal coordinate = (-11.7703, -11.7973, -9.5875) cm
maximal coordinate = (11.8297, 11.8027, 8.8125) cm
torch.Size([236, 236, 184])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/008_pudding_box/textured_simple_low_res.pth ...
minimal coordinate = (-10.0247, -9.0539, -5.2485) cm
maximal coordinate = (9.7753, 9.8461, 4.6515) cm
torch.Size([198, 189, 99])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/009_gelatin_box/textured_simple_low_res.pth ...
minimal coordinate = (-7.6130, -8.0064, -4.8624) cm
maximal coordinate = (7.3870, 8.1936, 4.2376) cm
torch.Size([150, 162, 91])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/010_potted_meat_can/textured_simple_low_res.pth ...
minimal coordinate = (-8.3410, -6.0904, -7.9775) cm
maximal coordinate = (7.9590, 6.0096, 6.4225) cm
torch.Size([163, 121, 144])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/011_banana/textured_simple_low_res.pth ...
minimal coordinate = (-6.5771, -13.1447, -4.6900) cm
maximal coordinate = (10.3229, 10.7553, 5.0100) cm
torch.Size([169, 239, 97])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/019_pitcher_base/textured_simple_low_res.pth ...
minimal coordinate = (-10.9739, -10.8570, -17.7016) cm
maximal coordinate = (9.9261, 9.6430, 12.5984) cm
torch.Size([209, 205, 303])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/021_bleach_cleanser/textured_simple_low_res.pth ...
minimal coordinate = (-8.6193, -6.1406, -14.2021) cm
maximal coordinate = (7.7307, 6.7594, 16.9979) cm
torch.Size([109, 86, 208])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/024_bowl/textured_simple_low_res.pth ...
minimal coordinate = (-11.0480, -11.1634, -5.4470) cm
maximal coordinate = (11.1520, 11.0366, 6.0530) cm
torch.Size([222, 222, 115])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/025_mug/textured_simple_low_res.pth ...
minimal coordinate = (-8.0214, -7.5925, -6.9003) cm
maximal coordinate = (9.6786, 7.8075, 7.2997) cm
torch.Size([177, 154, 142])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/035_power_drill/textured_simple_low_res.pth ...
minimal coordinate = (-13.1156, -14.4716, -5.6572) cm
maximal coordinate = (11.3844, 10.3284, 6.1428) cm
torch.Size([245, 248, 118])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/036_wood_block/textured_simple_low_res.pth ...
minimal coordinate = (-8.3391, -7.9251, -15.0091) cm
maximal coordinate = (8.0609, 8.4749, 11.5909) cm
torch.Size([164, 164, 266])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/037_scissors/textured_simple_low_res.pth ...
minimal coordinate = (-8.5101, -10.2541, -3.7781) cm
maximal coordinate = (7.2399, 15.9959, 3.8719) cm
torch.Size([105, 175, 51])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/040_large_marker/textured_simple_low_res.pth ...
minimal coordinate = (-4.0577, -8.8287, -3.9764) cm
maximal coordinate = (4.1423, 9.2713, 3.9236) cm
torch.Size([82, 181, 79])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/052_extra_large_clamp/textured_simple_low_res.pth ...
minimal coordinate = (-13.4513, -10.1756, -4.8376) cm
maximal coordinate = (13.5487, 12.3244, 4.8624) cm
torch.Size([270, 225, 97])
finished loading sdf !
start loading sdf from /home/r****/3dTracking/PoseCNN-PyTorch/tools/../lib/datasets/../../data/models/061_foam_brick/textured_simple_low_res.pth ...
minimal coordinate = (-5.6072, -6.8979, -4.7219) cm
maximal coordinate = (5.6928, 6.9021, 6.4781) cm
torch.Size([113, 138, 112])
finished loading sdf !
data/demo/000002-color.png
data/demo/000002-depth.png
/home/r****/anaconda3/envs/posecnn/lib/python3.6/site-packages/torch/nn/functional.py:3635: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
"See the documentation of nn.Upsample for details.".format(mode)
object 0, class 008_pudding_box, z 0.6868003606796265, z new 0.709780216217041
object 1, class 019_pitcher_base, z 0.5529112219810486, z new 0.6552914977073669
object 2, class 002_master_chef_can, z 0.5707491040229797, z new 0.6095099449157715
object 3, class 052_extra_large_clamp, z 0.6475031971931458, z new 0.6376608610153198
object 4, class 011_banana, z 0.6982769966125488, z new 0.7431917190551758
sdf 6888 points for object 0, class 6 008_pudding_box
sdf 27337 points for object 1, class 10 019_pitcher_base
sdf 16038 points for object 2, class 0 002_master_chef_can
sdf 11314 points for object 3, class 18 052_extra_large_clamp
sdf 3385 points for object 4, class 9 011_banana
sdf with 64962 points
sdf refinement iterations 50, time 0.054651
pose refine time 0.084577
008_pudding_box 0.9962274 6
019_pitcher_base 0.9949043 10
002_master_chef_can 0.97969073 0
052_extra_large_clamp 0.96948594 18
011_banana 0.9450298 9
