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Merge pull request #6 from arrmunoz/patch-2
Update README.md
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README.md

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@@ -22,25 +22,31 @@ Before you can annotate images using SAMJ-IJ, you need to install the plugin in
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1. **Install Fiji**: If you haven't already, download and install [Fiji](https://fiji.sc/).
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> [!IMPORTANT]
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> For MacOS users, if your Fiji instance is launched from the Downloads folder, SAMJ will not work! Move Fiji to another folder, Documents or Desktop for example.
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> For MacOS users, if your Fiji instance is launched from the Downloads folder, SAMJ will not work! Move Fiji to another folder, Documents or Desktop, for example.
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2. **Install SAMJ Plugin**: Open Fiji and navigate to `Help > Update...`. In the `Manage update sites` window, and look for an update site named `SAMJ`, select it, click on `Apply and close` and then `Apply changes`. Finally restart Fiji.
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If you cannot find `SAMJ` among the update sites list click on `Add update site`/`Add unlisted site`, write `SAMJ` in the `Name` field and `https://sites.imagej.net/SAMJ/` in the `URL` field. Click on `Apply and close`, click on `Apply changes` and restart Fiji.
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If you cannot find `SAMJ` among the update sites list, click on `Add update site`/`Add unlisted site`, write `SAMJ` in the `Name` field and `https://sites.imagej.net/SAMJ/` in the `URL` field. Click on `Apply and close`, click on `Apply changes` and restart Fiji.
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![SAMJ Update site](./images/update-site-example.png)
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5. **Open SAMJ-IJ Annotator**: Start Fiji and navigate to `Plugins > SAMJ > SAMJ Annotator` to open the plugin.
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## Model Installation
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To use the SAMJ-IJ plugin, you must install a SAM model. These are the models available for installation:
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* **EfficientSAM:** This is a base model designed for segmentation tasks, optimized for efficiency and performance on standard computational resources. It is ideal for quick, accurate segmentation in real-time applications.
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* **EfficientViTSAM-l0:** This is a lightweight variant of the EfficientViTSAM model. It offers a balance between segmentation accuracy and computational demand and is suitable for use on regular computers.
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* **EfficientViTSAM-l1:** This is an intermediate version that provides enhanced accuracy for complex segmentation tasks with manageable resource requirements.
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* **EfficientViTSAM-l2:** This is a more advanced version designed for high-accuracy segmentation in demanding scenarios that require higher computational resources.
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* **EfficientViTSAM-xl0:** This is an extra-large model variant that pushes the boundaries of segmentation accuracy at the expense of increased computational demand.
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* **EfficientSAM:** A base model designed for segmentation tasks, optimized for efficiency and performance on standard computational resources. Ideal for quick, accurate segmentation in real-time applications.
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* **EfficientViTSAM-l0:** A lightweight variant of the ]EfficientViTSAM](https://arxiv.org/abs/2402.05008) model, offering a balance between segmentation accuracy and computational demand, suitable for use on normal computers.
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* **EfficientViTSAM-l0:** A lightweight variant of the ]EfficientViTSAM](https://arxiv.org/abs/2402.05008) model, offering a balance between segmentation accuracy and computational demand, suitable for use on regular computers.
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* **EfficientViTSAM-l1:** An intermediate version, providing enhanced accuracy for complex segmentation tasks with manageable resource requirements.
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* **EfficientViTSAM-l2:** A more advanced version, designed for high-accuracy segmentation in demanding scenarios, requiring higher computational resources.
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* **EfficientViTSAM-xl0:** An extra-large model variant, pushing the boundaries of segmentation accuracy at the expense of increased computational demand.
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* **EfficientViTSAM-xl1:** The most advanced and resource-intensive version, offering state-of-the-art segmentation performance for the most challenging tasks.
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> [!WARNING]
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> Low end computers are advised not to use the **EfficientSAM** model as it might take up to 10 minutes to load the first time, or even freeze the computer. The fastest and lightest model is **EfficientViTSAM-l0** but low resources machines might take up to 2-3 minutes to load the first time. Subsequent loading times will be much faster (~10s).
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> Users with a low-end computer are advised not to use the **EfficientSAM** model as it might take up to 10 minutes to load the first time, or the computer can even be frozen. The fastest and lightest model is **EfficientViTSAM-l0**, but low-resource machines might take up to 2-3 minutes to load the first time. Subsequent loading times will be much faster (~10s).
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These are the steps to install a model:
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1. Open the SAMJ Annotator plugin as described above.

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