Quick Start Guide

This guide will help you get started with VISTA quickly.

VISTA demo

Click to watch a demo of VISTA on YouTube

Launching VISTA

After installation, you can launch VISTA in several ways:

From the command line:

vista

As a Python module:

python -m vista

From Python code:

from vista.__main__ import main
main()

Loading Imagery

VISTA supports various imagery formats. To load imagery:

  1. File Menu: Click File > Open and select your imagery file

  2. Drag and Drop: Drag imagery files directly into the VISTA window

  3. Programmatically: Use the VISTA API to load imagery

Supported Formats

VISTA loads imagery from HDF5 files (.h5, .hdf5). See the HDF5 format overview for details.

Basic Workflow

A typical VISTA workflow consists of:

  1. Load Imagery

    Load your multi-frame imagery dataset into VISTA.

  2. Apply Treatments

    Apply radiometric corrections such as bias removal or non-uniformity correction.

  3. Detect Objects

    Run detection algorithms (e.g., CFAR, threshold-based) to identify objects of interest.

  4. Track Objects

    Apply tracking algorithms to create tracks from detections across frames.

  5. Analyze Results

    Review tracks, extract features, and export results for further analysis.

Using the GUI

Main Interface Components

  • Imagery Viewer: Central display area showing the current frame

  • Playback Controls: Navigate through frames and control playback

  • Data Panels: Manage imagery, detections, tracks, and other data

  • Menu Bar: Access file operations, algorithms, and settings

  • Status Bar: Shows current frame, coordinates, and pixel values

Running Algorithms

  1. Select Algorithms from the menu bar

  2. Choose an algorithm category (Detection, Tracking, Enhancement, etc.)

  3. Configure algorithm parameters in the dialog

  4. Click Run to execute the algorithm

  5. Results will appear in the appropriate data panel

Keyboard Shortcuts

Common keyboard shortcuts:

  • Space: Play/Pause playback

  • Left/Right Arrow or A/D: Previous/Next frame

Example: Using the API - Detection Workflow

Here’s a simple example workflow using the VISTA API:

from vista.imagery import Imagery
from vista.algorithms.detectors.threshold import simple_threshold_detector
from vista.algorithms.trackers.simple_tracker import SimpleTracker

# Load imagery
imagery = Imagery.from_file('path/to/imagery.h5')

# Apply detection
detections = simple_threshold_detector(
    imagery.data,
    threshold=10.0
)

# Track detections
tracker = SimpleTracker(max_distance=5.0)
tracks = tracker.track(detections)

# Analyze results
print(f"Found {len(tracks)} tracks")
for track in tracks:
    print(f"Track {track.id}: {len(track)} detections")

Next Steps