Changes between Initial Version and Version 1 of tutorials/smart-city

Timestamp:

Oct 31, 2019, 1:50:57 AM (5 years ago)

Author:

wuyangzhang

Comment:

—

tutorials/smart-city

@@ +1 @@
+=== Smart City
+
+Smart city is a demo application that shows how to deploy a real-time edge application on COMOS. This application takes the real-time video streaming as the input, running deep learning algorithms to detect object of interest, and putting masks upon them. 
+
+The video camera is installed on Amsterdam Avenue, NY and delivers various resolutions at different frame rates. In this demo, we take H265 640 x 480 Constant rate 30 fps with 1024 Kbps. The backend object masking algorithm comes from the latest research work at Facebook https://github.com/facebookresearch/maskrcnn-benchmark. 
+
+=== Pre-set-up:
+1. Create a reservation
+1. Log into the console
+1. Load image: {{{ omf load -t srv3-lg1.bed.cosmos-lab.org -i baseline.ndz -r 40}}}
+1. Turn the node on: {{{ omf tell -a on -t srv3-lg1.bed.cosmos-lab.org }}}
+
+Next, we download a pre-configured container in order to minimize your experimental efforts. 
+
+{{{docker push qingshanyouyou/smartcity:tagname}}}
+
+Go to the container.
+
+{{{nvidia-docker container run -it qingshanyouyou/smartcity:tagname bash}}}
+
+Go to the script folder. 
+
+{{{cd /maskrcnn-benchmark/demo}}}
+
+Run the python script. 
+
+{{{python smartcity.py}}}
+
+After running the python script, you will get the output video file named "output.avi". Note that we take a file to record the real-time processing result because of the slow forwarding speed from X11. 
+
+Now, enjoy the video!