Not logged in.  Login/Logout/Register | List snippets | | Create snippet | Upload image | Upload data

155
LINES

< > BotCompany Repo | #1027225 // MultiLevelRecognizer1 - finds a single prototype image

JavaX fragment (include) [tags: use-pretranspiled]

Uses 108K of libraries. Click here for Pure Java version (10773L/76K).

1  
// complexity is number of assumed heights * number of widths
2  
sclass MultiLevelRecognizer1 {
3  
  // how big do we think the prototype is in the whole image
4  
  // (percentage by height)
5  
  transient L<Double> assumedPrototypeHeightPercentages =
 ll(70.0, 70.0/sqrt(2), 35.0, 35.0/sqrt(2), 17.0);
6  
  
7  
  // widths to scale camera image to
8  
  transient L<Int> widths = ll(32, 64, 128);
9  
  
10  
  transient JTabbedPane tabs; // initialize if you want visualization
11  
  transient ImageSurface bestImageSurface;
12  
  transient JLabel bestLabel;
13  
  
14  
  transient BWIntegralImage baseImage;
15  
  transient BWImage prototypeImage;
16  
  transient new L<IBWIntegralImage> integralImages;
17  
  transient new L<Chain> chains; // one per assumed height
18  
  
19  
  // chain of recognizers for one assumed height
20  
  class Chain {
21  
    double assumedHeightPercentage;
22  
    new L<OneLevel> levels; // recognizers for each granularity
23  
    
24  
    *(double *assumedHeightPercentage) { make(); }
25  
26  
    void make {
27  
      for (int w : widths) {
28  
        IBWIntegralImage ii = scaledIBWIntegralImage(baseImage, w);
29  
        integralImages.add(ii);
30  
        OneLevel lvl = new(this, ii);
31  
        levels.add(lvl);
32  
        if (tabs != null && eq(w, last(widths))) {
33  
          lvl.is = jPixelatedZoomedImageSurface(
34  
            doubleRatio(baseImage.getWidth(), w), iBWIntegralImageToBWImage(ii));
35  
          addTab(tabs, iround(assumedHeightPercentage) + ":" + w, northAndCenterWithMargins(
36  
            lvl.infoLabel = jcenteredlabel(), jFullCenterScroll(lvl.is)));
37  
        }
38  
      }
39  
    }
40  
41  
    Steppable makeSteppable() {
42  
      ret iteratorToSteppable(roundRobinCombinedIterator(lambdaMap steppableToIterator(levels)));
43  
    }
44  
    
45  
    Scored<Rect> bestResult() {
46  
      ret last(levels).scoredBestRescaled();
47  
    }
48  
  }
49  
50  
  class OneLevel extends SteppableAndBest<Rect> {
51  
    Chain chain;
52  
    IBWIntegralImage ii; // scaled integral image
53  
    BWImage image;       // scaled image
54  
    BWImage prototype;   // scaled prototype
55  
    float minSimilarity = 0.5f;
56  
    
57  
    ImageSurface is;
58  
    JLabel infoLabel;
59  
60  
    // candidates are top-left corner of rect to try in our coordinates
61  
    L<Pt> candidatesQueue = syncLinkedList();
62  
    new Set<Pt> candidatesTried;
63  
    Iterator<Pt> candidatesStream;
64  
65  
    *(Chain *chain, IBWIntegralImage *ii) {
66  
      image = iBWIntegralImageToBWImage(ii);
67  
      // get assumed height of prototype in scaled-down image
68  
      int ph = iround(ii.getHeight()*chain.assumedHeightPercentage/100.0);
69  
      // resize prototype
70  
      prototype = bwResizeToHeightSmooth(prototypeImage, ph);
71  
      /*addTab(tabs, "proto " + ii.getWidth(),
 jFullCenterScroll(jPixelatedZoomedImageSurface(4.0, prototype)));
*/
72  
      candidatesStream = mapI rectTopLeftCorner(allSubRectsOfSizeIterator(prototype.getWidth(), prototype.getHeight(),
73  
        imageRect(image)));
74  
    }
75  
    
76  
    public bool step() {
77  
      Pt p = nextCandidate();
78  
      if (p != null) ret true with tryCandidate(p);
79  
      false;
80  
    }
81  
82  
    Pt nextCandidate() {
83  
      try object Pt p = popFirst(candidatesQueue);
84  
      ret nextFromIterator(candidatesStream);
85  
    }
86  
87  
    void tryCandidate(Pt p) {
88  
      if (!candidatesTried.add(p)) ret;
89  
90  
      int x = p.x, y = p.y, wp = prototype.getWidth(), hp = prototype.getHeight();
91  
92  
      float maxError = (1f-minSimilarity)*wp*hp;
93  
      float diff = bwImageSectionsSimilarity(image, prototype, x, y, maxError);
94  
      if (diff <= maxError)
95  
        best.put(new Rect(x, y, wp, hp), 1-diff/(wp*hp));
96  
    }
97  
98  
    void showBest() {
99  
      setImageSurfaceSelection(is, best!);
100  
      setText(infoLabel, best);
101  
    }
102  
    
103  
    // best rect in original image coordinates
104  
    Rect bestRescaled() {
105  
      ret rescaleRect(best!, ii.getWidth(), ii.getHeight(),
106  
        baseImage.getWidth(), baseImage.getHeight());
107  
    }
108  
    
109  
    Scored<Rect> scoredBestRescaled() {
110  
      ret scored(bestRescaled(), best.score);
111  
    }
112  
  }
113  
  
114  
  *() {}
115  
  *(File prototypeImage, File imgFile) {
116  
    this.prototypeImage = loadBWImage(prototypeImage);
117  
    this.baseImage = loadBWIntegralImage(imgFile);
118  
  }
119  
120  
  Scored<Rect> go() {
121  
    assertNotNull(+baseImage);
122  
    assertNotNull(+prototypeImage);
123  
    
124  
    if (tabs != null)
125  
      addTab(tabs, "Best", northAndCenterWithMargins(
126  
        bestLabel = jcenteredlabel(), 
127  
        jFullCenterScroll(bestImageSurface = jImageSurface(bwIntegralImageToBWImage(baseImage)))));
128  
        
129  
    makeChains();
130  
131  
    time "Process" {
132  
      print("Steps: " + stepAll_roundRobin(map(chains, c -> c.makeSteppable())));
133  
    }
134  
  
135  
    showBest();
136  
    ret bestResult();
137  
  }
138  
  
139  
  void showBest {
140  
    for (Chain c : chains)
141  
      for (OneLevel l : c.levels)
142  
        l.showBest();
143  
    setText(bestLabel, bestResult());
144  
    setImageSurfaceSelection(bestImageSurface, bestResult()!);
145  
  }
146  
  
147  
  void makeChains {
148  
    for (double ah : assumedPrototypeHeightPercentages)
149  
      chains.add(new Chain(ah));
150  
  }
151  
      
152  
  Scored<Rect> bestResult() {
153  
    ret bestScored(map(methodLambda0 bestResult, chains));
154  
  }
155  
}

download  show line numbers  debug dex  old transpilations   

Travelled to 7 computer(s): bhatertpkbcr, mqqgnosmbjvj, pyentgdyhuwx, pzhvpgtvlbxg, tvejysmllsmz, vouqrxazstgt, xrpafgyirdlv

No comments. add comment

Snippet ID: #1027225
Snippet name: MultiLevelRecognizer1 - finds a single prototype image
Eternal ID of this version: #1027225/32
Text MD5: 2d327724a16b29fd1513a986e012be05
Transpilation MD5: 3b267b00ce652cb4b0c5826b3fd604cc
Author: stefan
Category: javax / image recognition
Type: JavaX fragment (include)
Public (visible to everyone): Yes
Archived (hidden from active list): No
Created/modified: 2020-02-26 15:16:33
Source code size: 5053 bytes / 155 lines
Pitched / IR pitched: No / No
Views / Downloads: 260 / 701
Version history: 31 change(s)
Referenced in: [show references]