time python ./tools/test_net.py --imdb plums_night_test --model /media/jasper/bigData/FasterRCNN-Output/Results/NightResults/vgg16_faster_rcnn_iter_28500.ckpt --cfg experiments/cfgs/vgg16.yml --net vgg16 --set ANCHOR_SCALES '[8,16,32]' ANCHOR_RATIOS '[0.5,1,2]' Called with args: Namespace(cfg_file='experiments/cfgs/vgg16.yml', comp_mode=False, imdb_name='plums_night_test', max_per_image=100, model='/media/jasper/bigData/FasterRCNN-Output/Results/NightResults/vgg16_faster_rcnn_iter_28500.ckpt', net='vgg16', set_cfgs=['ANCHOR_SCALES', '[8,16,32]', 'ANCHOR_RATIOS', '[0.5,1,2]'], tag='') /home/jasper/git/tf-faster-rcnn/tools/../lib/model/config.py:362: 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)) Using config: {'ANCHOR_RATIOS': [0.5, 1, 2], 'ANCHOR_SCALES': [8, 16, 32], 'DATA_DIR': '/home/jasper/git/tf-faster-rcnn/data', 'EXP_DIR': 'vgg16', 'MATLAB': 'matlab', 'MOBILENET': {'DEPTH_MULTIPLIER': 1.0, 'FIXED_LAYERS': 5, 'REGU_DEPTH': False, 'WEIGHT_DECAY': 4e-05}, 'PIXEL_MEANS': array([[[102.9801, 115.9465, 122.7717]]]), 'POOLING_MODE': 'crop', 'POOLING_SIZE': 7, 'RESNET': {'FIXED_BLOCKS': 1, 'MAX_POOL': False}, 'RNG_SEED': 3, 'ROOT_DIR': '/home/jasper/git/tf-faster-rcnn', 'RPN_CHANNELS': 512, 'TEST': {'BBOX_REG': True, 'HAS_RPN': True, 'MAX_SIZE': 1000, 'MODE': 'nms', 'NMS': 0.3, 'PROPOSAL_METHOD': 'gt', 'RPN_NMS_THRESH': 0.7, 'RPN_POST_NMS_TOP_N': 300, 'RPN_PRE_NMS_TOP_N': 6000, 'RPN_TOP_N': 5000, 'SCALES': [600], 'SVM': False}, 'TRAIN': {'ASPECT_GROUPING': False, 'BATCH_SIZE': 256, '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, 'BIAS_DECAY': False, 'DISPLAY': 20, 'DOUBLE_BIAS': True, '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_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_ITERS': 250, 'SNAPSHOT_KEPT': 150, 'SNAPSHOT_PREFIX': 'vgg16_faster_rcnn', 'STEPSIZE': [10000], 'SUMMARY_INTERVAL': 180, 'TRUNCATED': False, 'USE_ALL_GT': True, 'USE_FLIPPED': True, 'USE_GT': False, 'WEIGHT_DECAY': 0.0001}, 'USE_E2E_TF': True, 'USE_GPU_NMS': True} 2020-07-14 16:12:19.589744: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. 2020-07-14 16:12:19.589760: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. 2020-07-14 16:12:19.589765: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. 2020-07-14 16:12:19.589769: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations. 2020-07-14 16:12:19.589773: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations. 2020-07-14 16:12:19.697180: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:893] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2020-07-14 16:12:19.697456: I tensorflow/core/common_runtime/gpu/gpu_device.cc:940] Found device 0 with properties: name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate (GHz) 1.721 pciBusID 0000:01:00.0 Total memory: 10.91GiB Free memory: 9.86GiB 2020-07-14 16:12:19.697470: I tensorflow/core/common_runtime/gpu/gpu_device.cc:961] DMA: 0 2020-07-14 16:12:19.697475: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0: Y 2020-07-14 16:12:19.697484: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:01:00.0) Loading model check point from /media/jasper/bigData/FasterRCNN-Output/Results/NightResults/vgg16_faster_rcnn_iter_28500.ckpt Loaded. im_detect: 1/87 1.062s 0.001s im_detect: 2/87 0.591s 0.001s im_detect: 3/87 0.432s 0.001s im_detect: 4/87 0.350s 0.001s im_detect: 5/87 0.309s 0.001s im_detect: 6/87 0.278s 0.001s im_detect: 7/87 0.255s 0.001s im_detect: 8/87 0.240s 0.001s im_detect: 9/87 0.228s 0.001s im_detect: 10/87 0.217s 0.001s im_detect: 11/87 0.207s 0.001s im_detect: 12/87 0.199s 0.001s im_detect: 13/87 0.193s 0.001s im_detect: 14/87 0.189s 0.001s im_detect: 15/87 0.183s 0.001s im_detect: 16/87 0.180s 0.001s im_detect: 17/87 0.176s 0.001s im_detect: 18/87 0.174s 0.001s im_detect: 19/87 0.171s 0.001s im_detect: 20/87 0.169s 0.001s im_detect: 21/87 0.166s 0.001s im_detect: 22/87 0.165s 0.001s im_detect: 23/87 0.163s 0.001s im_detect: 24/87 0.160s 0.001s im_detect: 25/87 0.158s 0.001s im_detect: 26/87 0.157s 0.001s im_detect: 27/87 0.155s 0.001s im_detect: 28/87 0.154s 0.001s im_detect: 29/87 0.152s 0.001s im_detect: 30/87 0.152s 0.001s im_detect: 31/87 0.151s 0.001s im_detect: 32/87 0.151s 0.001s im_detect: 33/87 0.149s 0.001s im_detect: 34/87 0.149s 0.001s im_detect: 35/87 0.148s 0.001s im_detect: 36/87 0.146s 0.001s im_detect: 37/87 0.146s 0.001s im_detect: 38/87 0.145s 0.001s im_detect: 39/87 0.144s 0.001s im_detect: 40/87 0.144s 0.001s im_detect: 41/87 0.143s 0.001s im_detect: 42/87 0.142s 0.001s im_detect: 43/87 0.142s 0.001s im_detect: 44/87 0.141s 0.001s im_detect: 45/87 0.141s 0.001s im_detect: 46/87 0.141s 0.001s im_detect: 47/87 0.141s 0.001s im_detect: 48/87 0.140s 0.001s im_detect: 49/87 0.140s 0.001s im_detect: 50/87 0.139s 0.001s im_detect: 51/87 0.139s 0.001s im_detect: 52/87 0.138s 0.001s im_detect: 53/87 0.138s 0.001s im_detect: 54/87 0.137s 0.001s im_detect: 55/87 0.137s 0.001s im_detect: 56/87 0.137s 0.001s im_detect: 57/87 0.137s 0.001s im_detect: 58/87 0.137s 0.001s im_detect: 59/87 0.137s 0.001s im_detect: 60/87 0.136s 0.001s im_detect: 61/87 0.136s 0.001s im_detect: 62/87 0.135s 0.001s im_detect: 63/87 0.135s 0.001s im_detect: 64/87 0.135s 0.001s im_detect: 65/87 0.134s 0.001s im_detect: 66/87 0.134s 0.001s im_detect: 67/87 0.134s 0.001s im_detect: 68/87 0.134s 0.001s im_detect: 69/87 0.134s 0.001s im_detect: 70/87 0.133s 0.001s im_detect: 71/87 0.134s 0.001s im_detect: 72/87 0.133s 0.001s im_detect: 73/87 0.133s 0.001s im_detect: 74/87 0.133s 0.001s im_detect: 75/87 0.133s 0.001s im_detect: 76/87 0.132s 0.001s im_detect: 77/87 0.132s 0.001s im_detect: 78/87 0.132s 0.001s im_detect: 79/87 0.132s 0.001s im_detect: 80/87 0.132s 0.001s im_detect: 81/87 0.131s 0.001s im_detect: 82/87 0.131s 0.001s im_detect: 83/87 0.131s 0.001s im_detect: 84/87 0.131s 0.001s im_detect: 85/87 0.130s 0.001s im_detect: 86/87 0.130s 0.001s im_detect: 87/87 0.130s 0.001s Detection saved to pickle real 0m19.578s user 0m12.206s sys 0m1.948s