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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,168 @@ | ||
| #include <string.h> | ||
| #include <math.h> | ||
| #include "FireLog.h" | ||
| #include "FireSight.hpp" | ||
| #include "opencv2/features2d/features2d.hpp" | ||
| #include "opencv2/highgui/highgui.hpp" | ||
| #include "opencv2/imgproc/imgproc.hpp" | ||
| #include "jansson.h" | ||
| #include "jo_util.hpp" | ||
| #include "MatUtil.hpp" | ||
|
|
||
| using namespace cv; | ||
| using namespace std; | ||
| using namespace firesight; | ||
|
|
||
| bool Pipeline::apply_calcOffset(json_t *pStage, json_t *pStageModel, Model &model) { | ||
| validateImage(model.image); | ||
| string tmpltPath = jo_string(pStage, "template", "", model.argMap); | ||
| int xtol = jo_int(pStage, "xtol", 32, model.argMap); | ||
| int ytol = jo_int(pStage, "ytol", 32, model.argMap); | ||
| vector<int> channels = jo_vectori(pStage, "channels", vector<int>(), model.argMap); | ||
| assert(model.image.cols > 2*xtol); | ||
| assert(model.image.rows > 2*ytol); | ||
| Rect roi= jo_Rect(pStage, "roi", Rect(xtol, ytol, model.image.cols-2*xtol, model.image.rows-2*ytol), model.argMap); | ||
| Rect roiScan = Rect(roi.x-xtol, roi.y-ytol, roi.width+2*xtol, roi.height+2*ytol); | ||
| float minval = jo_float(pStage, "minval", 0.7f, model.argMap); | ||
| float corr = jo_float(pStage, "corr", 0.99f); | ||
| string outputStr = jo_string(pStage, "output", "current", model.argMap); | ||
| const char *errMsg = NULL; | ||
| int flags = INTER_LINEAR; | ||
| int method = CV_TM_CCOEFF_NORMED; | ||
| Mat tmplt; | ||
| int borderMode = BORDER_REPLICATE; | ||
|
|
||
| if (tmpltPath.empty()) { | ||
| errMsg = "Expected template path for imread"; | ||
| } else { | ||
| if (model.image.channels() == 1) { | ||
| tmplt = imread(tmpltPath.c_str(), CV_LOAD_IMAGE_GRAYSCALE); | ||
| } else { | ||
| tmplt = imread(tmpltPath.c_str(), CV_LOAD_IMAGE_COLOR); | ||
| } | ||
| if (tmplt.data) { | ||
| LOGTRACE2("apply_calcOffset(%s) %s", tmpltPath.c_str(), matInfo(tmplt).c_str()); | ||
| if (model.image.rows<tmplt.rows || model.image.cols<tmplt.cols) { | ||
| errMsg = "Expected template smaller than image to match"; | ||
| } | ||
| } else { | ||
| errMsg = "imread failed"; | ||
| } | ||
| } | ||
| if (!errMsg) { | ||
| if (model.image.channels() > 3) { | ||
| errMsg = "Expected at most 3 channels for pipeline image"; | ||
| } else if (tmplt.channels() != model.image.channels()) { | ||
| errMsg = "Template and pipeline image must have same number of channels"; | ||
| } else { | ||
| for (int iChannel = 0; iChannel < channels.size(); iChannel++) { | ||
| if (channels[iChannel] < 0 || model.image.channels() <= channels[iChannel]) { | ||
| errMsg = "Referenced channel is not in image"; | ||
| } | ||
| } | ||
| } | ||
| } | ||
|
|
||
| if (!errMsg) { | ||
| Mat result; | ||
| Mat imagePlanes[] = { Mat(), Mat(), Mat() }; | ||
| Mat tmpltPlanes[] = { Mat(), Mat(), Mat() }; | ||
| if (channels.size() == 0) { | ||
| channels.push_back(0); | ||
| if (model.image.channels() == 1) { | ||
| imagePlanes[0] = model.image; | ||
| tmpltPlanes[0] = tmplt; | ||
| } else { | ||
| cvtColor(model.image, imagePlanes[0], CV_BGR2GRAY); | ||
| cvtColor(tmplt, tmpltPlanes[0], CV_BGR2GRAY); | ||
| } | ||
| } else if (model.image.channels() == 1) { | ||
| imagePlanes[0] = model.image; | ||
| tmpltPlanes[0] = tmplt; | ||
| } else { | ||
| split(model.image, imagePlanes); | ||
| split(tmplt, tmpltPlanes); | ||
| } | ||
|
|
||
| json_t *pChannels = json_object(); | ||
| json_object_set(pStageModel, "channels", pChannels); | ||
| for (int iChannel=0; iChannel<channels.size(); iChannel++) { | ||
| int channel = channels[iChannel]; | ||
| Mat imageSource(imagePlanes[channel], roiScan); | ||
| Mat tmpltSource(tmpltPlanes[channel], roi); | ||
|
|
||
| matchTemplate(imageSource, tmpltSource, result, method); | ||
| LOGTRACE4("apply_calcOffset() matchTemplate(%s,%s,%s,CV_TM_CCOEFF_NORMED) channel:%d", | ||
| matInfo(imageSource).c_str(), matInfo(tmpltSource).c_str(), matInfo(result).c_str(), channel); | ||
|
|
||
| vector<Point> matches; | ||
| float maxVal = *max_element(result.begin<float>(),result.end<float>()); | ||
| float rangeMin = corr * maxVal; | ||
| float rangeMax = maxVal; | ||
| matMaxima(result, matches, rangeMin, rangeMax); | ||
|
|
||
| if (logLevel >= FIRELOG_TRACE) { | ||
| for (size_t iMatch=0; iMatch<matches.size(); iMatch++) { | ||
| int mx = matches[iMatch].x; | ||
| int my = matches[iMatch].y; | ||
| float val = result.at<float>(my,mx); | ||
| if (val < minval) { | ||
| LOGTRACE4("apply_calcOffset() ignoring (%d,%d) val:%g corr:%g", mx, my, val, val/maxVal); | ||
| } else { | ||
| LOGTRACE4("apply_calcOffset() matched (%d,%d) val:%g corr:%g", mx, my, val, val/maxVal); | ||
| } | ||
| } | ||
| } | ||
| json_t *pMatches = json_object(); | ||
| char key[10]; | ||
| snprintf(key, sizeof(key), "%d", channel); | ||
| json_object_set(pChannels, key, pMatches); | ||
| if (matches.size() == 1) { | ||
| int mx = matches[0].x; | ||
| int my = matches[0].y; | ||
| float val = result.at<float>(my,mx); | ||
| if (minval <= val) { | ||
| int dx = xtol - mx; | ||
| int dy = ytol - my; | ||
| json_object_set(pMatches, "dx", json_integer(dx)); | ||
| json_object_set(pMatches, "dy", json_integer(dy)); | ||
| json_object_set(pMatches, "match", json_float(val)); | ||
| } | ||
| } | ||
| } | ||
|
|
||
| json_t *pRects = json_array(); | ||
| json_object_set(pStageModel, "rects", pRects); | ||
| json_t *pRect = json_object(); | ||
| json_array_append(pRects, pRect); | ||
| json_object_set(pRect, "x", json_integer(roi.x+roi.width/2)); | ||
| json_object_set(pRect, "y", json_integer(roi.y+roi.height/2)); | ||
| json_object_set(pRect, "width", json_integer(roi.width)); | ||
| json_object_set(pRect, "height", json_integer(roi.height)); | ||
| json_object_set(pRect, "angle", json_integer(0)); | ||
| pRect = json_object(); | ||
| json_array_append(pRects, pRect); | ||
| json_object_set(pRect, "x", json_integer(roiScan.x+roiScan.width/2)); | ||
| json_object_set(pRect, "y", json_integer(roiScan.y+roiScan.height/2)); | ||
| json_object_set(pRect, "width", json_integer(roiScan.width)); | ||
| json_object_set(pRect, "height", json_integer(roiScan.height)); | ||
| json_object_set(pRect, "angle", json_integer(0)); | ||
|
|
||
| normalize(result, result, 0, 255, NORM_MINMAX); | ||
| result.convertTo(result, CV_8U); | ||
| Mat corrInset = model.image.colRange(0,result.cols).rowRange(0,result.rows); | ||
| switch (model.image.channels()) { | ||
| case 3: | ||
| cvtColor(result, corrInset, CV_GRAY2BGR); | ||
| break; | ||
| case 4: | ||
| cvtColor(result, corrInset, CV_GRAY2BGRA); | ||
| break; | ||
| default: | ||
| result.copyTo(corrInset); | ||
| break; | ||
| } | ||
| } | ||
|
|
||
| return stageOK("apply_calcOffset(%s) %s", errMsg, pStage, pStageModel); | ||
| } |
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