A newer version of the Gradio SDK is available:
4.39.0
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.