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Diffstat (limited to 'README.md')
| -rw-r--r-- | README.md | 9 |
1 files changed, 5 insertions, 4 deletions
@@ -1,6 +1,6 @@ # embeddings-sort -This program can sort images such that ones with similar motives are close together. This is accomplished by using [AI](https://github.com/minimaxir/imgbeddings) to extract the meaning of the image, and then approximating a travelling-salesperson-tour through all of them. +This program can sort images such that ones with similar content are close together. This is accomplished by using AI to extract the meaning of the image, and then approximating a travelling-salesperson-tour through all of them. As a bonus feature, this program can also sort the images by hue, brightness or color, though the results for this could be improved by using a less generalized algorithm. The sorting can be accessed by letting the progam print the image paths in order, or by copying/symlinking the images into a new directory. @@ -11,7 +11,7 @@ Detailed usage: Usage: embeddings-sort [OPTIONS] [IMAGES]... Arguments: - [IMAGES]... + [IMAGES]... Options: -e, --embedder <EMBEDDER> Characteristic to sort by [default: content-angular-distance] [possible values: brightness, hue, color, content-euclidean, content-angular-distance, content-manhatten] @@ -21,7 +21,8 @@ Options: -0, --stdout0 Write sorted paths into stdout, null-separated. Overrides -c -b, --benchmark Output total tour length to stderr --tsp-approx <TSP_APPROX> Algorithm for TSP approximation. Leave as default if unsure [default: christofides] [possible values: mst-dfs, christofides] - -r <REFINE> Number of 2-Opt refinement steps. Has quickly diminishing returns [default: 3] + -r <REFINE> Number of 2-Opt refinement steps. Has quickly diminishing returns [default: 5] + --no-rotate Don't try to improve result by rotating the output path such that less emphasis is put on the similarity of the first and last image -i, --ignore-errors Ignore failed embeddings --hash-seed <HASH_SEED> Seed for hashing. Random by default -h, --help Print help @@ -30,7 +31,7 @@ Options: ## Insides The christofides implementation uses an approximated min-weight matching algorithm, which may be non-ideal, though I haven't benchmarked how much of a difference it makes (mainly due to the implementation complexity of an exact algorithm, which would also increase the implementations complexity from O(n²) to O(n³) where n is the number of given images). -The 2-Opt refinement algorithm uses a doubly linked list with implicit iteration order to be able to do 2-Opt swaps in O(1), bringing a 2-Opt iteration to O(n²) complexity. +The 2-Opt refinement algorithm uses a doubly linked list with implicit iteration order to be able to do 2-Opt swaps in O(1), bringing a 2-Opt iteration to O(n²) complexity. Unless `--no-rotate` is given, the calculated path is rotated in-between 2-Opt iterations such that the longest edge is between the first and the last image - as this edge is of no importance for the output of the algorithm, this improves output quality, though it does not improve the output according to the TSP problem formulation. ## Compatibility `embeddings-sort` has, at some point, worked on both linux and windows. |