Promptless Task-Specific Finetuning of MetaAI Segment-Anything

# Task:

**Finetune SAM model on Custom dataset to segment objects without prompts (during training and inference)**

# Approach:

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https://preview.redd.it/8h0xgyk500bc1.png?width=1333&format=png&auto=webp&s=839212aaf8ab209ea0e4eadebaec9d3467c4df4c

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>Note: The post is created using my Kaggle notebook -- [https://www.kaggle.com/code/yogendrayatnalkar/promptless-taskspecific-finetuning-of-metaai-sam](https://www.kaggle.com/code/yogendrayatnalkar/promptless-taskspecific-finetuning-of-metaai-sam)

## How does SAM work (high-level):

* Sam Encoder --> **ViT + Neck-Module** (Consisting of 2 Conv2D layers used for downsampling the channels of the ViT output)
* The Encoder ViT has a patch-size of **16x16**.
* Input: **1024x1024x3**
* With the above patch-size and input-image-size, the …

computervision dataset downsampling encoder finetuning inference objects prompts sam segment training vit work