car_detection AP: 0.000000 0.000000 0.000000

[sarimmehdi]

Hello. I am running your code and it gives me 0.0 detection AP. I am also using my own dataset but I made the detection files as is needed by your code. This is my log output after running:
python train/test_net_det.py --cfg cfgs/det_sample.yaml OUTPUT_DIR pretrained_models/car TEST.WEIGHTS pretrained_models/car/model_0050.pth

The log output:

YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
  return yaml.load(cfg_to_load)
config:
 {'DATA': {'CAR_ONLY': True,
          'DATA_ROOT': 'kitti/data/pickle_data',
          'EXTEND_FROM_DET': False,
          'FILE': 'datasets/provider_sample.py',
          'HEIGHT_HALF': (0.25, 0.5, 1.0, 2.0),
          'NUM_HEADING_BIN': 12,
          'NUM_SAMPLES': 154,
          'NUM_SAMPLES_DET': 154,
          'PEOPLE_ONLY': False,
          'RTC': True,
          'STRIDE': (0.25, 0.5, 1.0, 2.0),
          'WITH_EXTRA_FEAT': False},
 'EVAL_MODE': False,
 'FROM_RGB_DET': True,
 'IOU_THRESH': 0.7,
 'LOSS': {'BOX_LOSS_WEIGHT': 1.0,
          'CORNER_LOSS_WEIGHT': 10.0,
          'HEAD_REG_WEIGHT': 20.0,
          'SIZE_REG_WEIGHT': 20.0},
 'MODEL': {'FILE': 'models/det_base.py', 'NUM_CLASSES': 2},
 'NUM_GPUS': 1,
 'NUM_WORKERS': 4,
 'OUTPUT_DIR': 'pretrained_models/car',
 'OVER_WRITE_TEST_FILE': '',
 'RESUME': False,
 'SAVE_SUB_DIR': 'val_nms',
 'TEST': {'BATCH_SIZE': 32,
          'DATASET': 'val',
          'METHOD': 'nms',
          'THRESH': 0.1,
          'WEIGHTS': 'pretrained_models/car/model_0050.pth'},
 'TRAIN': {'BASE_LR': 0.001,
           'BATCH_SIZE': 32,
           'DATASET': 'train',
           'GAMMA': 0.1,
           'LR_POLICY': 'step',
           'LR_STEPS': [20],
           'MAX_EPOCH': 50,
           'MIN_LR': 1e-05,
           'MOMENTUM': 0.9,
           'OPTIMIZER': 'adam',
           'START_EPOCH': 0,
           'WEIGHTS': '',
           'WEIGHT_DECAY': 0.0001},
 'USE_TFBOARD': True,
 'disp': 100}
load dataset from kitti/data/pickle_data/frustum_caronly_val_rgb_detection.pickle
=> loaded checkpoint 'pretrained_models/car/model_0050.pth')
0/1 0.017
Average time:
batch:0.017
avg_per_object:0.001
avg_per_image:0.008
./train/kitti_eval/evaluate_object_3d_offline data/kitti/training/label_2/ pretrained_models/car/val_nms/result 2>&1 | tee -a  pretrained_models/car/val_nms/result/log_test.txt
mkdir: cannot create directory ‘pretrained_models/car/val_nms/result/plot’: File exists
PDFCROP 1.38, 2012/11/02 - Copyright (c) 2002-2012 by Heiko Oberdiek.
==> 1 page written on `car_detection.pdf'.
PDFCROP 1.38, 2012/11/02 - Copyright (c) 2002-2012 by Heiko Oberdiek.
==> 1 page written on `car_detection_ground.pdf'.
PDFCROP 1.38, 2012/11/02 - Copyright (c) 2002-2012 by Heiko Oberdiek.
==> 1 page written on `car_detection_3d.pdf'.
Thank you for participating in our evaluation!
Loading detections...
number of files for evaluation: 154
  done.
save pretrained_models/car/val_nms/result/plot/car_detection.txt
car_detection AP: 0.000000 0.000000 0.000000
Finished 2D bounding box eval.
Going to eval ground for class: car
save pretrained_models/car/val_nms/result/plot/car_detection_ground.txt
car_detection_ground AP: 0.000000 0.000000 0.000000
Finished Birdeye eval.
Going to eval 3D box for class: car
save pretrained_models/car/val_nms/result/plot/car_detection_3d.txt
car_detection_3d AP: 0.000000 0.000000 0.000000
Finished 3D bounding box eval.
Your evaluation results are available at:
pretrained_models/car/val_nms/result

Process finished with exit code 0