Hi,
I managed to run the sample grocery image data set on CNTK.
I then tried Running Fast R-CNN on my own data, as described below (on azure datascience virtual windows machine):
https://github.com/Microsoft/CNTK/tree/master/Examples/Image/Detection/FastRCNN
I annotated several image sets using VOTT and then tried running:
----------------------------------------
(py35) c:\\dsvm\\tools\\cntk\\Examples\\Image\\Detection\\utils\\annotations>python annotations_helper.py
(py35) c:\\dsvm\\tools\\cntk\\Examples\\Image\\Detection\\FastRCNN>python run_fast_rcnn.py
Selected CPU as the process wide default device.
Using base model: AlexNet
lr_per_sample: [0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.0001]
Training model for 20 epochs.
Training 56950164 parameters in 21 parameter tensors.
-------------------------------------------------------------------
Build info:
Built time: Sep 15 2017 07:42:54
Last modified date: Thu Sep 14 22:33:54 2017
Build type: Release
Build target: GPU
With 1bit-SGD: no
With ASGD: yes
Math lib: mkl
CUDA version: 9.0.0
CUDNN version: 6.0.21
Build Branch: HEAD
Build SHA1: 23878e5d1f73180d6564b6f907b14fe5f53513bb
MPI distribution: Microsoft MPI
MPI version: 7.0.12437.6
-------------------------------------------------------------------
PROGRESS: 0.00%
PROGRESS: 0.00%
PROGRESS: 0.00%
PROGRESS: 0.00%
Traceback (most recent call last):
File 'run_fast_rcnn.py', line 32, in <module>
trained_model = train_fast_rcnn(cfg)
File 'c:\\dsvm\\tools\\cntk\\Examples\\Image\\Detection\\FastRCNN\\FastRCNN_train.py', line 345, in train_fast_rcnn
data = od_minibatch_source.next_minibatch(min(cfg.MB_SIZE, cfg['DATA'].NUM_TRAIN_IMAGES - sample_count), input_map=input_map)
File 'c:\\dsvm\\tools\\cntk\\Examples\\Image\\Detection\\FastRCNN\\..\\utils\\od_mb_source.py', line 70, in next_minibatch
img_data, roi_data, img_dims, proposals, label_targets, bbox_targets, bbox_inside_weights = self.od_reader.get_next_input()
File 'c:\\dsvm\\tools\\cntk\\Examples\\Image\\Detection\\FastRCNN\\..\\utils\\od_reader.py', line 63, in get_next_input
img_data, img_dims = self._load_resize_and_pad_image(index)
File 'c:\\dsvm\\tools\\cntk\\Examples\\Image\\Detection\\FastRCNN\\..\\utils\\od_reader.py', line 215, in _load_resize_and_pad_image
self._prepare_annotations_proposals_and_stats(index, img)
File 'c:\\dsvm\\tools\\cntk\\Examples\\Image\\Detection\\FastRCNN\\..\\utils\\od_reader.py', line 181, in _prepare_annotations_proposals_and_stats
proposals = self._proposal_provider.get_proposals(index, img)
File 'c:\\dsvm\\tools\\cntk\\Examples\\Image\\Detection\\FastRCNN\\..\\utils\\proposal_helpers.py', line 277, in get_proposals
return compute_proposals(img, num_proposals, self._proposal_cfg)
File 'c:\\dsvm\\tools\\cntk\\Examples\\Image\\Detection\\FastRCNN\\..\\utils\\proposal_helpers.py', line 106, in compute_proposals
filtered_rects = filterRois(rects, img_w, img_h, roi_min_area, roi_max_area, roi_min_side, roi_max_side, roi_max_aspect_ratio)
File 'c:\\dsvm\\tools\\cntk\\Examples\\Image\\Detection\\FastRCNN\\..\\utils\\proposal_helpers.py', line 72, in filterRois
assert(len(filteredRects) > 0)
AssertionErrortx again
----------------------------------------
To rule out stuff I made a custom image set, with the same amount of images as the Grocery dataset and even placed it in the grocery dataset folder.
I attached my sample dataset annotated using VOTT.
I can send my custom annotated custom image dataset by DM/email.
Maybe someone can see what I'm doing wrong?
thanks in advance,
