Object Detection Using Mask R-CNN with TensorFlow

Mask R-CNN is an object detection model based on deep convolutional neural networks (CNN) developed by a group of Facebook AI researchers in 2017. The model can return both the bounding box and a mask for each detected object in an image. The model was originally developed in Python using the Caffe2 deep learning library. The original source code is available on GitHub. To support the Mask R-CNN model in more libraries that are currently more popular, such as TensorFlow, there is a popular popular open-source project called that offers an implementation based on Keras and TensorFlow 1.3. Google officially released TensorFlow 2.0 in September 2020. TensorFlow 2.0 is better organized and much easier to learn compared to TensorFlow 1.0.