synthesizer argument error (python argument type does not match c++)

Hi I was trying to run the training shell script: ./experiments/scripts/lov_color_2d_train.sh 0 When it runs it stops at render function and gives me this error: I guess it has problems matching str in python to string in c++ which could be cython error. " Exception in thread Thread-1: Traceback (most recent call last): File "/usr/lib/python2.7/threading.py", line 801, in bootstrap_inner self.run() File "/usr/lib/python2.7/threading.py", line 754, in run self.target(*self.args, **self.__kwargs) File "./tools/train_net.py", line 160, in render synthesizer = libsynthesizer.Synthesizer(cfg.CAD, cfg.POSE ) ArgumentError: Python argument types in Synthesizer.init(Synthesizer, str, str) did not match C++ signature: init__(_object*, std::string, std::string) "

The whole log file is attached:`+ echo Logging output to experiments/logs/lov_color_2d_train.txt.2018-07-10_15-39-28 Logging output to experiments/logs/lov_color_2d_train.txt.2018-07-10_15-39-28

export LD_PRELOAD=/usr/lib/libtcmalloc.so.4
LD_PRELOAD=/usr/lib/libtcmalloc.so.4
./tools/train_net.py --gpu 0 --network vgg16_convs --weights data/imagenet_models/vgg16.npy --imdb lov_train --cfg experiments/cfgs/lov_color_2d.yml --cad data/LOV/models.txt --pose data/LOV/poses.txt --iters 160000 shapenet_scene_train shapenet_scene_val shapenet_single_train shapenet_single_val gmu_scene_train gmu_scene_val rgbd_scene_train rgbd_scene_val rgbd_scene_trainval lov_train lov_val lov_keyframe lov_trainval lov_debug lov_train_few lov_val_few lov_single_002_master_chef_can_train lov_single_002_master_chef_can_val lov_single_002_master_chef_can_keyframe lov_single_003_cracker_box_train lov_single_003_cracker_box_val lov_single_003_cracker_box_keyframe lov_single_004_sugar_box_train lov_single_004_sugar_box_val lov_single_004_sugar_box_keyframe lov_single_005_tomato_soup_can_train lov_single_005_tomato_soup_can_val lov_single_005_tomato_soup_can_keyframe lov_single_006_mustard_bottle_train lov_single_006_mustard_bottle_val lov_single_006_mustard_bottle_keyframe lov_single_007_tuna_fish_can_train lov_single_007_tuna_fish_can_val lov_single_007_tuna_fish_can_keyframe lov_single_008_pudding_box_train lov_single_008_pudding_box_val lov_single_008_pudding_box_keyframe lov_single_009_gelatin_box_train lov_single_009_gelatin_box_val lov_single_009_gelatin_box_keyframe lov_single_010_potted_meat_can_train lov_single_010_potted_meat_can_val lov_single_010_potted_meat_can_keyframe lov_single_011_banana_train lov_single_011_banana_val lov_single_011_banana_keyframe lov_single_019_pitcher_base_train lov_single_019_pitcher_base_val lov_single_019_pitcher_base_keyframe lov_single_021_bleach_cleanser_train lov_single_021_bleach_cleanser_val lov_single_021_bleach_cleanser_keyframe lov_single_024_bowl_train lov_single_024_bowl_val lov_single_024_bowl_keyframe lov_single_025_mug_train lov_single_025_mug_val lov_single_025_mug_keyframe lov_single_035_power_drill_train lov_single_035_power_drill_val lov_single_035_power_drill_keyframe lov_single_036_wood_block_train lov_single_036_wood_block_val lov_single_036_wood_block_keyframe lov_single_037_scissors_train lov_single_037_scissors_val lov_single_037_scissors_keyframe lov_single_040_large_marker_train lov_single_040_large_marker_val lov_single_040_large_marker_keyframe lov_single_051_large_clamp_train lov_single_051_large_clamp_val lov_single_051_large_clamp_keyframe lov_single_052_extra_large_clamp_train lov_single_052_extra_large_clamp_val lov_single_052_extra_large_clamp_keyframe lov_single_061_foam_brick_train lov_single_061_foam_brick_val lov_single_061_foam_brick_keyframe ycb_trainval ycb_single_002_master_chef_can_train ycb_single_003_cracker_box_train ycb_single_004_sugar_box_train ycb_single_005_tomato_soup_can_train ycb_single_006_mustard_bottle_train ycb_single_007_tuna_fish_can_train ycb_single_008_pudding_box_train ycb_single_009_gelatin_box_train ycb_single_010_potted_meat_can_train ycb_single_011_banana_train ycb_single_019_pitcher_base_train ycb_single_021_bleach_cleanser_train ycb_single_024_bowl_train ycb_single_025_mug_train ycb_single_035_power_drill_train ycb_single_036_wood_block_train ycb_single_037_scissors_train ycb_single_040_large_marker_train ycb_single_051_large_clamp_train ycb_single_052_extra_large_clamp_train ycb_single_061_foam_brick_train yumi_train linemod_ape_train linemod_ape_test linemod_ape_train_few linemod_ape_test_few linemod_benchvise_train linemod_benchvise_test linemod_benchvise_train_few linemod_benchvise_test_few linemod_bowl_train linemod_bowl_test linemod_bowl_train_few linemod_bowl_test_few linemod_camera_train linemod_camera_test linemod_camera_train_few linemod_camera_test_few linemod_can_train linemod_can_test linemod_can_train_few linemod_can_test_few linemod_cat_train linemod_cat_test linemod_cat_train_few linemod_cat_test_few linemod_cup_train linemod_cup_test linemod_cup_train_few linemod_cup_test_few linemod_driller_train linemod_driller_test linemod_driller_train_few linemod_driller_test_few linemod_duck_train linemod_duck_test linemod_duck_train_few linemod_duck_test_few linemod_eggbox_train linemod_eggbox_test linemod_eggbox_train_few linemod_eggbox_test_few linemod_glue_train linemod_glue_test linemod_glue_train_few linemod_glue_test_few linemod_holepuncher_train linemod_holepuncher_test linemod_holepuncher_train_few linemod_holepuncher_test_few linemod_iron_train linemod_iron_test linemod_iron_train_few linemod_iron_test_few linemod_lamp_train linemod_lamp_test linemod_lamp_train_few linemod_lamp_test_few linemod_phone_train linemod_phone_test linemod_phone_train_few linemod_phone_test_few sym_train Called with args: Namespace(cad_name='data/LOV/models.txt', cfg_file='experiments/cfgs/lov_color_2d.yml', gpu_id=0, imdb_name='lov_train', max_iters=160000, network_name='vgg16_convs', pose_name='data/LOV/poses.txt', pretrained_ckpt=None, pretrained_model='data/imagenet_models/vgg16.npy', randomize=False, rig_name=None) Using config: {'ANCHOR_RATIOS': [0.5, 1, 2], 'ANCHOR_SCALES': [8, 16, 32], 'BACKGROUND': '', 'CAD': '', 'EPS': 1e-14, 'EXP_DIR': 'lov', 'FEATURE_STRIDE': 16, 'FLIP_X': False, 'GPU_ID': 0, 'INPUT': 'COLOR', 'NETWORK': 'VGG16', 'PIXEL_MEANS': array([[[102.9801, 115.9465, 122.7717]]]), 'POSE': '', 'RIG': '', 'RNG_SEED': 3, 'ROOT_DIR': '/home/mamad/PoseCNN', 'TEST': {'BBOX_REG': True, 'GAN': False, 'GRID_SIZE': 256, 'NMS': 0.3, 'POSE_REFINE': False, 'POSE_REG': True, 'RANSAC': False, 'RPN_NMS_THRESH': 0.7, 'RPN_POST_NMS_TOP_N': 300, 'RPN_PRE_NMS_TOP_N': 6000, 'SCALES_BASE': [1.0], 'SEGMENTATION': True, 'SINGLE_FRAME': True, 'SYNTHETIC': False, 'VERTEX_REG_2D': True, 'VERTEX_REG_3D': False, 'VISUALIZE': True, 'VOTING_THRESHOLD': -1}, 'TRAIN': {'ADAPT': False, 'ADAPT_NUM': 400, 'ADAPT_RATIO': 1, 'ADAPT_ROOT': '', 'ADAPT_WEIGHT': 0.1, 'ADD_NOISE': True, '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, 'BG_THRESH_HI': 0.5, 'BG_THRESH_LO': 0.1, 'CHROMATIC': True, 'DISPLAY': 20, 'FG_FRACTION': 0.25, 'FG_THRESH': 0.5, 'GAMMA': 0.1, 'GAN': False, 'GRID_SIZE': 256, 'HAS_RPN': True, 'IMS_PER_BATCH': 2, 'LABEL_W': 1.0, 'LEARNING_RATE': 0.001, 'MATCHING': False, 'MOMENTUM': 0.9, 'NUM_CLASSES': 22, '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': True, 'SNAPSHOT_INFIX': 'lov', 'SNAPSHOT_ITERS': 10000, 'SNAPSHOT_PREFIX': 'vgg16_fcn_color_single_frame_2d_pose_add', 'STEPSIZE': 80000, 'SYMSIZE': 0, 'SYNITER': 0, 'SYNNUM': 80000, 'SYNROOT': 'data/LOV/data_syn/', 'SYNTHESIZE': True, 'SYN_CLASS_INDEX': -1, 'SYN_HEIGHT': 480, 'SYN_ONLINE': True, 'SYN_RATIO': 5, 'SYN_SAMPLE_OBJECT': True, 'SYN_SAMPLE_POSE': True, 'SYN_TFAR': 2.0, 'SYN_TNEAR': 0.5, 'SYN_WIDTH': 640, 'THRESHOLD_LABEL': 1.0, 'TRAINABLE': True, 'USE_FLIPPED': False, 'USE_GT': False, 'VERTEX_REG_2D': True, 'VERTEX_REG_3D': False, 'VERTEX_W': 1.0, 'VERTEX_W_INSIDE': 10.0, 'VISUALIZE': False, 'VOTING_THRESHOLD': -1, 'WEIGHT_REG': 0.0001}, 'USE_GPU_NMS': True} /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/002_master_chef_can/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/003_cracker_box/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/004_sugar_box/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/005_tomato_soup_can/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/006_mustard_bottle/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/007_tuna_fish_can/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/008_pudding_box/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/009_gelatin_box/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/010_potted_meat_can/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/011_banana/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/019_pitcher_base/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/021_bleach_cleanser/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/024_bowl/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/025_mug/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/035_power_drill/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/036_wood_block/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/037_scissors/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/040_large_marker/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/051_large_clamp/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/052_extra_large_clamp/points.xyz /home/mamad/PoseCNN/tools/../lib/datasets/../../data/LOV/models/061_foam_brick/points.xyz Loaded dataset lov_train for training symmetry [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1] lov_train gt roidb loaded from /home/mamad/PoseCNN/data/cache/lov_train_gt_roidb.pkl class weights: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] Output will be saved to /home/mamad/PoseCNN/output/lov/lov_train /gpu:0 registered Poly3 registered Poly3 registered Linear registered Linear Start Rendering ... Start Rendering fn ('CAD ', <type 'str'>) ('pose ', <type 'str'>) Exception in thread Thread-1: Traceback (most recent call last): File "/usr/lib/python2.7/threading.py", line 801, in bootstrap_inner self.run() File "/usr/lib/python2.7/threading.py", line 754, in run self.target(*self.args, **self.__kwargs) File "./tools/train_net.py", line 160, in render synthesizer = libsynthesizer.Synthesizer(cfg.CAD, cfg.POSE ) ArgumentError: Python argument types in Synthesizer.init(Synthesizer, str, str) did not match C++ signature: init__(_object*, std::string, std::string)

Tensor("fifo_queue_Dequeue:0", dtype=float32) Tensor("conv5_3/conv5_3:0", shape=(?, ?, ?, 512), dtype=float32) Tensor("conv4_3/conv4_3:0", shape=(?, ?, ?, 512), dtype=float32) Tensor("score_conv4/score_conv4:0", shape=(?, ?, ?, 64), dtype=float32) Tensor("upscore_conv5_1:0", shape=(?, ?, ?, 64), dtype=float32) Tensor("upscore_1:0", shape=(?, ?, ?, 64), dtype=float32) Tensor("score/score:0", shape=(?, ?, ?, 22), dtype=float32) Tensor("div:0", shape=(?, ?, ?, 22), dtype=float32) Tensor("fifo_queue_Dequeue:1", dtype=int32) Tensor("conv5_3/conv5_3:0", shape=(?, ?, ?, 512), dtype=float32) Tensor("conv4_3/conv4_3:0", shape=(?, ?, ?, 512), dtype=float32) Tensor("score_conv4_vertex/BiasAdd:0", shape=(?, ?, ?, 128), dtype=float32) Tensor("upscore_conv5_vertex_1:0", shape=(?, ?, ?, 128), dtype=float32) Tensor("ToInt32:0", shape=(?, ?, ?), dtype=int32) Tensor("vertex_pred/BiasAdd:0", shape=(?, ?, ?, 66), dtype=float32) Tensor("fifo_queue_Dequeue:6", dtype=float32) Tensor("fifo_queue_Dequeue:7", dtype=float32) Tensor("fifo_queue_Dequeue:5", dtype=float32) Tensor("conv5_3/conv5_3:0", shape=(?, ?, ?, 512), dtype=float32) Tensor("hough:0", shape=(?, 7), dtype=float32) Tensor("conv4_3/conv4_3:0", shape=(?, ?, ?, 512), dtype=float32) Tensor("hough:0", shape=(?, 7), dtype=float32) RoiPool(top_data=<tf.Tensor 'pool5:0' shape=(?, 7, 7, 512) dtype=float32>, argmax=<tf.Tensor 'pool5:1' shape=(?, 7, 7, 512) dtype=int32>) RoiPool(top_data=<tf.Tensor 'pool4_1:0' shape=(?, 7, 7, 512) dtype=float32>, argmax=<tf.Tensor 'pool4_1:1' shape=(?, 7, 7, 512) dtype=int32>) Tensor("poses_tanh:0", shape=(?, 88), dtype=float32) Tensor("hough:3", shape=(?, 88), dtype=float32) Tensor("poses_pred:0", shape=(?, 88), dtype=float32) Tensor("hough:2", shape=(?, 88), dtype=float32) Tensor("hough:3", shape=(?, 88), dtype=float32) Tensor("fifo_queue_Dequeue:8", dtype=float32) Tensor("fifo_queue_Dequeue:9", dtype=float32) Use network vgg16_convs in training 2018-07-10 15:39:32.228268: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX 2018-07-10 15:39:32.337709: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Found device 0 with properties: name: TITAN X (Pascal) major: 6 minor: 1 memoryClockRate(GHz): 1.531 pciBusID: 0000:02:00.0 totalMemory: 11.90GiB freeMemory: 11.36GiB 2018-07-10 15:39:32.337748: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: TITAN X (Pascal), pci bus id: 0000:02:00.0, compute capability: 6.1) lov_train backgrounds loaded from /home/mamad/PoseCNN/data/cache/backgrounds.pkl lov_train backgrounds depth loaded from /home/mamad/PoseCNN/data/cache/backgrounds_depth.pkl Solving... ('Layer.py back', []) Loading pretrained model weights from data/imagenet_models/vgg16.npy conv5_1 conv5_1 weights assigned conv5_1 biases assigned fc6 fc6 weights assigned fc6 biases assigned conv5_3 conv5_3 weights assigned conv5_3 biases assigned fc7 fc7 weights assigned fc7 biases assigned fc8 conv5_2 conv5_2 weights assigned conv5_2 biases assigned conv4_1 conv4_1 weights assigned conv4_1 biases assigned conv4_2 conv4_2 weights assigned conv4_2 biases assigned conv4_3 conv4_3 weights assigned conv4_3 biases assigned conv3_3 conv3_3 weights assigned conv3_3 biases assigned conv3_2 conv3_2 weights assigned conv3_2 biases assigned conv3_1 conv3_1 weights assigned conv3_1 biases assigned conv1_1 conv1_1 weights assigned conv1_1 biases assigned conv1_2 conv1_2 weights assigned conv1_2 biases assigned conv2_2 conv2_2 weights assigned conv2_2 biases assigned conv2_1 conv2_1 weights assigned conv2_1 biases assigned`

yuxng / PoseCNN

synthesizer argument error (python argument type does not match c++) #37