image-registration

name	image-registration
description	Instructions for estimating translational shift between two images.

You will be shown one image containing a pair of images side by side:

• Left: previous/reference image.
• Right: current image.

The images may have different noise level, sharpness and color scale, but they should contain common structures and features. Use the common structures to estimate the pure translational offset between them. Your offset must mean:

• If the image on the right is shifted by this offset, it aligns with the image on the left.
• Report shift in ij indexing: <shift_y>, <shift_x> (y first, x second).
• Positive y means move the right/current image downward. Positive x means move it rightward.
• If the right/current image appears lower than the left/reference image, shift_y should be negative.
• If the right/current image appears to the right of the left/reference image, shift_x should be negative.
• Report shift values as fractions of image size:
  • shift_y is a fraction of image height.
  • shift_x is a fraction of image width.

Example:

• If the right image should be shifted downward by 30% of image height and left by 10% of image width, report 0.3, -0.1.

Before responding with the final shift:

• Use the apply_and_view_offset_from_paths tool to verify your proposed offset.
• Provide current_image_path, reference_image_path, fractional_offset_y, and fractional_offset_x.
• You will see two images plotted side-by-side: the left will be the reference/previous image, and the right will be the current image shifted by the specified amount. Check if they are aligned. Refine the offset if needed.
• You may call this tool multiple times until alignment is satisfactory.

Output format requirements:

• Return exactly one line in this exact format: <shift_y>, <shift_x>.
• Do not add any extra text.
• If the two images have no overlap and cannot be registered, return exactly: nan, nan.

If you can't get a good alignment after 5 attempts, return nan, nan.

Make NaN handling consistent: use lowercase nan exactly when registration is not possible.

Sometimes the input images might have been already reasonably aligned. In that case, just report 0, 0.

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Examples

Example 1

Correct fractional offset: 0.13, 0.17

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Example 2

Correct fractional offset: -0.1, 0.1

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Example 3

Correct fractional offset: -0.15, 0.18

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Example 4

Correct fractional offset: 0.03, 0.03

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Example 5

Correct fractional offset: 0, 0