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| export function MatchingNote() { |
| return ( |
| <p className="text-xs text-gray-500 mt-3 leading-relaxed"> |
| <span className="font-medium text-gray-700">How it works:</span> A model turns each image into |
| a feature vector (a list of numbers) describing the dog. This is used like a fingerprint. |
| Visually similar dogs have similar features, so comparing features against the found-dog |
| database enables the tool to rank the closest look-alikes. The top 10 matches are always |
| returned, and the higher the score, the closer the match. If a dog is in the database, it is |
| usually returned as the top match or, at worst, should be among the top 10 matches over 95% of |
| the time. If all the scores are low, the dog is likely not in the database. |
| </p> |
| ); |
| } |
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| |
| export function BreedNote() { |
| return ( |
| <> |
| <p className="text-xs text-gray-500 mt-3 leading-relaxed"> |
| <span className="font-medium text-gray-700">How it works:</span> The breed classification |
| model attempts to predict a dog breed from an image. The higher the score, the more confident |
| the model is about a specific breed prediction. The top 10 breed guesses are always shown |
| even if most of the scores are very low. This does not imply a mixed breed dog. Many breeds |
| have similar visual features and photo angles vary, so the correct breed isn’t always |
| ranked first. However, for clear, known breed photos the correct breed should be listed in |
| the top 10 over 95% of the time. We don’t have accuracy stats on mixed breed images, |
| but the model will certainly surface breeds with similar features. |
| </p> |
| <p className="text-xs text-gray-500 mt-2 leading-relaxed"> |
| <span className="font-medium text-gray-700">Note:</span> The breed classification model is |
| entirely separate from image matching and is included here mainly for fun and interest. |
| </p> |
| </> |
| ); |
| } |
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