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README.md
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---
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title: VLM Demo
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app_file: app.py
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---
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`prismatic-vlms` package (`prisma`) are installed in the current environment.
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These can both be installed from source from the following git repos:
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+ `vlm-bench`: `
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+ `prismatic-vlms`: `https://github.com/TRI-ML/prismatic-vlms`
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## Usage
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The default interaction mode is Chat, which is the main way to use our models. However, we also support a number of other
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interaction modes for more specific use cases:
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+ Captioning: Here,
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is input by the user, it will not be used in producing the caption.
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+ Bounding Box Prediction: After uploading an image, simply specify a portion of the image for which bounding box coordinates are desired
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in the prompt and the selected model will output corresponding coordinates.
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---
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title: VLM Demo
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sdk: gradio
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sdk_version: 3.35.2
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app_file: app.py
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---
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`prismatic-vlms` package (`prisma`) are installed in the current environment.
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These can both be installed from source from the following git repos:
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+ `vlm-bench`: `htts://github.com/TRI-ML/vlm-bench`
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+ `prismatic-vlms`: `https://github.com/TRI-ML/prismatic-vlms`
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## Usage
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The default interaction mode is Chat, which is the main way to use our models. However, we also support a number of other
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interaction modes for more specific use cases:
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+ Captioning: Here,you can simply upload an image with no provided prompt and the selected model will output a caption. Even if a prompt
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is input by the user, it will not be used in producing the caption.
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+ Bounding Box Prediction: After uploading an image, simply specify a portion of the image for which bounding box coordinates are desired
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in the prompt and the selected model will output corresponding coordinates.
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