In this post, I would like to share my practice with Facebook’s new Detectron2 package on macOS without GPU support for street view panoptic segmentation. If you want to create the following video by yourself, this post is all you need. This demo video clip is from my car’s dashcam footages from Preston, Melbourne. I used the PyTorch and Detectron2 to create this video with segmentation masks.
Phase 1: Problem assessment – Determine the problem’s characteristics.
What is an intelligent system?
The process of building Intelligent knowledge-based system has been called knowledge engineering since the 80s. It usually contains six phases: 1. Problem assessment; 2. Data and knowledge acquisition; 3. Development of a prototype system; 4. Development of a complete system; 5. Evaluation and revision of the system; 6. Integration and maintenance of the system .
When I am using TensorFlow on my MacBook Air, I always get annoyed by the warnings comes from nowhere, so I followed the documentation below to build TensorFlow sources into a TensorFlow binary and installed it successfully. In theory, this will make the TF running faster on my machine.
Python is a great general-purpose programming language on its own, but with the help of a few popular libraries (Numpy, SciPy, Matplotlib, TensorFlow) it becomes a powerful environment for scientific computing and data analysis.
I start sharing my notebooks on learning Python and TensorFlow, here is my GitHub repository: Data_Science_Python.
You could download my compiled Apk file here and install on your android device (>Android 7.0) (22-May-2018).
Update: 25-May-2018, fixed the bug of object tracking function in TF Detect. PS: While running the activities, pressing the volume keys on your device will
toggle debug visualizations on/off, rendering additional info to the screen that
may be useful for development purposes.
In the last post, I just tried the TensorFlow for object classification (TF Classify). This time I installed all four demos of the TensorFlow Mobile for Android according to this tutorial: TensorFlow Lite Demo for Android. They are awesome 😛
The original program is written in Python, and uses [PyTorch], [SciPy]. A GPU is not necessary but can provide a significant speedup especially for training a new model. Regular sized images can be styled on a laptop or desktop using saved models.
More details about the algorithm could be found in the following papers: