Can't train pascal_voc

[litingsjj]

Hi, thanks for your codes! But when I run sh experiments/scripts/faster_rcnn_end2end.sh 1 VGG16 pascal_voc I got a error :
Traceback (most recent call last): File "./tools/train_net.py", line 109, in <module> imdb, roidb = combined_roidb(args.imdb_name) File "./tools/train_net.py", line 74, in combined_roidb roidbs = [get_roidb(s) for s in imdb_names.split('+')] File "./tools/train_net.py", line 67, in get_roidb roidb = get_training_roidb(imdb) File "/tools/../lib/fast_rcnn/train.py", line 128, in get_training_roidb imdb.append_flipped_images() File "/tools/../lib/datasets/imdb.py", line 116, in append_flipped_images assert (boxes[:, 2] >= boxes[:, 0]).all() AssertionError

[nqanh]

Do you train on Pascal VOC dataset (not IIT-AFF)? If you train on a different dataset, then you have to prepare the input in the right way. Please see Readme file for details.

[litingsjj]

@nqanh Yes, I train on Pascal_voc dataset, but I have no problem when I train faster rcnn or rfcn with this dataset. So the input prepared a right way, I think.

[thanhtoando]

Hi,
Faster RCNN and RFCN are only for detection. If you want to train with AffordanceNet, you should prepare the groundtruth mask for the segmentation. Please read the readme to create mask groundtruth.

[litingsjj]

@nqanh Hi, I solved this problem. But still have proble with training.

Traceback (most recent call last):
File "./tools/train_net.py", line 117, in
max_iters=args.max_iters)
File "AffordanceNet/tools/../lib/fast_rcnn/train.py", line 172, in train_net
model_paths = sw.train_model(max_iters)
File "/AffordanceNet/tools/../lib/fast_rcnn/train.py", line 111, in train_model
self.solver.step(1)
File "/AffordanceNet/tools/../lib/rpn/proposal_target_layer.py", line 106, in forward
rois_per_image, self._num_classes) #bbox_targets_oris: original gt of rois
File "/AffordanceNet/tools/../lib/rpn/proposal_target_layer.py", line 606, in _sample_rois
_get_bbox_regression_labels(bbox_target_data, num_classes)
File "/AffordanceNet/tools/../lib/rpn/proposal_target_layer.py", line 532, in _get_bbox_regression_labels
bbox_targets[ind, start:end] = bbox_target_data[ind, 1:] #gan gia tri tai class tuong ung la bbox_target_data, con lai la so 0
ValueError: could not broadcast input array from shape (4) into shape (0)

I think I haven't input top: 'seg_mask_inds'. And I have create .sm file, but how should I deal with it? Is put it into cache folder? It doesn't work. Can you help me? Thanks!