I’ve been doing the Hello AI World tutorial and am on the " Re-training on the Cat/Dog Dataset" lesson: https://github.com/dusty-nv/jetson-inference/blob/master/docs/pytorch-cat-dog.md
Everything seems to work without error. But when I run the video feed, everything (walls, person, etc) is classified as 50% dog. When I point the video camera at an actual dog, the percentage jumps up to 65% or so.
That level of accuracy seems disappointing. Are there any pointers for improving this? Have these types of results been seen with others, or is this type of result an indicator of incorrect training? Perhaps a video feed has less accurate results than a single still image?
Any advice is appreciated.