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Tentative fix for handling time-lapses. #1

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Tentative fix for handling time-lapses. #1

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ee4ab37
Tentative fix for handling time-lapses.
tinevez Jan 4, 2021
8683d7f
Make the plugin stoppable.
tinevez Jan 4, 2021
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13 changes: 9 additions & 4 deletions src/main/java/plugins/frauzufall/deeplearning/tensorflow/TensorFlowModelPrediction.java
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Original file line number Diff line number Diff line change
Expand Up @@ -95,10 +95,16 @@ public Sequence predict(Sequence inputSequence) {
@Override
public Sequence predict(Sequence inputSequence, int time) {
Sequence normalized = normalize(inputSequence, time);
inputSequence.setImage(0, 0, normalized.getImage(0, 0));
return super.predict(normalized, time);
// Because the normalized sequence has only 1 time-point, we have to process its first time-point, the number 0.
return super.predict(normalized, 0);
}

/**
* Normalizes the time-point of the specified sequence, and returns the results in a <b>1 time-point</b> sequence.
* @param input the sequence to normalize.
* @param time the time-point to normalize.
* @return a new sequence, with only one time-point.
*/
private Sequence normalize(Sequence input, int time) {
double[] values = new double[input.getWidth() * input.getHeight()];
for (int x = 0; x < input.getWidth(); x++) {
Expand All @@ -115,8 +121,7 @@ private Sequence normalize(Sequence input, int time) {
valuesOut[i] = (float) ((values[i] - minVal) * factor);
}
Sequence res = new Sequence(resImg);
res.setDataXY(time, 0, 0, valuesOut);
res.setDataXY(0, 0, 0, valuesOut);
return res;
}

}
39 changes: 29 additions & 10 deletions src/main/java/plugins/stardist/StarDist2DPlugin.java
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@
import plugins.adufour.ezplug.EzGroup;
import plugins.adufour.ezplug.EzLabel;
import plugins.adufour.ezplug.EzPlug;
import plugins.adufour.ezplug.EzStoppable;
import plugins.adufour.ezplug.EzVarBoolean;
import plugins.adufour.ezplug.EzVarDouble;
import plugins.adufour.ezplug.EzVarEnum;
Expand All @@ -31,7 +32,7 @@
import java.lang.reflect.InvocationTargetException;
import java.util.Map;

public class StarDist2DPlugin extends EzPlug
public class StarDist2DPlugin extends EzPlug implements EzStoppable
{

private final String msgTitle = "<html>" +
Expand All @@ -56,6 +57,8 @@ public class StarDist2DPlugin extends EzPlug
private EzVarBoolean normalizeInput;
private EzVarEnum<AvailableModels.Model2D> modelChoice;

private boolean wasCanceled;

@Override
protected void initialize()
{
Expand Down Expand Up @@ -108,19 +111,26 @@ public void clean()
{
// Nothing to do
}

@Override
public void stopExecution()
{
this.wasCanceled = true;
}

@Override
protected void execute()
{

// Load in a separate thread.
ThreadUtil.bgRun(() -> {
predict(input.getValue());
predict();
});
}

private void predict(Sequence sequence) {
Sequence inputSequence = input.getValue();
private void predict() {
wasCanceled = false;
Sequence sequence = input.getValue();
ModelPrediction prediction = new TensorFlowModelPrediction();
// if (roiPosition.equals(Opt.ROI_POSITION_AUTO))
// roiPositionActive = input.numDimensions() > 3 && !input.isRGBMerged() ? Opt.ROI_POSITION_HYPERSTACK : Opt.ROI_POSITION_STACK;
Expand Down Expand Up @@ -163,16 +173,23 @@ private void predict(Sequence sequence) {
// paramsNMS.put("verbose", verbose);

// final LinkedHashSet<AxisType> inputAxes = Utils.orderedAxesSet(input);
final boolean isTimelapse = inputSequence.getSizeT() > 1;
final boolean isTimelapse = sequence.getSizeT() > 1;

// TODO: option to normalize image/timelapse channel by channel or all channels jointly

if (isTimelapse) {
// TODO: option to normalize timelapse frame by frame (currently) or jointly
final long numFrames = inputSequence.getSizeT();
final long numFrames = sequence.getSizeT();
for (int t = 0; t < numFrames; t++) {
Sequence predictionResult = prediction.predict(inputSequence, t);
Candidates polygons = nms.run(predictionResult, t);
if (wasCanceled)
break;
getStatus().setMessage("Processing time-point " + t + " of " + numFrames);
Sequence predictionResult = prediction.predict(sequence, t);
/*
* Because the prediction results will only have 1 time-point, we need to run
* the NMS prediction on its first time-point, the number 0.
*/
Candidates polygons = nms.run(predictionResult, 0);
display(sequence, polygons, t);
getStatus().setCompletion((float)(1+t) / (float)numFrames);
}
Expand All @@ -181,7 +198,7 @@ private void predict(Sequence sequence) {
// - joint normalization of all frames
// - requires more memory to store intermediate results (prob and dist) of all frames
// - allows showing prob and dist easily
Sequence predictionResult = prediction.predict(inputSequence);
Sequence predictionResult = prediction.predict(sequence);
Candidates polygons = nms.run(predictionResult, 0);
display(sequence, polygons, 0);
}
Expand All @@ -195,6 +212,7 @@ private void predict(Sequence sequence) {
e.printStackTrace();
}
}
getStatus().done();
}

private void display(Sequence sequence, Candidates polygons, int time) {
Expand Down Expand Up @@ -232,7 +250,8 @@ public static void main( final String[] args ) {
* Programmatically launch a plugin, as if the user had clicked its
* button.
*/
String imagePath = "samples/blobs.png";
// String imagePath = "samples/blobs.png";
String imagePath = "C:/Users/tinevez/Development/TrackMateWS/TrackMate-StarDist/samples/P31-crop.tif";
final Sequence sequence = Loader.loadSequence( imagePath, 0, true );
display(sequence);
PluginLauncher.start( PluginLoader.getPlugin( StarDist2DPlugin.class.getName() ) );
Expand Down