Akhil Iyer
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Revised README
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# ShortScribe Pipeline
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This repository provides code for the paper [Making Short-Form Videos Accessible With Hierarchical Video Summaries](https://arxiv.org/abs/2402.10382). In this repository, we introduce the pipeline for ShortScribe, a tool that makes short-form videos accessible to blind and low-vision users by generating summaries at varying levels of depth. This source code specifically provides an API for generating the summaries. To see the source code for ShortScribe's interface, see this GitHub repository [here](https://github.com/
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# Installing ShortScribe
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Before building the environment to run the ShortScribe pipeline, ensure that you have enough resources and credentials. You will need Google Cloud service account credentials in the form of a JSON file and an OpenAI API Key. We deployed our system on an NVIDIA A100 GPU with about 50 GB memory using PyTorch 2.0.1+cu118.
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To get a local copy of the pipeline, run ```git lfs install``` and then ```git clone [email protected]:spaces/akhil03/ShortScribe-Pipeline```
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# ShortScribe Pipeline
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This repository provides code for the paper [Making Short-Form Videos Accessible With Hierarchical Video Summaries](https://arxiv.org/abs/2402.10382). In this repository, we introduce the pipeline for ShortScribe, a tool that makes short-form videos accessible to blind and low-vision users by generating summaries at varying levels of depth. This source code specifically provides an API for generating the summaries. To see the source code for ShortScribe's interface, see this GitHub repository [here](https://github.com/Akl35/shortscribe)
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# Installing ShortScribe
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IMPORTANT NOTE: This repository is using the `gpt-4` model because it was built before the release of `gpt-4-turbo` and `gpt-4o`
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Before building the environment to run the ShortScribe pipeline, ensure that you have enough resources and credentials. You will need Google Cloud service account credentials in the form of a JSON file and an OpenAI API Key. We deployed our system on an NVIDIA A100 GPU with about 50 GB memory using PyTorch 2.0.1+cu118.
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To get a local copy of the pipeline, run ```git lfs install``` and then ```git clone [email protected]:spaces/akhil03/ShortScribe-Pipeline```
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