the false positive rate & detection rate setting for each classification in the cascade framework

[hesperxxz]

Hi luoyetx, thanks for your code.
In your config.json, for each cart,
detection rate = 1 - drop_n / number_of_positive_samples = 1-2/50000 = 0.99996
max false positive rate = 1 - restart.th = 0.999
Therefore, the final detection rate is pow(0.99996, 5405) = 0.8976
the final false positive rate = pow(0.999, 5405) = 0.0671
Is that right? Maybe the DR is a little low and the FPR is too high.

[luoyetx]

@hesperxxz your formula is right. And I think I'm using number_of_positive_samples = 100,000 (not all of them has landmark points). And I only trained 2700 carts.

The FPR you calculates is not the truth. Actually max false positive rate < 1 - restart.th, it will be much smaller than 0.999. I think the final FR will be 1e-5, that small.