Build a convolutional neural net for image similarity -- 2
£1300 GBP
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Publicado hace más de 6 años
£1300 GBP
Pagado a la entrega
Build two statistical models:
Model 1) Input: one query image, a dataset of product images; Output: visually similar images from product image dataset matching query image, together with a similarity score for each
Model 2) Input: one set of images; Output: a clustering of the input images
Idea: since Model 1 can compute image similarity between images, Model 2 can simply run Model 1 on all pairs of images to get similarities, then use a standard clustering algorithm based on the similarity matrix. Model 2: Given a function model1(X) -> {a:0.9, b:0.7, c:0.6, d:0.4}, Gabi will build model 2.
Accuracy / Precision / Recall will be computed on the top 10 results, and we desire 80% accuracy on those.
Datasets to be provided:
Dataset 1: Lifesytle images - aprox 4.5k images of fashion related lifestyle images. Provided in a zip folder with just the individual images.
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Dataset 2: Products: aprox 50k product file with, ID, Name, Description, Main Image URL and Alternative Image URL.
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Dataset 3: Visenze results for all images and associated product results with their similarity score.
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