Awesome to see this! I actually wrote PySceneDetect, was great to see it getting some use here. Would you be willing to share what parameters you were using? I'm curious why the accuracy was so low.
PySceneDetect only uses basic heuristic methods right now so it does require some degree of tuning to get things working for certain data sets. Your post inspired me to look into maybe integrating TransNetV2 as a detector in the future!
Nice to see you on here! I used the ContentDetector with a threshold of 27.0 and otherwise default parameters. Realize I could have done a grid sweep to really hone in on a good param range, but because I had only one input video labeled I wanted something that would work well enough out of the box. I imagine this dataset is rather... heterogenous.
If you happen to know a better apriori threshold I would be happy to re-run the analysis and update the chart.
If you're willing, could you try using AdaptiveDetector? It should have better defaults for handling fast camera movements a bit better.
The threshold values themselves can be tuned if you generate a statsfile and plot the result, but that can sometimes be tedious if you have a lot of files (thus the huge interest in methods like TransNetV2). Glad to see the real world applications of those in action. You can always just increase/decrease the threshold by 5-10% depending on if you find it's too sensitive or not sensitive enough as well.
PySceneDetect only uses basic heuristic methods right now so it does require some degree of tuning to get things working for certain data sets. Your post inspired me to look into maybe integrating TransNetV2 as a detector in the future!