Why My map all 0?

[ACbccc]

I set 200 iteration to test, but get all 0 map, wtat's wrong with me ?

CUDA_VISIBLE_DEVICES=4 python test.py CenterNet-104 --testiter 200 --split validation cfg_file: config/CenterNet-104.json loading all datasets... split: minival loading from cache file: cache/coco_minival2014.pkl loading annotations into memory... Done (t=0.89s) creating index... index created! system config... {'batch_size': 4, 'cache_dir': 'cache', 'chunk_sizes': [2, 2], 'config_dir': 'config', 'data_dir': '/home/bianjc/datasets/CenterNet', 'data_rng': <mtrand.RandomState object at 0x7f8a43aaaab0>, 'dataset': 'MSCOCO', 'decay_rate': 10, 'display': 5, 'learning_rate': 0.00025, 'max_iter': 480000, 'nnet_rng': <mtrand.RandomState object at 0x7f8a43aaaaf8>, 'opt_algo': 'adam', 'prefetch_size': 6, 'pretrain': None, 'result_dir': 'results', 'sampling_function': 'kp_detection', 'snapshot': 5000, 'snapshot_name': 'CenterNet-104', 'stepsize': 450000, 'test_split': 'testdev', 'train_split': 'trainval', 'val_iter': 500, 'val_split': 'minival', 'weight_decay': False, 'weight_decay_rate': 1e-05, 'weight_decay_type': 'l2'} db config... {'ae_threshold': 0.5, 'border': 128, 'categories': 80, '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: 200 building neural network... module_file: models.CenterNet-104 total parameters: 210062960 loading parameters... loading model from cache/nnet/CenterNet-104/CenterNet-104_200.pkl locating kps: 100%|███████████████████████| 5000/5000 [3:25:05<00:00, 2.46s/it] Loading and preparing results... DONE (t=3.83s) creating index... index created! Running per image evaluation... Evaluate annotation type bbox DONE (t=49.52s). Accumulating evaluation results... DONE (t=12.57s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.002 Running per image evaluation... Evaluate annotation type bbox DONE (t=47.80s). Accumulating evaluation results... DONE (t=11.18s). False discovery (FD) @[ IoU=0.05:0.50 | area= all | maxDets=100 ] = 1.000 False discovery (FD) @[ IoU=0.05 | area= all | maxDets=100 ] = 0.999 False discovery (FD) @[ IoU=0.25 | area= all | maxDets=100 ] = 1.000 False discovery (FD) @[ IoU=0.50 | area= all | maxDets=100 ] = 1.000 False discovery (FD) @[ IoU=0.05:0.50 | area= small | maxDets=100 ] = 1.000 False discovery (FD) @[ IoU=0.05:0.50 | area=medium | maxDets=100 ] = 1.000 False discovery (FD) @[ IoU=0.05:0.50 | area= large | maxDets=100 ] = 0.999

[Duankaiwen]

@ACbccc 200 iterations is too short