Uses 911K of libraries. Click here for Pure Java version (8529L/45K).
!7 cmodule VectorLiveRecogSpike1 > DynImageSurfaceAndEnabled { transient ReliableSingleThread rstRecog = dm_rst(this, r recognize); start { rstRecog.trigger(); dm_vmBus_onMessage haveVectorImage((mod, _img) -> rstRecog.trigger()); } void recognize { if (!enabled) ret; BufferedImage inputImage = dm_getLatestVectorImage(); CheesyRecognizer rec = new(inputImage); CheesyRecognizer.Prototype proto = rec.addPrototype(loadBWImage(#1102893)); int w = rec.getWidth(); // input image width int w1 = 16; // coarse resolution to scan int w2 = 128; // fine resolution to scan print(+w); L<Int> assumedProtoSizes = sqrt2progression_int_dropFirst(5, w); print(+assumedProtoSizes); time "Recog" { // Look for center-of-object candidates in coarse resolution new LPair<Rect, Double> allCandidates; // for all proto sizes in coarse image L<Int> pwScaled = uniquify(map(pw -> scaleDouble_iround(w, w1, pw), assumedProtoSizes)); for (int pw : pwScaled) { // candidates are in full image resolution LPair<Rect, Double> candidates = rec.fullScanToNBest(proto, w1, pw, 0f, 3); printVars(+pwScaled, +candidates); allCandidates.addAll(candidates); } L<Rect> candidates = pairsA(takeFirst(5, sortBySecondOfPairsDesc_inPlace(allCandidates))); L<Pt> centers = centerOfRects(candidates); print(+candidates); print(+centers); // Stage 2: scan around candidates in higher resolution int h2 = rec.scaledInputImage(w2).getHeight(); int spiralSize = w2/w1*2; int pixelsPerSpiral = sqr(spiralSize); print("Spiral size: " + spiralSize + " / " + pixelsPerSpiral); new Best<Rect> best; CheesyRecognizer.ScaledInputImage scaledInputImage = rec.scaledInputImage(w2); L<Int> pwScaled2 = uniquify(map(pw -> scaleDouble_iround(w, w2, pw), assumedProtoSizes)); print(+pwScaled2); for (int pw : pwScaled2) { CheesyRecognizer.ScaledPrototype scaledProto = proto.scaledPrototype(pw); new Set<Pt> pointsTried; for (Pt p : centers) { // scaled center point, moved to top left of prototype Pt pScaled = translatePt(-pw/2, -scaledProto.getHeight()/2, scalePt(doubleRatio(w2, rec.getWidth()), p)); //print(+pScaled); for (Pt p2 : pixelSpiral(pScaled.x, pScaled.y, w2, h2, pixelsPerSpiral)) { if (!pointsTried.add(p2)) continue; //print("Trying point " + p2); Pair<Rect, Double> result = rec.singleCheck(scaledInputImage, scaledProto, p2.x, p2.y, 0f); best.put(result); } } } Scored<Rect> bestInInputSpace = scored(scaleRect(doubleRatio(rec.getWidth(), w2), best!), best.score); print(bestInInputSpace); } setImage(inputImage); setSelection(bestInInputSpace!); } }
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Snippet ID: | #1027288 |
Snippet name: | Vector Live Recognition Spike ["finds" the wrong spots?] |
Eternal ID of this version: | #1027288/5 |
Text MD5: | d566e35ca21bb9bc22c893ea337d4bf2 |
Transpilation MD5: | 1e04308c8aa45dcab4d0efb1a236d5ea |
Author: | stefan |
Category: | javax / maths |
Type: | JavaX source code (Dynamic Module) |
Public (visible to everyone): | Yes |
Archived (hidden from active list): | No |
Created/modified: | 2020-03-01 01:15:45 |
Source code size: | 3010 bytes / 74 lines |
Pitched / IR pitched: | No / No |
Views / Downloads: | 222 / 1581 |
Version history: | 4 change(s) |
Referenced in: | [show references] |