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@@ -453,7 +453,7 @@ Phew. Let's get to work.
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Remember, the nub of any supervised learning algorithm is that **we need to be able to match predictions to their ground truths**. This is tricky since object detection is more open-ended than the average learning task.
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For the model to learn _anything_, we'd need to structure the problem in a way that allows for comparisions between our predictions and the objects actually present in the image.
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For the model to learn _anything_, we'd need to structure the problem in a way that allows for comparisons between our predictions and the objects actually present in the image.
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Priors enable us to do exactly this!
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#### Download
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Specfically, you will need to download the following VOC datasets –
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Specifically, you will need to download the following VOC datasets –
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