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there is a trap here:

    Mat result = net.forward();

result is a shallow copy of the last dnn output layer, so if you call your eval() function twice, both results will point to the very same data ! (the last evaluation)

the remedy is to clone() the result, like:

    Mat result = net.forward().clone(); // "deep" copy !

(and yea, i've beeen bitten by that before, too. painful learning curve, there ..)

there is a (c++ specific) trap here:

    Mat result = net.forward();

result is a shallow copy of the last dnn output layer, so if you call your eval() function twice, both results will point to the very same data ! (the last evaluation)

the remedy is to clone() the result, like:

    Mat result = net.forward().clone(); // "deep" copy !

(and yea, i've beeen bitten by that before, too. painful learning curve, there ..)