* Add instance segmentation example - first version of training code
* Add MMOD options; get rid of the cache approach, and instead load all MMOD rects upfront
* Improve console output
* Set filter count
* Minor tweaking
* Inference - first version, at least compiles!
* Ignore overlapped boxes
* Ignore even small instances
* Set overlaps_ignore
* Add TODO remarks
* Revert "Set overlaps_ignore"
This reverts commit 65adeff1f8.
* Set result size
* Set label image size
* Take ignore-color into account
* Fix the cropping rect's aspect ratio; also slightly expand the rect
* Draw the largest findings last
* Improve masking of the current instance
* Add some perturbation to the inputs
* Simplify ground-truth reading; fix random cropping
* Read even class labels
* Tweak default minibatch size
* Learn only one class
* Really train only instances of the selected class
* Remove outdated TODO remark
* Automatically skip images with no detections
* Print to console what was found
* Fix class index problem
* Fix indentation
* Allow to choose multiple classes
* Draw rect in the color of the corresponding class
* Write detector window classes to ostream; also group detection windows by class (when ostreaming)
* Train a separate instance segmentation network for each classlabel
* Use separate synchronization file for each seg net of each class
* Allow more overlap
* Fix sorting criterion
* Fix interpolating the predicted mask
* Improve bilinear interpolation: if output type is an integer, round instead of truncating
* Add helpful comments
* Ignore large aspect ratios; refactor the code; tweak some network parameters
* Simplify the segmentation network structure; make the object detection network more complex in turn
* Problem: CUDA errors not reported properly to console
Solution: stop and join data loader threads even in case of exceptions
* Minor parameters tweaking
* Loss may have increased, even if prob_loss_increasing_thresh > prob_loss_increasing_thresh_max_value
* Add previous_loss_values_dump_amount to previous_loss_values.size() when deciding if loss has been increasing
* Improve behaviour when loss actually increased after disk sync
* Revert some of the earlier change
* Disregard dumped loss values only when deciding if learning rate should be shrunk, but *not* when deciding if loss has been going up since last disk sync
* Revert "Revert some of the earlier change"
This reverts commit 6c852124ef.
* Keep enough previous loss values, until the disk sync
* Fix maintaining the dumped (now "effectively disregarded") loss values count
* Detect cats instead of aeroplanes
* Add helpful logging
* Clarify the intention and the code
* Review fixes
* Add operator== for the other pixel types as well; remove the inline
* If available, use constexpr if
* Revert "If available, use constexpr if"
This reverts commit 503d4dd335.
* Simplify code as per review comments
* Keep estimating steps_without_progress, even if steps_since_last_learning_rate_shrink < iter_without_progress_thresh
* Clarify console output
* Revert "Keep estimating steps_without_progress, even if steps_since_last_learning_rate_shrink < iter_without_progress_thresh"
This reverts commit 9191ebc776.
* To keep the changes to a bare minimum, revert the steps_since_last_learning_rate_shrink change after all (at least for now)
* Even empty out some of the previous test loss values
* Minor review fixes
* Can't use C++14 features here
* Do not use the struct name as a variable name
