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>Realtime Object Recognition
- Nov, 2019
While taking a famous (as all others start with) coursera's Machine Learning course, I decided to explore some of the open source API with more practical applications. The first attempt was to run real-time object recogntion in PC environment. I referred to lots of detailed steps from towardsdatascience.com
DEVELOPMENT
Environment : MacOS, Tensorflow CPU Resource : Tensorflow Object Detection API / OpenCV / Python 3.6 Pre-trained model : detection model ZOO trained on COCO Dataset
Google's Object Recognition API provides most of the code to train/evaluate/deploy customized recognition models farely easily. The most of the time will be taken in the process of taking various picture in different environment, occluded with different objects etc. and labeling those pictures manually. The detailed process can be found in this Youtube video
MY RESULT
Environment : MacOS, Tensorflow CPU Resource : Tensorflow Object Detection API / OpenCV / Python 3.6 Pre-trained model : detection model ZOO trained on COCO Dataset
The first video is tested with SSD MobileNet with Tensorflow CPU installed in MacOS, and the second one with Yolo v2 with Tensorflow GPU (CUDA 9.0/CUDNN 7.0) with Surfacebook 2.