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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.

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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.

Thanks for the response!

AdaptiveDetector definitely did a better job, will append these new stats to the post:

precision 0.397, recall 0.727, F1 0.513, mean temporal error 0.307 s

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