3/11/2024 0 Comments Fastai multilabel evaluation![]() Is it possible for a Keras deep neural network to return multiple predictions? I don’t want to have to apply them individually in a cascade of if/else code that uses a different network depending on the output of a previous classification. Is there a way to combine the three CNNs into a single network? Or at least train a single network to complete all three classification tasks? I’ve trained three separate CNNs for each of the three categories and they work really well. Texture/appearance: Cotton, wool, silk, tweed, etc.Clothing type: Shirts, dresses, pants, shoes, etc. ![]() The problem is that I need to train a classifier to categorize the items into various classes: shirt, dress, pants, shoes) and my system will return similar items and include links for them to purchase the clothes online. Using my app a user will upload a photo of clothing they like (ex. I’m building an image fashion search engine and need help. Hi Adrian, thanks for the PyImageSearch blog and sharing your knowledge each week. Today’s blog post on multi-label classification with Keras was inspired from an email I received last week from PyImageSearch reader, Switaj. Click here to download the source code to this post
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