Segment Anything - Model explanation with code

Umar Jamil · Beginner ·👁️ Computer Vision ·2y ago

Skills: Modern CV Models61%

About this lesson

Full explanation of the Segment Anything Model from Meta, along with its code. As always the slides are freely available: https://github.com/hkproj/segment-anything-slides Chapters 00:00 - Introduction 01:20 - Image Segmentation 03:28 - Segment Anything 06:58 - Task 08:20 - Model (Overview) 09:51 - Image Encoder 10:07 - Vision Transformer 12:30 - Masked Autoencoder Vision Transformer 15:32 - Prompt Encoder 21:15 - Positional Encodings 24:52 - Mask Decoder 35:43 - Intersection Over Union 37:08 - Loss Functions 39:10 - Data Engine and Dataset 41:35 - Non Maximal Suppression

Original Description

Full explanation of the Segment Anything Model from Meta, along with its code. As always the slides are freely available: https://github.com/hkproj/segment-anything-slides Chapters 00:00 - Introduction 01:20 - Image Segmentation 03:28 - Segment Anything 06:58 - Task 08:20 - Model (Overview) 09:51 - Image Encoder 10:07 - Vision Transformer 12:30 - Masked Autoencoder Vision Transformer 15:32 - Prompt Encoder 21:15 - Positional Encodings 24:52 - Mask Decoder 35:43 - Intersection Over Union 37:08 - Loss Functions 39:10 - Data Engine and Dataset 41:35 - Non Maximal Suppression

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Chapters (15)

Introduction

1:20 Image Segmentation

3:28 Segment Anything

6:58 Task

8:20 Model (Overview)

9:51 Image Encoder

10:07 Vision Transformer

12:30 Masked Autoencoder Vision Transformer

15:32 Prompt Encoder

21:15 Positional Encodings

24:52 Mask Decoder

35:43 Intersection Over Union

37:08 Loss Functions

39:10 Data Engine and Dataset

41:35 Non Maximal Suppression

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