# FluoSA (Fluorescence Signal Analyzer)
<p> </p>
FluoSA inputs *.LIF and *.tif files, detects user-defined neural structures, and quantifies the fluorescence signal changes (frame-wise fluorescence intensity and the dF/F0) in these structures.
<p> </p>
The outputs of FluoSA include:
1. An annotated video showing the detected neural structures:
2. Spreadsheets storing frame-wise fluorescence intensity in each detected neural structure:
3. Spreadsheets storing summary of fluorescence signal changes (dF/F0) in each detected neural structure:
<p> </p>
## Installation
### 1 Install FluoSA
```
python3 -m pip install FluoSA
```
### 2 Install CUDA toolkit v11.8
https://developer.nvidia.com/cuda-11-8-0-download-archive?target_os=Windows&target_arch=x86_64
### 3 Install Detectron2
```
python3 -m pip install 'git+https://github.com/facebookresearch/detectron2.git'
```
### 4 Install PyTorch 2.0.1
#### 4.1 For Windows and Linux
##### 4.1.1 If using GPU
```
python3 -m pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118
```
##### 4.1.2 CPU only
```
python3 -m pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cpu
```
#### 4.2 For Mac
```
python3 -m pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2
```
<p> </p>
## Usage
In your terminal / command prompt, type:
```
FluoSA
```
Then the user interface will be initiated:
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"description": "# FluoSA (Fluorescence Signal Analyzer)\n\n<p> </p>\n\nFluoSA inputs *.LIF and *.tif files, detects user-defined neural structures, and quantifies the fluorescence signal changes (frame-wise fluorescence intensity and the dF/F0) in these structures.\n\n<p> </p>\n\nThe outputs of FluoSA include:\n\n1. An annotated video showing the detected neural structures:\n\n  \n\n2. Spreadsheets storing frame-wise fluorescence intensity in each detected neural structure:\n\n \n\n3. Spreadsheets storing summary of fluorescence signal changes (dF/F0) in each detected neural structure:\n\n \n\n<p> </p>\n\n## Installation\n### 1 Install FluoSA\n```\npython3 -m pip install FluoSA\n```\n\n### 2 Install CUDA toolkit v11.8\nhttps://developer.nvidia.com/cuda-11-8-0-download-archive?target_os=Windows&target_arch=x86_64\n\n### 3 Install Detectron2\n```\npython3 -m pip install 'git+https://github.com/facebookresearch/detectron2.git'\n```\n\n### 4 Install PyTorch 2.0.1\n#### 4.1 For Windows and Linux\n##### 4.1.1 If using GPU\n```\npython3 -m pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118\n```\n##### 4.1.2 CPU only\n```\npython3 -m pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cpu\n```\n#### 4.2 For Mac\n```\npython3 -m pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2\n```\n\n<p> </p>\n\n## Usage\nIn your terminal / command prompt, type:\n```\nFluoSA\n```\n\nThen the user interface will be initiated:\n\n \n\n",
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