Tensorflow 1.5 Object Detection :: TFRecord
What is MobileNetSSDv2?
MobileNetSSDv2 (MobileNet Single Shot Detector) is an object detection model with 267 layers and 15 million parameters. It provides real-time inference under compute constraints in devices like smartphones. Once trained, MobileNetSSDv2 can be stored with 63 MB, making it an ideal model to use on smaller devices.
The MobileNetSSDv2 Model essentially is a 2-part model. The first part consists of the base MobileNetV2 network with a SSD layer that classifies the detected image. In essence, the MobileNet base network acts as a feature extractor for the SSD layer which will then classify the object of interest.
Image in Courtesy of Matthijs Hollemans
MobileNet V2 outperforms MobileNet V1 with higher accuracies and lower latencies.
Image in Courtesy of Google AI
Training a TensorFlow MobileNet Object Detection Model with a Custom Dataset: https://blog.roboflow.ai/training-a-tensorflow-object-detection-model-with-a-custom-dataset/