Faster RCNN PyTorch Code Walkthrough | Fine-Tuning and Custom Dataset Training скачать в хорошем качестве

Faster RCNN PyTorch Code Walkthrough | Fine-Tuning and Custom Dataset Training

This tutorial covers all the details of Faster R-CNN with an in-depth PyTorch code walkthrough! This will guide you through the implementation of Faster R-CNN in PyTorch, including training on custom datasets and fine-tuning faster r cnn techniques. We first do a walkthrough of Faster RCNN with resnet50 FPN backbone wherein we cover the backbone initialization part, RPN, ROI head and also dive deep into all transformations happening inside torchvision’s Faster RCNN class. We then get into how to use this pytorch code to train an Object Detection model with Faster R-CNN on our own dataset . For that we talk about Faster-RCNN fine tuning with PyTorch, using pre-trained model with resnet 50 fpn backbone on our dataset. We also look at how to create our own version of faster r cnn by initializing different components and having PyTorch's Faster RCNN class, plug those components together and give us a model, which we can train from scratch on our dataset. ⏱️ Timestamps 00:00 Intro 00:45 Resnet50 FPN Overview 04:32 Faster RCNN Module Intro 05:02 Faster R-CNN PyTorch Class Walkthrough 06:47 GeneralizedRCNN Class 07:53 Input Transformations for Faster RCNN 12:39 Backbone Call 14:05 RPN Module 18:22 AnchorGenerator 25:42 Anchors to Proposal Transformation 27:39 Proposal Filtering in Region Proposal Network 31:15 Target and Loss Computation in RPN 35:08 ROI Head module in PyTorch Faster R-CNN 36:06 Sampling Proposals and Target Computation in ROI Head 41:32 MultiScale ROI Align in PyTorch Faster R CNN 48:58 Prediction FC Layers for ROI Head 49:47 Loss Computation for ROI Head 51:05 Transforming Proposal to Predictions and Filtering 56:22 Prediction Boxes Transformations for Faster RCNN 57:22 Fine-Tuning and Custom Dataset Training 01:02:20 Results 01:02:40 Outro 📖 Resources Faster R-CNN Paper - https://tinyurl.com/exai-faster-rcnn-... Implementation - https://github.com/explainingai-code/... 🔔 Subscribe : https://tinyurl.com/exai-channel-link Background Track - Fruits of Life by Jimena Contreras Email - explainingai.official@gmail.com