Tensorflow 1.5 Object Detection :: TFRecord

Faster R-CNN

Faster R-CNN is a state of the art object detection framework. It has been around for a while and has a lot of nice integrations.

Faster R-CNN, despite its name, is known as being a slower model than some other choices (like YOLOv3 or MobileNet) for inference but slightly more accurate.

Faster R-CNN is a two-stage deep learning object detector: first it identifies regions of interest, and then passes these regions to a convolutional neural network. The outputted features maps are passed to a support vector machine (SVM) for classification. Regression between predicted bounding boxes and ground truth bounding boxes are computed.

Faster R-CNN is one of the many model architectures that the TensorFlow Object Detection API provides by default, including with pre-trained weights.

This implementation links in with Tensorboard.