[VTA] YoloV3 Support (#4887)
authorHua Jiang <huaj@xilinx.com>
Wed, 26 Feb 2020 23:52:28 +0000 (15:52 -0800)
committerGitHub <noreply@github.com>
Wed, 26 Feb 2020 23:52:28 +0000 (15:52 -0800)
commit09c55fd1f3354d2280bb792a252590ac6bd68e58
tree38ef3a32c1e759bcded24365c3187f8b869050ef
parent8e7e7792aafb9333a3f2b3fe9527249b9c987e54
[VTA] YoloV3 Support (#4887)

* [VTA] YoloV3 Support

Issue:
YoloV3 use some operator and logic that not get good support by
existing vta logic, like nn.pad, upsample, and 255 output channel.

Solution:
add related logic to let darknet YoloV3 can running on VTA

* Fix small(0, or 1 heigh/width) detect frame issue.

* add yolov3-tiny turtorial

* add os import

* address review comments.

* rename tutorial file with a short name.

* rename deploy_vision_on_vta.py into deploy_classification.py.

* address review comment, fix plint eror in deploy_detection.py
vta/python/vta/top/graphpack.py
vta/tutorials/frontend/deploy_classification.py [moved from vta/tutorials/frontend/deploy_vision_on_vta.py with 100% similarity]
vta/tutorials/frontend/deploy_detection.py [new file with mode: 0644]