This page presents the final visualization outputs from the Astro Cultivators project, including the RealSense stress detection dashboard and the hyperspectral vegetation index tracker.
The output system was designed to make the project easier to understand visually. Instead of only showing raw data or CSV files, the dashboards connect images, extracted features, spectral trends, and model results in interactive views.
Shows daily stress detection outputs using RGB frames, segmentation overlays, confidence values, VARI trends, and canopy area trends.
Shows VOG1 and NDVI temporal trends from the Cubert hyperspectral workflow.
Combines image outputs, feature summaries, trend charts, and model ready information for project presentation and future digital twin use.
This dashboard is the main visualization output from the RealSense workflow. It shows the original RGB image, segmentation overlay, daily plant metrics, model confidence, VARI trend, and canopy area trend.
The dashboard brings together image outputs, segmentation results, feature changes, and stress classification into one interactive monitoring view.
This dashboard visualizes Lia’s hyperspectral temporal outputs using VOG1 and NDVI. It summarizes the latest values, index ranges, and daily trends from Set 2 Cubert hyperspectral data.
The tracker shows how VOG1 and NDVI changed across the selected experiment dates using an interactive dashboard style layout.
The workflows produced visual and structured outputs that can be used for reporting, dashboard display, and future digital twin integration.
These outputs help turn raw RealSense and hyperspectral data into interpretable visual information for soybean growth monitoring and drought stress detection.
Visualization makes the pipeline easier to explain because it connects raw plant images, segmentation results, extracted features, hyperspectral trends, and model predictions. This helps users see both the final outputs and the visual evidence behind them.
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