public static SearchResult <T> Find <T>(IEnumerable <T> collection, string input, Func <T, ISearchableProperty> searchProperties)
{
var normalizedInput = input.ToLower();
var lev = new Fastenshtein.Levenshtein(normalizedInput);
var lowestDistance = int.MaxValue;
var currentWinner = default(T);
foreach (var item in collection)
{
foreach (var searchProperty in searchProperties(item).AsStrings)
{
var termToMatchAgainst = searchProperty.ToLower();
if (termToMatchAgainst == normalizedInput)
{
return(new SearchResult <T>(item, 0));
}
var distance = lev.DistanceFrom(termToMatchAgainst);
if (distance >= lowestDistance)
{
continue;
}
lowestDistance = distance;
currentWinner = item;
}
}
return(new SearchResult <T>(currentWinner, lowestDistance));
}
// Grab text from image
private string GetText(TessBaseAPI tessBaseAPI, int partX, int partY)
{
// These can change depending on resolution, HUD scaling, or UI changes
// For now, only supports 1440p with full HUD scaling
// TODO: Dynamic scaling
const int BOXWIDTH = 311;
const int BOXHEIGHT = 33;
// Set image location start
tessBaseAPI.SetRectangle(partX, partY, BOXWIDTH, BOXHEIGHT);
// Recognize image
tessBaseAPI.Recognize();
ResultIterator resultIterator = tessBaseAPI.GetIterator();
// Extract text from result iterator
StringBuilder stringBuilder = new StringBuilder();
PageIteratorLevel pageIteratorLevel = PageIteratorLevel.RIL_PARA;
do
{
stringBuilder.Append(resultIterator.GetUTF8Text(pageIteratorLevel));
} while (resultIterator.Next(pageIteratorLevel));
// Fix up string for Warframe.market
stringBuilder = stringBuilder.Replace("\n", String.Empty);
string guess = stringBuilder.ToString();
// Changed to use Levenshtein here due to important of having a matching "Blueprint" word
Levenshtein levBP = new Fastenshtein.Levenshtein("Blueprint");
int levBPDistance = levBP.DistanceFrom(guess);
Debug.WriteLine("Distance from Blueprint: " + levBPDistance);
// If there is a 4-character difference, accept the word is == "Blueprint"
// Adjust the offset for 2-lined parts
if (levBPDistance < 5)
{
guess = GetText(tessBaseAPI, partX, 550);
}
// Match whatever result we get to the closest selling item name from Warframe.market
// We want to ignore "Blueprint" because this indicates that it's a 2-lined item
if (guess != "Blueprint" && !guess.Contains("Forma"))
{
Debug.Write("");
Debug.Write("Old: " + guess);
guess = FindClosestWord(guess);
Debug.WriteLine(" | New: " + guess);
}
return(guess);
}
private void SearchLev()
{
Debug.Log("Searching Lev now");
var stopwatch = new Stopwatch();
stopwatch.Start();
Levenshtein lev = new Levenshtein(searchTerm);
for (var index = 0; index < termList.Count; index++)
{
var term = termList[index];
int levenshteinDistance = lev.DistanceFrom(term);
}
stopwatch.Stop();
Debug.Log("Lev terms in ticks: " + stopwatch.ElapsedTicks);
Debug.Log("Break");
}
// The Levenshtein distance algorithm is awesome. This basically allows us to quickly compute the distance between words
// This function is called when a proper json can't be found and tries to find the closest part from all currently known tradable parts
private string FindClosestWord(string word)
{
Levenshtein lev = new Fastenshtein.Levenshtein(word);
int minDistance = 9999;
string potential = "";
using (StreamReader r = new StreamReader(@"items\items.json"))
{
string json = r.ReadToEnd();
JObject items = (JObject)JsonConvert.DeserializeObject(json);
foreach (var item in items["payload"]["items"])
{
string currentItem = item["item_name"].ToString(); //.ToUpper();
int levenshteinDistance = lev.DistanceFrom(currentItem);
//Debug.WriteLine((string)item["item_name"] + " | " + levenshteinDistance);
if (minDistance > levenshteinDistance)
{
minDistance = levenshteinDistance;
potential = currentItem;
}
}
}
// Arbitrary value; needs more testing for the sweetspot
/*if (minDistance <= 15)
* {
* return potential;
* }
* return word;
*/
return(potential);
}