Single Label Regression(Finetuning) With Input Artificial Features In Caffe
<p>I have,say, <code>n</code> images and for each of them I have additional 2 artificial(made-up) features, and image-labels are single dimensional integers. </p>

<p>I want to fine-tune Image-net on my dataset, but I do not know how to handle these 2 additional features as input, how should I feed the data to caffe? Please help!</p>

<p>EDIT: The 2 features can be any 2 numbers (1 dimensional) say two numbers representing what class an image falls into, and how many images fall into that class.</p>

<p>Say, I have 'cat.jpg', then the features are say, 5 and 2000, where 5 is the feature 1 representing the class and 2000 is the total images in that class. 
In short, the 2 features can be any two integers.</p>