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Tried it on chat gpt 4, here what it thinks:
This image is a collage that alternates between photos of Chihuahuas and blueberry muffins. The arrangement is such that it plays on the visual similarities between the two, with the muffins and parts of the Chihuahuas (likely their faces) mimicking each other in color and texture. This creates a humorous effect, as it can be initially challenging to differentiate between the muffins and the dogs.
Starting from the top left corner and moving left to right, row by row:
- Blueberry muffin with spots resembling a dog's eyes and nose.
- Face of a Chihuahua with a similar coloration to the muffin.
- Blueberry muffin resembling the face of a Chihuahua.
- Chihuahua face with a light fur color matching the muffin's surface.
- Chihuahua face with dark eyes and nose similar to blueberry spots.
- Muffin with a pattern that resembles a Chihuahua's facial features.
- Chihuahua with an expression and coloring that echoes the appearance of a muffin.
- Muffin with blueberries and coloring that looks like a Chihuahua's face.
- Chihuahua with a facial expression and fur colors that mimic a muffin's texture.
- Muffin with blueberries mimicking the eyes and nose of a Chihuahua.
- Chihuahua with features that resemble the spots on a muffin.
- Muffin resembling a Chihuahua's face in color and texture.
- Close-up of a Chihuahua's face with colors similar to a blueberry muffin.
- Muffin with a pattern of blueberries resembling a Chihuahua's face.
- Chihuahua looking directly at the camera, with fur colors like a muffin.
- Two Chihuahuas close together, with their heads resembling muffin tops.
Conclusion it sometimes gets fooled :)
It's likely seen the image before. Try randomising the image, reversing some of them, altering the gamma, and adding some noise. See how it does then.
It did make errors, also the training of it is old it's unlikely that it seen the images