In this post, we'll see how to create a Beagle Detector using Faster-RCNN. Faster-RCNN is the state-of-the-art object detection model in terms of detection accuracy.

This time, we are using PyTorch to train a custom Mask-RCNN. And we are using a different dataset which has mask images (.png files) as . So, we can practice our skills in dealing with different data types. Without any futher ado, let's get into it.

In this post, we will explore Mask-RCNN object detector with Pytorch. We will use the pretrained Mask-RCNN model with Resnet50 as the backbone.

In this post, we will use Pytorch to train a NLP Sincereness Detector which will detect whether a question is asked sincerely or not.

(source: https://commons.wikimedia.org/wiki/File:Pytorch_logo.png)

In this post, we will explore Faster-RCNN object detector with Pytorch. We will use the pretrained Faster-RCNN model with Resnet50 as the backbone.