Shadowless
The more fast your are, the more shadowless you got.
The 3 main part of shadowless are:
- Detection: this part implements many state-of-art detection algorithms to detect objects;
- Segmentation: currently we seg only on objects;
- Lane Detect: this will tell vehicle where should to ride and avoid touch the lane in 2 sides.
Preparation
You need to do some setups to run Shadowless, you should download mxnet_ssd model from mxnet official examples repo.
and you should download one video from Youtube or anywhere place it into: videos/ directory. then:
sudo pip3 install -r requirements.txt
Please do 2 steps before you start running python3 main.py:
- Download the pretrained model from here, currently you should download
Resnet-50 512x512, directly download url is here, after downloaded untar it into mxnet_ssd/model dir; - You should install mxnet with the newest version.
- Mask-RCNN backend for detection will release very soon
Run
To run Shadowless after you get all pre-requirements, you can simply do:
python3 main.py
this will start a Shadowless master process to serve camera inputs and do the perception jobs.
Contribute
So much welcome the community contribute your code to Shadowless, we are now need those features:
-
Detection with SSD
-
Detection with FasterRCNN
-
Detection with RFCN
-
Lane Segment using OpenCV
-
Lane Segment with DeepLearning methods
-
Distance estimate with Objects
-
Speed estimate with moving objects
-
Accelerate whole networks to a real-time speed.
Copyright
this work inspired by Jin Fagang, you should not spread this soft-ware witout any guarantee, please using this under Apache License.