Also the TF Object Detection API has a suite of pretrained SOTA object detection models https://github.com/tensorflow/models/tree/master/research/ob...
What makes object detection really valuable is being able to finetune a model to detect objects that are relevant to your problem. However collecting, labeling, takes a lot of time since the best way is to manually label. But 30-50 hrs of manual labeling can get you some great results when you are leveraging pretrained models. Building a tool to manage data labeling and training for finetuning object detection models would be very valuable.