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doc: update README.md

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- title: SamGIS - LISA on CUDA
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  emoji: 🗺️
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  [LISA](https://github.com/dvlab-research/LISA) (Reasoning Segmentation via Large Language Model) applied to geospatial data thanks to [SamGIS](https://github.com/trincadev/samgis-be).
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- About SamGIS - LISA on ZeroGPU see the [samgis-lisa-on-zero demo](https://huggingface.co/spaces/aletrn/samgis-lisa-on-zero).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  To change the base relative url for custom frontend add the VITE_PREFIX environment variable, e.g.:
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  VITE_PREFIX="/custom-url"
 
 
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+ title: SamGIS - LISA on ZeroGPU
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  emoji: 🗺️
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  colorFrom: red
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  colorTo: blue
 
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  [LISA](https://github.com/dvlab-research/LISA) (Reasoning Segmentation via Large Language Model) applied to geospatial data thanks to [SamGIS](https://github.com/trincadev/samgis-be).
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+ I also adapted LISA to HuggingFace [lisa-on-cuda](https://huggingface.co/spaces/aletrn/lisa-on-cuda) ZeroGPU space.
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+ ##  Custom environment variables for HuggingFace ZeroGPU Space
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+ Fundamental environment variables you need are:
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+ ```bash
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+ XDG_CACHE_HOME="/data/.cache"
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+ PROJECT_ROOT_FOLDER="/home/user/app"
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+ WORKDIR="/home/user/app"
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+ ```
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+ Derived ones:
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+ ```bash
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+ MPLCONFIGDIR="/data/.cache/matplotlib"
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+ TRANSFORMERS_CACHE="/data/.cache/transformers"
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+ PYTORCH_KERNEL_CACHE_PATH="/data/.cache/torch/kernels"
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+ FASTAPI_STATIC="/home/user/app/static"
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+ VIS_OUTPUT="/home/user/app/vis_output"
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+ MODEL_FOLDER="/home/user/app/machine_learning_models"
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+ FOLDERS_MAP='{"WORKDIR":"/home/user/app","XDG_CACHE_HOME":"/data/.cache","PROJECT_ROOT_FOLDER":"/home/user/app","MPLCONFIGDIR":"/data/.cache/matplotlib","TRANSFORMERS_CACHE":"/data/.cache/transformers","PYTORCH_KERNEL_CACHE_PATH":"/data/.cache/torch/kernels","FASTAPI_STATIC":"/home/user/app/static","VIS_OUTPUT":"/home/user/app/vis_output"}'
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+ ```
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+ The function `build_frontend()` from lisa_on_cuda package create all the folders required for this project using the environment variable `FOLDERS_MAP`. That's useful for cache folders (XDG_CACHE_HOME, MPLCONFIGDIR, TRANSFORMERS_CACHE, PYTORCH_KERNEL_CACHE_PATH) because missing these can slow down the inference process. Also you could keep these folders in a permanent storage disk mounted on a custom path.
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  To change the base relative url for custom frontend add the VITE_PREFIX environment variable, e.g.:
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+ ```bash
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  VITE_PREFIX="/custom-url"
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+ ```