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doc/faq.md

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### 1. How to install `micro_sam`?
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The [installation](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html#installation) for `micro_sam` is supported in three ways: [from conda](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html#from-conda) (recommended), [from source](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html#from-source) and [from installers](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html#from-installer). Check out our [tutorial video](https://youtu.be/gcv0fa84mCc) to get started with `micro_sam`, briefly walking you through the installation process and how to start the tool.
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The [installation](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html#installation) for `micro_sam` is supported in four ways: [from pip](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html#from-pip), [from conda](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html#from-conda), [from source](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html#from-source), and [from installers](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html#from-installer).
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We recommend installation from pip or conda for most users.
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Check out our [tutorial video](https://youtu.be/gcv0fa84mCc) to get started with `micro_sam`, briefly walking you through the installation process and how to start the tool.
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### 2. I cannot install `micro_sam` using the installer, I am getting some errors.
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The installer should work out-of-the-box on Windows and Linux platforms. Please open an issue to report the error you encounter.
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>NOTE: The installers enable using `micro_sam` without conda. However, we recommend the installation from conda or from source to use all its features seamlessly. Specifically, the installers currently only support the CPU and won't enable you to use the GPU (if you have one).
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>NOTE: The installers enable using `micro_sam` without conda. However, we recommend the installation from pip, from conda, or from source to use all its features seamlessly. Specifically, the installers are out-of-date and currently only support the CPU and won't enable you to use the GPU (if you have one).
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### 3. What is the minimum system requirement for `micro_sam`?
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With the latest release 1.0.0, the installation from conda and source should take care of this and install all the relevant packages for you.
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So please reinstall `micro_sam`, following [the installation guide](#installation).
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### 6. Can I install `micro_sam` using pip?
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We do *not* recommend installing `micro-sam` with pip. It has several dependencies that are only avaoiable from conda-forge, which will not install correctly via pip.
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Please see [the installation guide](#installation) for the recommended way to install `micro-sam`.
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Yes! We recently made available `micro_sam` with pip. Check out [the installation guide](https://computational-cell-analytics.github.io/micro-sam/micro_sam.html#from-pip) for details.
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The PyPI page for `micro-sam` exists only so that the [napari-hub](https://www.napari-hub.org/) can find it.
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### 7. I get the following error: `importError: cannot import name 'UNETR' from 'torch_em.model'`.
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It's possible that you have an older version of `torch-em` installed. Similar errors could often be raised from other libraries, the reasons being: a) Outdated packages installed, or b) Some non-existent module being called. If the source of such error is from `micro_sam`, then `a)` is most likely the reason . We recommend installing the latest version following the [installation instructions](https://github.com/constantinpape/torch-em?tab=readme-ov-file#installation).
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### 8. My system does not support internet connection. Where should I put the model checkpoints for the `micro-sam` models?
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### 8. My system does not have a internet connection. Where should I put the model checkpoints for the `micro-sam` models?
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We recommend transferring the model checkpoints to the system-level cache directory (you can find yours by running the following in terminal: `python -c "from micro_sam import util; print(util.microsam_cachedir())`). Once you have identified the cache directory, you need to create an additional `models` directory inside the `micro-sam` cache directory (if not present already) and move the model checkpoints there. At last, you **must** rename the transferred checkpoints as per the respective [key values](https://github.com/computational-cell-analytics/micro-sam/blob/main/micro_sam/util.py#L87) in the url dictionaries located in the `micro_sam.util.models` function (below mentioned is an example for Linux users).
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```bash

doc/installation.md

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# Installation
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There are three ways to install `micro_sam`:
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- [From conda](#from-conda) is the recommended way if you want to use all functionality.
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There are four ways to install `micro_sam`:
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- [From pip](#from-pip) to use all functionality and install via pip.
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- [From conda](#from-conda) to use all functionality and install in an encapsulated environment.
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- [From source](#from-source) for setting up a development environment to use the latest version and to change and contribute to our software.
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- [From installer](#from-installer) to install it without having to use conda (supported platforms: Windows and Linux, supports only CPU).
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- [From installer](#from-installer) to install it without having to use pip or conda (supported platforms: Windows and Linux, supports only CPU, deprecated).
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You can find more information on the installation and how to troubleshoot it in [the FAQ section](#installation-questions).
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We do **not support** installing `micro_sam` with pip.
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## From pip
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`pip` is the default python package manager. You can install `micro_sam` via pip with the command:
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```bash
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pip install micro_sam
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```
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Note: when using pip you have to manage your python environments yourself. For example, you could create a conda environment and install `micro_sam` via pip in there, or use `venv` for this.
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To use the `vit_t` (MobileSAM) model, you have to additionally install [MobileSAM](https://github.com/ChaoningZhang/MobileSAM) in the environment where `micro_sam` was installed via pip. It is not available on PyPI, so it has to be installed from GitHub:
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```bash
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pip install git+https://github.com/ChaoningZhang/MobileSAM.git
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```
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## From conda
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pip install -e .
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```
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## Trackastra installation
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To use [automatic tracking](#annotator-tracking), you have to install [trackastra](https://github.com/weigertlab/trackastra) in the conda environment where `micro_sam` is installed.
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You can install it with pip:
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```bash
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conda activate sam
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pip install trackastra
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```
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## MobileSAM installation
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To use the `vit_t` (MobileSAM) model, you have to install [MobileSAM](https://github.com/ChaoningZhang/MobileSAM) in the environment where `micro_sam` is installed.
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It is not available on PyPI, so it has to be installed from GitHub with pip:
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```bash
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conda activate sam
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pip install git+https://github.com/ChaoningZhang/MobileSAM.git
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```
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## From installer
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**Note: The installers are not yet up-to-date with the latest version of micro-sam (v1.4.0 onwards). We will update them in the next few weeks.**
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**Note: The installers are not yet up-to-date with the latest version of micro-sam (v1.4.0 onwards). We recommend installing micro-sam via pip or conda instead.**
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We also provide installers for Linux and Windows:
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- [Linux](https://owncloud.gwdg.de/index.php/s/Fyf57WZuiX1NyXs)
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- [Mac](https://owncloud.gwdg.de/index.php/s/7YupGgACw9SHy2P)
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-->
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The installers will not enable you to use a GPU, so if you have one then please consider installing `micro_sam` via [conda](#from-conda) instead. They will also not enable using the python library.
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The installers will not enable you to use a GPU, so if you have one then please consider installing `micro_sam` via [pip](#from-pip) or [conda](#from-conda) instead.
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### Linux Installer:
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micro_sam/__version__.py

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__version__ = "1.7.7"
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__version__ = "1.8.0"

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