Difference between revisions of "DSC180F20W3"
From Immersive Visualization Lab Wiki
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| − | =Week 3= | + | =Week 3: COCO Dataset= |
==Reading== | ==Reading== | ||
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==Programming== | ==Programming== | ||
| − | You can do this week's programming assignment on your own computer, or on the cluster. The advantage of using the cluster is that the COCO data set | + | You can do this week's programming assignment on your own computer, or on the DSMLP cluster. The advantage of using the cluster is that the COCO data set has already been downloaded to it. |
| − | + | ||
| − | + | Download the [https://github.com/cocodataset/cocoapi COCO API] and get the Python API to work (no need to deal with Matlab or Lua). | |
| − | For your Participation submission, describe the demo in a few sentences, and report on a few obstacles you encountered in getting the demo to work. | + | Run the demo at: <tt>cocoapi/PythonAPI/pycocoDemo.ipynb</tt> |
| + | |||
| + | For your Week 3 Participation submission, describe the demo in a few sentences, and report on a few obstacles you encountered in getting the demo to work. | ||
Revision as of 22:50, 13 October 2020
Week 3: COCO Dataset
Reading
Browse the COCO dataset website and read the paper.
Programming
You can do this week's programming assignment on your own computer, or on the DSMLP cluster. The advantage of using the cluster is that the COCO data set has already been downloaded to it.
Download the COCO API and get the Python API to work (no need to deal with Matlab or Lua).
Run the demo at: cocoapi/PythonAPI/pycocoDemo.ipynb
For your Week 3 Participation submission, describe the demo in a few sentences, and report on a few obstacles you encountered in getting the demo to work.
