deploying_aipys

Deploying AIPyS for Integration with Nikon-nis Elements

Leverage the AIPyS platform for efficient image processing, segmentation, analysis, and deployment file generation compatible with the Nikon-nis elements jobs module. Utilize the following command-line interface (CLI) instructions for a comprehensive workflow:

Initial Image Selection and Parameter Adjustment

Image Selection and Path Configuration:

updateParameters --Image_name "\dest\20X\WT\3_XY01.tif"

Diameter Measurement via measDia (Web Application):

In this step, use the web application to measure the diameter across several sample cells. This helps establish analysis parameters:
```
aipys --option measDia
```
Update Estimated Cell Diameter:

Assuming a standard object diameter of 60 for a 20x objective:
```
updateParameters --diameter 60
```

Segmented Image Video Production

Configure Video Generation Parameters:

Specify the details for video creation including, image count, video name, and related configurations:

updateParameters --videoName "ImageSeqcp.avi" --data_dir "\dest\20X\PHENO" --imagesN 5 --outPath "\dest\AIPyS_output_images" --model_type cyto --channels greyscale

Generate the Segmented Image Sequence with Cellpose:
```
aipys --option cp_seg_video
```

Granularity Analysis

Define Granularity Analysis Parameters:

updateParameters --videoName "GranMeasVideo_cp.avi" --start_kernel 2 --end_karnel 50 --kernel_size 20 --extract_pixel 50 --resize_pixel 150 --outputImageSize 500

Produce Granularity Images:
```
aipys --option cp_gran_video
```

Data Labeling and Visualization

Save Single Cell Images & Compile an Intensity Table:

Specify the desired kernel size and set the base directory for gathering training data:
```
updateParameters --kernelGran 6 --trainingDataPath "\dest\20X" --imagesN 5
```
```
aipys --option cp_gran_table_gen
```
Binary Labeling via dataLabeling (Web Application):

With this tool, users can perform binary phenotype labeling for the training dataset, improving the model’s accuracy:
```
updateParameters --imagePath "\dest\AIPyS_output_images\imageSequence\images" --dataPath "\dest\AIPyS_output_images\imageSequence\data"
```
```
aipys --option dataLabeling
```

Analyze Image Distribution with data_viz (Web Application):

Engage in data visualization to scrutinize image distribution and evaluate analytical results:

updateParameters --imagePath "\dest\AIPyS_output_images\table_example\images" --dataPath "\dest\AIPyS_output_images\table_example"

aipys --option data_viz

Model Construction and Deployment File Preparation

Build the Deployment Model:

Establish criteria for data training and model development:

updateParameters --dataPath "\dest\AIPyS_output_images\table_example" --outPath "\dest\AIPyS_output_images" --imW 10 --imH 10 --thold 0.7 --areaSel 1000 --fractionData 50

aipys --option modelBuild

Generate Deployment Build File:

After the model is finalized, ready the deployment file for integration with Nikon-nis elements:

updateParameters --Image_name "\dest\022224\2.tif" --outPath "\dest\AIPyS_output_images\outproc_temp"

aipys --option deployBuild

Parameter Management

For adjustments or resets of parameters at any phase:

For Help: load-parameters --help
To Generate Default Parameters: load-parameters --select generate
To Reset Parameters: load-parameters --select reset
To Display Current Settings: load-parameters --select display

Ensure to align paths to your directory configurations. The full suite of CLI instructions provides a detailed process from initiating the AIPyS project to model readiness and subsequent deployment, with enhanced focus on web application functions for user engagement and analytic insights.