resolve conflict GN-dev with master

tools/test.py

@@ -14,15 +14,16 @@ from mmdet.models import build_detector, detectors
 def single_test(model, data_loader, show=False):
     model.eval()
     results = []
-    prog_bar = mmcv.ProgressBar(len(data_loader.dataset))
+    dataset = data_loader.dataset
+    prog_bar = mmcv.ProgressBar(len(dataset))
     for i, data in enumerate(data_loader):
         with torch.no_grad():
             result = model(return_loss=False, rescale=not show, **data)
         results.append(result)
 
         if show:
-            model.module.show_result(data, result,
-                                     data_loader.dataset.img_norm_cfg)
+            model.module.show_result(data, result, dataset.img_norm_cfg,
+                                     dataset.CLASSES)
 
         batch_size = data['img'][0].size(0)
         for _ in range(batch_size):
@@ -65,6 +66,9 @@ def main():
         raise ValueError('The output file must be a pkl file.')
 
     cfg = mmcv.Config.fromfile(args.config)
+    # set cudnn_benchmark
+    if cfg.get('cudnn_benchmark', False):
+        torch.backends.cudnn.benchmark = True
     cfg.model.pretrained = None
     cfg.data.test.test_mode = True
 

tools/train.py

@@ -8,12 +8,15 @@ from mmdet.datasets import get_dataset
 from mmdet.apis import (train_detector, init_dist, get_root_logger,
                         set_random_seed)
 from mmdet.models import build_detector
+import torch
 
 
 def parse_args():
     parser = argparse.ArgumentParser(description='Train a detector')
     parser.add_argument('config', help='train config file path')
     parser.add_argument('--work_dir', help='the dir to save logs and models')
+    parser.add_argument(
+        '--resume_from', help='the checkpoint file to resume from')
     parser.add_argument(
         '--validate',
         action='store_true',
@@ -40,9 +43,14 @@ def main():
     args = parse_args()
 
     cfg = Config.fromfile(args.config)
+    # set cudnn_benchmark
+    if cfg.get('cudnn_benchmark', False):
+        torch.backends.cudnn.benchmark = True
     # update configs according to CLI args
     if args.work_dir is not None:
         cfg.work_dir = args.work_dir
+    if args.resume_from is not None:
+        cfg.resume_from = args.resume_from
     cfg.gpus = args.gpus
     if cfg.checkpoint_config is not None:
         # save mmdet version in checkpoints as meta data
@@ -67,6 +75,7 @@ def main():
 
     model = build_detector(
         cfg.model, train_cfg=cfg.train_cfg, test_cfg=cfg.test_cfg)
+
     train_dataset = get_dataset(cfg.data.train)
     train_detector(
         model,

tools/voc_eval.py

+from argparse import ArgumentParser
+
+import mmcv
+import numpy as np
+
+from mmdet import datasets
+from mmdet.core import eval_map
+
+
+def voc_eval(result_file, dataset, iou_thr=0.5):
+    det_results = mmcv.load(result_file)
+    gt_bboxes = []
+    gt_labels = []
+    gt_ignore = []
+    for i in range(len(dataset)):
+        ann = dataset.get_ann_info(i)
+        bboxes = ann['bboxes']
+        labels = ann['labels']
+        if 'bboxes_ignore' in ann:
+            ignore = np.concatenate([
+                np.zeros(bboxes.shape[0], dtype=np.bool),
+                np.ones(ann['bboxes_ignore'].shape[0], dtype=np.bool)
+            ])
+            gt_ignore.append(ignore)
+            bboxes = np.vstack([bboxes, ann['bboxes_ignore']])
+            labels = np.concatenate([labels, ann['labels_ignore']])
+        gt_bboxes.append(bboxes)
+        gt_labels.append(labels)
+    if not gt_ignore:
+        gt_ignore = gt_ignore
+    if hasattr(dataset, 'year') and dataset.year == 2007:
+        dataset_name = 'voc07'
+    else:
+        dataset_name = dataset.CLASSES
+    eval_map(
+        det_results,
+        gt_bboxes,
+        gt_labels,
+        gt_ignore=gt_ignore,
+        scale_ranges=None,
+        iou_thr=iou_thr,
+        dataset=dataset_name,
+        print_summary=True)
+
+
+def main():
+    parser = ArgumentParser(description='VOC Evaluation')
+    parser.add_argument('result', help='result file path')
+    parser.add_argument('config', help='config file path')
+    parser.add_argument(
+        '--iou-thr',
+        type=float,
+        default=0.5,
+        help='IoU threshold for evaluation')
+    args = parser.parse_args()
+    cfg = mmcv.Config.fromfile(args.config)
+    test_dataset = mmcv.runner.obj_from_dict(cfg.data.test, datasets)
+    voc_eval(args.result, test_dataset, args.iou_thr)
+
+
+if __name__ == '__main__':
+    main()