cfg_file: config/CenterNet-104-NightTransferPlums.json
loading all datasets...
split: test
looking for label files at /home/jasper/Datasets/NightPlumsCoco/coco/annotations/instances_nighttest.json
Loading dataset normalisation values from python file
loading from cache file: cache/coco_nighttest.pkl
loading annotations into memory...
Done (t=0.00s)
creating index...
index created!
system config...
{'batch_size': 2,
 'cache_dir': 'cache',
 'chunk_sizes': [2],
 'config_dir': 'config',
 'data_dir': '/home/jasper/Datasets/NightPlumsCoco',
 'data_rng': <mtrand.RandomState object at 0x7f1676e5f0d8>,
 'dataset': 'NIGHTPLUMS',
 'decay_rate': 10,
 'display': 5,
 'learning_rate': 0.00025,
 'max_iter': 480000,
 'nnet_rng': <mtrand.RandomState object at 0x7f1676e5f120>,
 'opt_algo': 'adam',
 'prefetch_size': 6,
 'pretrain': '/home/jasper/git/CEIG/CenterNet/cache/nnet/CenterNet-104_480000.pkl',
 'result_dir': 'results',
 'sampling_function': 'kp_detection',
 'snapshot': 20,
 'snapshot_name': 'CenterNet-104-NightTransferPlums',
 'stepsize': 450000,
 'test_split': 'test',
 'train_split': 'train',
 'val_iter': 20,
 'val_split': 'val',
 'weight_decay': False,
 'weight_decay_rate': 1e-05,
 'weight_decay_type': 'l2'}
db config...
{'ae_threshold': 0.5,
 'border': 128,
 'categories': 1,
 'data_aug': True,
 'gaussian_bump': True,
 'gaussian_iou': 0.7,
 'gaussian_radius': -1,
 'input_size': [511, 511],
 'kp_categories': 1,
 'lighting': True,
 'max_per_image': 100,
 'merge_bbox': False,
 'nms_algorithm': 'exp_soft_nms',
 'nms_kernel': 3,
 'nms_threshold': 0.5,
 'output_sizes': [[128, 128]],
 'rand_color': True,
 'rand_crop': True,
 'rand_pushes': False,
 'rand_samples': False,
 'rand_scale_max': 1.4,
 'rand_scale_min': 0.6,
 'rand_scale_step': 0.1,
 'rand_scales': array([0.6, 0.7, 0.8, 0.9, 1. , 1.1, 1.2, 1.3]),
 'special_crop': False,
 'test_scales': [1],
 'top_k': 70,
 'weight_exp': 8}
loading parameters at iteration: 1920
building neural network...
module_file: models.CenterNet-104-NightTransferPlums
total parameters: 209941142
loading parameters...
loading model from cache/nnet/CenterNet-104-NightTransferPlums/CenterNet-104-NightTransferPlums_1920.pkl
Testing on a total of 87 images
locating kps:   0%|                                      | 0/87 [00:00<?, ?it/s]/home/jasper/anaconda3/envs/CenterNet/lib/python3.6/site-packages/torch/nn/modules/upsampling.py:122: UserWarning: nn.Upsampling is deprecated. Use nn.functional.interpolate instead.
  warnings.warn("nn.Upsampling is deprecated. Use nn.functional.interpolate instead.")
locating kps: 100%|█████████████████████████████| 87/87 [00:23<00:00,  3.70it/s]
Running detections on test set took 23.503639936447144 sec
Loading and preparing results...
DONE (t=0.02s)
creating index...
index created!
Running per image evaluation...
Evaluate annotation type *bbox*
DONE (t=0.65s).
Accumulating evaluation results...
DONE (t=0.05s).
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.432
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.763
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.444
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.214
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.497
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.442
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.155
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.493
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.568
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.413
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.602
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.681
Running per image evaluation...
Evaluate annotation type *bbox*
DONE (t=0.59s).
Accumulating evaluation results...
DONE (t=0.05s).
 False discovery    (FD) @[ IoU=0.05:0.50 | area=   all | maxDets=100 ] = 0.143
 False discovery    (FD) @[ IoU=0.05      | area=   all | maxDets=100 ] = 0.099
 False discovery    (FD) @[ IoU=0.25      | area=   all | maxDets=100 ] = 0.119
 False discovery    (FD) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.237
 False discovery    (FD) @[ IoU=0.05:0.50 | area= small | maxDets=100 ] = 0.275
 False discovery    (FD) @[ IoU=0.05:0.50 | area=medium | maxDets=100 ] = 0.079
 False discovery    (FD) @[ IoU=0.05:0.50 | area= large | maxDets=100 ] = 0.322