This is an experiment I started a while ago before life happened. It
reduces memory usage of fast evaluation (-o2 and lower), bringing it
inline with normal (slow) evaluation. It does this by not retaining the
filtered image data of the evaluations, but instead retaining the row
filters that were used in each line so it can be quickly re-filtered
when required. This does incur a tiny performance penalty, but it's
negligible even at `-o0`.
Although this is fully functional, there are a few rough spots in the
code so I'm just opening it as a draft for now.
```
PR -sao6
70.08 real 614.36 user 2.66 sys
2024243200 maximum resident set size
1839339520 peak memory footprint
PR -sao2
11.16 real 60.85 user 1.33 sys
1982562304 maximum resident set size
1842173824 peak memory footprint
PR -sao2 -t1
55.11 real 53.85 user 0.76 sys
429457408 maximum resident set size
245008064 peak memory footprint
master -sao6
67.70 real 616.07 user 2.72 sys
2043379712 maximum resident set size
1838340416 peak memory footprint
master -sao2
11.53 real 60.63 user 1.25 sys
2753396736 maximum resident set size
2283741440 peak memory footprint
master -sao2 -t1
54.29 real 53.55 user 0.72 sys
626311168 maximum resident set size
305252544 peak memory footprint
```
Note that this involves some refactoring of `RowFilter` and the new
`FilterStrategy`. These are breaking changes so it will ultimately be
destined for v10. One advantage to this new structure is it opens the
door for future changes such as allowing the Brute strategy to take a
parameter for the number of lines.
* Refactor filters as enum
* Include filter byte in filter output
* Add entropy filter
* Add bigrams filter
* Add bigram entropy filter
* Add brute filter
* Replace bit-vec
* Add tests and benches
* Show filters in help
* Use FxHasher in color to palette
* Use windows function for minor improvement
