* update release/1.6 from develop

* update api

* fix config for obj365 model

* unify reader to dataloader

* add check_version

* Add benchmark (fps) in MODEL_ZOO doc

* fix train on VOC on multi-GPU hang

* not set persistable in parse_fetches

# Add VGG-SSD on VOC and COCO dataset.
# Add config and model zoo. 
# Refine bbox2out and draw_bbox:
    - Add bbox de-normalize in bbox2out function.
    - Remove bbox de-normalize in draw_bbox.

* add save best model & fix dcn configs

* fix easy problem

Add PaddleDetection docs & some model configs

* add voc_eval and yolo_darknet_voc

* add yolov3_darknet_voc in MODEL_ZOO

* fix default im_size

* fix MODEL_ZOO note

* fix is_bbox_normalized

* extract map to map_utils.py

* update yolov3_dorknet_voc mixup

* add yolov3_r34_voc

* add yolov3_mobilenet_v1_voc

* fix drop empty in VAL mode

* use cfg.num_classes

* assert metric valid

* enable difficulty can be None

* add comment for bbox_eval

* num_classes in retinanet

* add rpn recall function and class-aware rpn

* Rename object_detection to PaddleDetection
* Small fix for doc

* Tweak command line scripts

enable fine grained control of command flags parsing
switch to attribute style of accessing config options

* Break down visualization function

decouple it from IO operations

* Move flag parsing out of `main()`

* Fix a bug where `None` is returned instead of `{}`

* Rename `save_xxx` to `output_xxx` in command line flags

could be confusing since checkpoint is stored in `save_dir`

* Support image file extensions in upper case

* Unified object detection framework based on PaddlePaddle.
* Include algo: Faster, Mask, FPN, Cascade, RetinaNet, Yolo v3, SSD.