GitLab

In reader.py, GFile returns an object of type bytes independently from the Python version. Therefore, the object must be decoded as string in any case. Removed the check of Python version

Add back six dependency and change pbtxt files to reflect new way of …

Replace in-memory DastaSet with FixedLengthRecordDataSet

In-memory DataSet initiated without feed_dict are saved in TF graph def,
causing exported graph.pbtxt over-bloated.
Change to FixedLengthRecordDataSet and does a few refactorization.

* We do this because we want rules outside of slim to be able to depend on it in order to pull in slim models.

Add back six dependency and change pbtxt files to reflect new way of using own data to train object recognition models

Fixing small typo in CONTRIBUTING.md

Add slim/scripts/finetune_inception_resnet_v2_on_flowers.sh

Make object_detection dictionaries compatible with Python3

Also fixes some typos in other scripts.

Update directories in running_pets.md

Correct documentation so all commands should be run from the root
of the git directory.

Update directories in running_pets.md

Also clarifies usage on label maps. In a nutshell, label map IDs
should start at index 1 (and not include 0).

Fix reversions plus a few improvements

Implementation of PCL and other newly proposed algorithms

* Change dictionnaries iteritems() to items()

CIFAR-10 Estimator-based example for multi-device training

Fix compatibility for object_detection/core/batcher.py

Fix CDNA transformation bug and speed up its implementation.

_strict_random_crop_image: fix mask slice

Minor typo obj detection's preparing_inputs.md

Make object detection's installation instruction more obvious

Also use the url link to github because *.md files are not
rendered when using jupyter notebook

- Fix CDNA transformation bug where transformed channels of color and masks were combined incorrectly.
- Remove for loop over batch size in implementation of CDNA transformation. This speeds up the building of the graph.