A high-precision coordinate transformation tool for microscopy researchers. LabCoordinator bridges the gap between disparate analytical instruments (e.g., Optical Microscope → SEM → EPMA) by allowing users to map points of interest on a high-resolution image and dynamically calculate coordinate transformations using a least-squares similarity mathematical model.

Simply open the link below in Chrome or Edge. The app runs entirely in your browser; your lab data never leaves your computer. 👉 https://aggyface.github.io/coordinator/

For lab computers with no internet access:

1. Copy the dist/index.html file to a USB stick.
2. Double-click the file on any computer to open the app instantly.

To update the live website with your latest changes:

1. Build the project:

   npm run build

2. Deploy to GitHub:

   npm run deploy

   The app will be updated at the URL above within a few minutes.

1. Initialize: Click New in the top toolbar. Enter your Project Name and Sample ID.
2. Source Instrument: Define your baseline instrument (e.g., SEM) and its unit system (µm, mm, or Custom).
3. Load Image: Click Open and select your microscopy asset (BMP, TIFF, JPG). A "Loading..." screen will appear while the asset is processed.

4. Place Targets: Switch to Add Point mode. Click features on the image to place markers (yellow ◎).
5. Calibrate Source: Switch to Select mode. Click a marker and enter its verified coordinates for your Source Instrument. Once 3 points have coordinates, they become References (cyan ◆).
6. Verify Baseline: Check the sidebar for the Source Instrument. Since this is the baseline, precision is perfect, and coordinates appear in Cyan.

7. Add Target Instrument: Click + Add in the sidebar. Select your target instrument (e.g., EPMA) and choose the Source Instrument from the "Transform From" dropdown.
8. Enter References: Enter the coordinates for your cyan reference points in the new instrument's coordinate system.
9. Monitor Quality: The sidebar will display the RMSE (Root Mean Square Error). If the value turns RED, check for "Likely X/Y axis swaps" or misplaced points in the alert box.

10. Analyze Targets: Switch to Navigate mode while at the target instrument.
11. Use Proxies: For uncalibrated targets, the app will show grey italic estimated coordinates derived from the transform.
12. Track Progress: Mark features as "Analysed" using the checkbox. A green checkmark (✓) will appear in the main list.

13. Data Export: Click CSV to download a detailed table including a "Reliability" column (Verified vs Transform vs Proxy).
14. Visual Export: Click Image to generate a high-resolution PNG with all markers, labels, legends, and scale bars perfectly overlaid.
15. Save Project: Click Save to bundle everything into a portable .labcoord file.

• Local Server Requirement: Due to browser security policies regarding high-performance APIs (Web Workers and ImageBitmap), image export may fail when running the app directly from the file system (file://). For full functionality, use a local development server (npm run dev) or the hosted web link.
• Passive Listeners: The zoom functionality has been optimized for Chrome by explicitly using non-passive event listeners, ensuring smooth scroll-to-zoom behavior.

• Cyan: Verified Manual entry or Inside the reference hull (Highest Reliability).
• Yellow: Near or just outside the reference hull (Extrapolated).
• Red: Far from references (Unreliable).

The current "Pixel Proxy" logic uses a linear Euclidean distance model. In cases of significant image sheer or non-uniform instrument stage scaling, slight drift may occur. For maximum precision, always ensure your analysis targets are contained inside the cyan dashed boundary (the Convex Hull) of your reference points.