问题
I'm categorizing 30 types of clothes from the image using R-CNN Object Detection Library from tensorflow : https://github.com/tensorflow/models/tree/master/research/object_detection
Does color matter when we collect images for training and testing?
If I put only purple and blue shirts, I guess it won't recognize red shirts?
Should I gray scale all images to detect the types of clothes? :)
回答1:
Yes, colour does matter. The underlying visual feature extraction is based on a convolutional neural network, pre-trained to perform image recognition on colour images in the ImageNet dataset.
The R-CNN repository instructions on bringing in your own dataset asks for RGB images.
Dataset Requirements
For every example in your dataset, you should have the following information:
- An RGB image for the dataset encoded as jpeg or png.
- A list of bounding boxes for the image. Each bounding box should contain:
- A bounding box coordinates (with origin in top left corner) defined by 4 floating point numbers [ymin, xmin, ymax, xmax]. Note that we store the normalized coordinates (x / width, y / height) in the TFRecord dataset.
- The class of the object in the bounding box.
来源：https://stackoverflow.com/questions/46762421/should-i-gray-scale-the-image