---
title: TSAI S19
emoji: 🏆
colorFrom: yellow
colorTo: blue
sdk: gradio
sdk_version: 3.45.2
app_file: app.py
pinned: false
license: mit
---

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

# The School of AI - ERA(Extensive & Reimagined AI Program) - Assignment 19

This folder consists of Assignment-19 from ERA course offered by - TSAI(The school of AI). 
Follow https://theschoolof.ai/ for more updates on TSAI

Assignment-19
Make a CLIP or FastSAM application on gradio/spaces using open-source models. 
- You may use the open source pre-trained models for CLIP or FastSAM

### Implementation and Results:
Implemented a simple gradio interface on higgingface and Github. Used a pretrained CLIP model from https://github.com/openai/CLIP. Model has been pretrained on Coco Dataset

HF Link: https://huggingface.co/spaces/ToletiSri/TSAI_S19
Github Link: https://github.com/ToletiSri/TSAI_ERA_Assignments/tree/main/S19

Add any image that belongs to one of the 80 Coco datasets, in the input image box
Add some captions for this image. The results(output text box) shown are the likelihood percentage that the image belongs to one of these captions.