1. What if you want to classify pictures that have different sizes (not too uncommon)? Wont work because you first have to set a fixed number of neurons in your first layer.
All images are scaled to the same dimensions determined by the sample resolution settings.
2. What about different locations of the same object?
This problem is not adresed here. Suggested approach can be used on whole images or specific known image locations.
Hi, you're right when you say the Neuroph has always been open source, but the image recognition used by http://dota-autoscript.com/ has not been open source. With this release of Neuroph we added the image recognition support based on ideas and original code from http://dota-autoscript.com./
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1. What if you want to classify pictures that have different sizes (not too uncommon)? Wont work because you first have to set a fixed number of neurons in your first layer.
All images are scaled to the same dimensions determined by the sample resolution settings.
2. What about different locations of the same object?
This problem is not adresed here. Suggested approach can be used on whole images or specific known image locations.
Hi, you're right when you say the Neuroph has always been open source, but the image recognition used by http://dota-autoscript.com/ has not been open source. With this release of Neuroph we added the image recognition support based on ideas and original code from http://dota-autoscript.com./