R-CNN stands for Region-based Convolutional Neural Network. Region-based within R-CNN stands for the region proposals. Region proposals are used to identify objects within an image. Note that R-CNN assists in identifying both the objects present in the image and the location of objects within the image.
In the following sections, we will learn about the working details of R-CNN before training it on our custom dataset.
Working details of R-CNN
Let's get an idea of R-CNN-based object detection at a high level using the following diagram:
Image source: https://arxiv.org/pdf/1311.2524.pdf
We perform the following steps when leveraging the R-CNN technique for object detection:
- Extract region proposals from an image:
- Ensure that we extract a high number of proposals to not miss out on any potential object within the image.
- Resize (warp) all the extracted regions to get images of the same size.
- Pass the resized region proposals through...
