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CNTK Image Detection FAST R-CNN not working on custom image data set?

Question
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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:
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(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
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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,
- Edited by Rudgr Wednesday, January 24, 2018 3:32 PM
Wednesday, January 24, 2018 3:29 PM
Answers
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Hi,
This is a question best suited for the CNTK team. You can file an issue on their GitHub page or ask a question on StackOverflow with the CNTK tag.
Thanks,
Paul
- Marked as answer by Paul Shealy [MSFT]Microsoft employee Wednesday, January 24, 2018 11:51 PM
Wednesday, January 24, 2018 11:51 PM
All replies
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Hi,
This is a question best suited for the CNTK team. You can file an issue on their GitHub page or ask a question on StackOverflow with the CNTK tag.
Thanks,
Paul
- Marked as answer by Paul Shealy [MSFT]Microsoft employee Wednesday, January 24, 2018 11:51 PM
Wednesday, January 24, 2018 11:51 PM -
tx paul!Thursday, January 25, 2018 7:44 AM