Training model error

[Pratosha-29]

Hi, I am currently facing this error while I am trying to train VGGnet from 21 classes to 7. nvidia@tegra-ubuntu:~/TensorFlowTX2/Faster-RCNN_TF_changes$ ./experiments/scripts/faster_rcnn_end2end.sh GPU 0 /home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/data/VGG_imagenet.npy pascal_voc

• set -e
• export PYTHONUNBUFFERED=True
• PYTHONUNBUFFERED=True
• DEV=GPU
• DEV_ID=0
• NET=/home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/data/VGG_imagenet.npy
• DATASET=pascal_voc
• array=($@)
• len=4
• EXTRA_ARGS=
• EXTRA_ARGS_SLUG=
• case $DATASET in
• TRAIN_IMDB=/home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/data/VOCdevkit16/VOCdevkit/VOC2007/ImageSets/Main/voc_2007_trainval
• TEST_IMDB=voc_2007_test
• PT_DIR=pascal_voc
• ITERS=70000 ++ date +%Y-%m-%d_%H-%M-%S
• LOG=experiments/logs/faster_rcnnend2end/home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/data/VGGimagenet.npy.txt.2018-01-30_16-57-32
• exec ++ tee -a experiments/logs/faster_rcnnend2end/home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/data/VGGimagenet.npy.txt.2018-01-30_16-57-32 tee: experiments/logs/faster_rcnnend2end/home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/data/VGGimagenet.npy.txt.2018-01-30_16-57-32: No such file or directory
• echo Logging output to experiments/logs/faster_rcnnend2end/home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/data/VGGimagenet.npy.txt.2018-01-30_16-57-32 Logging output to experiments/logs/faster_rcnnend2end/home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/data/VGGimagenet.npy.txt.2018-01-30_16-57-32
• python ./tools/train_net.py --device GPU --device_id 0 --weights data/pretrain_model/VGG_imagenet.npy --imdb /home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/data/VOCdevkit16/VOCdevkit/VOC2007/ImageSets/Main/voc_2007_trainval --iters 70000 --cfg experiments/cfgs/faster_rcnn_end2end.yml --network VGGnet_train I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.so.8.0 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.so.5 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.so.8.0 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.so.1 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.so.8.0 locally voc_2007_train voc_2007_val voc_2007_trainval voc_2007_test kitti_train kitti_val kitti_trainval kitti_test nthu_71 nthu_370 Called with args: Namespace(cfg_file='experiments/cfgs/faster_rcnn_end2end.yml', device='GPU', device_id=0, imdb_name='/home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/data/VOCdevkit16/VOCdevkit/VOC2007/ImageSets/Main/voc_2007_trainval', max_iters=70000, network_name='VGGnet_train', pretrained_model='data/pretrain_model/VGG_imagenet.npy', randomize=False, set_cfgs=None, solver=None) Using config: {'DATA_DIR': '/home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/data', 'DEDUP_BOXES': 0.0625, 'EPS': 1e-14, 'EXP_DIR': 'faster_rcnn_end2end', 'GPU_ID': 0, 'IS_MULTISCALE': False, 'MATLAB': 'matlab', 'MODELS_DIR': '/home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/models/pascal_voc', 'PIXEL_MEANS': array([[[ 102.9801, 115.9465, 122.7717]]]), 'RNG_SEED': 3, 'ROOT_DIR': '/home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes', 'TEST': {'BBOX_REG': True, 'DEBUG_TIMELINE': False, 'HAS_RPN': True, 'MAX_SIZE': 1000, 'NMS': 0.3, 'PROPOSAL_METHOD': 'selective_search', 'RPN_MIN_SIZE': 16, 'RPN_NMS_THRESH': 0.7, 'RPN_POST_NMS_TOP_N': 300, 'RPN_PRE_NMS_TOP_N': 6000, 'SCALES': [600], 'SVM': False}, 'TRAIN': {'ASPECT_GROUPING': 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, 'BBOX_REG': True, 'BBOX_THRESH': 0.5, 'BG_THRESH_HI': 0.5, 'BG_THRESH_LO': 0.0, 'DEBUG_TIMELINE': False, 'DISPLAY': 10, 'FG_FRACTION': 0.25, 'FG_THRESH': 0.5, 'GAMMA': 0.1, 'HAS_RPN': True, 'IMS_PER_BATCH': 1, 'LEARNING_RATE': 0.001, 'MAX_SIZE': 1000, 'MOMENTUM': 0.9, 'PROPOSAL_METHOD': 'gt', '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_MIN_SIZE': 16, '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': [600], 'SNAPSHOT_INFIX': '', 'SNAPSHOT_ITERS': 5000, 'SNAPSHOT_PREFIX': 'VGGnet_fast_rcnn', 'STEPSIZE': 5000, 'USE_FLIPPED': True, 'USE_PREFETCH': False}, 'USE_GPU_NMS': True} Traceback (most recent call last): File "./tools/train_net.py", line 81, in imdb = get_imdb(args.imdb_name) File "/home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/tools/../lib/datasets/factory.py", line 82, in get_imdb raise KeyError('Unknown dataset: {}'.format(name)) KeyError: 'Unknown dataset: /home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/data/VOCdevkit16/VOCdevkit/VOC2007/ImageSets/Main/voc_2007_trainval'

Kindly help. Totally new to this @smallcorgi

[woxihuanchirou]

try to use /home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/data/VOCdevkit2007/VOC2007/ImageSets/Main/voc_2007_trainval instead of /home/nvidia/TensorFlowTX2/Faster-RCNN_TF_changes/data/VOCdevkit16/VOCdevkit/VOC2007/ImageSets/Main/voc_2007_trainval