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System properties for debugging #91

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merged 2 commits into from
Sep 18, 2024
Merged

System properties for debugging #91

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c58818b
System properties for debugging
petebankhead Sep 13, 2024
fbdffab
Fix tile debugging
petebankhead Sep 13, 2024
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93 changes: 74 additions & 19 deletions src/main/java/qupath/ext/instanseg/core/InstanSeg.java
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Original file line number Diff line number Diff line change
Expand Up @@ -5,10 +5,14 @@
import ai.djl.ndarray.BaseNDManager;
import ai.djl.repository.zoo.Criteria;
import ai.djl.training.util.ProgressBar;
import org.bytedeco.opencv.global.opencv_core;
import org.bytedeco.opencv.opencv_core.Mat;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import qupath.lib.experimental.pixels.OpenCVProcessor;
import qupath.lib.experimental.pixels.OutputHandler;
import qupath.lib.experimental.pixels.Parameters;
import qupath.lib.experimental.pixels.Processor;
import qupath.lib.images.ImageData;
import qupath.lib.images.servers.ColorTransforms;
import qupath.lib.objects.PathAnnotationObject;
Expand Down Expand Up @@ -226,33 +230,34 @@ private InstanSegResults runInstanSeg(ImageData<BufferedImage> imageData, Collec
printResourceCount("Resource count after creating predictors",
(BaseNDManager)baseManager.getParentManager());

int sizeWithoutPadding = (int) Math.ceil(downsample * (tileDims - (double) padding*2));
var predictionProcessor = new TilePredictionProcessor(predictors, inputChannels, tileDims, tileDims, padToInputSize);
var tiler = createTiler(downsample, tileDims, padding);
var predictionProcessor = createProcessor(predictors, inputChannels, tileDims, padToInputSize);
var outputHandler = createOutputHandler(preferredOutputClass, randomColors, boundaryThreshold);
var postProcessor = createPostProcessor();

var processor = OpenCVProcessor.builder(predictionProcessor)
.imageSupplier((parameters) -> ImageOps.buildImageDataOp(inputChannels)
.apply(parameters.getImageData(), parameters.getRegionRequest()))
.tiler(Tiler.builder(sizeWithoutPadding)
.alignCenter()
.cropTiles(false)
.build()
)
.outputHandler(
new PruneObjectOutputHandler<>(
new InstanSegOutputToObjectConverter(preferredOutputClass, randomColors), boundaryThreshold))
.tiler(tiler)
.outputHandler(outputHandler)
.padding(padding)
.postProcess(createPostProcessor())
.postProcess(postProcessor)
.downsample(downsample)
.build();
processor.processObjects(taskRunner, imageData, pathObjects);
int nObjects = pathObjects.stream().mapToInt(PathObject::nChildObjects).sum();
return new InstanSegResults(
predictionProcessor.getPixelsProcessedCount(),
predictionProcessor.getTilesProcessedCount(),
predictionProcessor.getTilesFailedCount(),
nObjects,
System.currentTimeMillis() - startTime,
predictionProcessor.wasInterrupted()
);
if (predictionProcessor instanceof TilePredictionProcessor tileProcessor) {
return new InstanSegResults(
tileProcessor.getPixelsProcessedCount(),
tileProcessor.getTilesProcessedCount(),
tileProcessor.getTilesFailedCount(),
nObjects,
System.currentTimeMillis() - startTime,
tileProcessor.wasInterrupted()
);
} else {
return InstanSegResults.emptyInstance();
}
} finally {
for (var predictor: predictors) {
predictor.close();
Expand All @@ -266,6 +271,54 @@ private InstanSegResults runInstanSeg(ImageData<BufferedImage> imageData, Collec
}
}

/**
* Check if we are requesting tiles for debugging purposes.
* When this is true, we should create objects that represent the tiles - not the objects to be detected.
* @return
*/
private static boolean debugTiles() {
return System.getProperty("instanseg.debug.tiles", "false").strip().equalsIgnoreCase("true");
}

private static Processor<Mat, Mat, Mat> createProcessor(BlockingQueue<Predictor<Mat, Mat>> predictors,
Collection<? extends ColorTransforms.ColorTransform> inputChannels,
int tileDims, boolean padToInputSize) {
if (debugTiles())
return InstanSeg::createOnes;
return new TilePredictionProcessor(predictors, inputChannels, tileDims, tileDims, padToInputSize);
}

private static Mat createOnes(Parameters<Mat, Mat> parameters) {
var tileRequest = parameters.getTileRequest();
int width, height;
if (tileRequest == null) {
var region = parameters.getRegionRequest();
width = (int)Math.round(region.getWidth() / region.getDownsample());
height = (int)Math.round(region.getHeight() / region.getDownsample());
} else {
width = tileRequest.getTileWidth();
height = tileRequest.getTileHeight();
}
return Mat.ones(height, width, opencv_core.CV_8UC1).asMat();
}

private static OutputHandler<Mat, Mat, Mat> createOutputHandler(Class<? extends PathObject> preferredOutputClass, boolean randomColors,
int boundaryThreshold) {
if (debugTiles())
return OutputHandler.createUnmaskedObjectOutputHandler(OpenCVProcessor.createAnnotationConverter());
return new PruneObjectOutputHandler<>(
new InstanSegOutputToObjectConverter(preferredOutputClass, randomColors), boundaryThreshold);
}

private static Tiler createTiler(double downsample, int tileDims, int padding) {
int sizeWithoutPadding = (int) Math.ceil(downsample * (tileDims - (double) padding*2));
return Tiler.builder(sizeWithoutPadding)
.alignCenter()
.cropTiles(false)
.build();
}


/**
* Get the input channels to use; if we don't have any specified, use all of them
* @param imageData
Expand All @@ -284,6 +337,8 @@ private List<ColorTransforms.ColorTransform> getInputChannels(ImageData<Buffered
}

private static ObjectProcessor createPostProcessor() {
if (debugTiles())
return null;
var merger = ObjectMerger.createIoMinMerger(0.5);
var fixer = OverlapFixer.builder()
.clipOverlaps()
Expand Down
2 changes: 1 addition & 1 deletion src/main/java/qupath/ext/instanseg/core/TilePredictionProcessor.java
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Original file line number Diff line number Diff line change
Expand Up @@ -143,7 +143,7 @@ public Mat process(Parameters<Mat, Mat> params) throws IOException {
var matOutput = predictor.predict(mat);

// These are useful for spotting issues with the model
if (System.getProperty("instanseg.showTiles", "false").equalsIgnoreCase("true")) {
if (System.getProperty("instanseg.debug.predictions", "false").equalsIgnoreCase("true")) {
OpenCVTools.matToImagePlus("Input " + params.getRegionRequest(), mat).show();
OpenCVTools.matToImagePlus("Output " + params.getRegionRequest(), matOutput).show();
}
Expand Down
4 changes: 3 additions & 1 deletion src/main/java/qupath/ext/instanseg/ui/InstanSegController.java
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Original file line number Diff line number Diff line change
Expand Up @@ -794,14 +794,16 @@ private void runInstanSeg(InstanSegModel model) {
CompletableFuture.supplyAsync(this::ensurePyTorchAvailable, ForkJoinPool.commonPool())
.thenAccept((Boolean success) -> {
if (success) {
pendingTask.set(task);
// Reset the pending task when it completes (either successfully or not)
task.stateProperty().addListener((observable, oldValue, newValue) -> {
if (Set.of(Worker.State.CANCELLED, Worker.State.SUCCEEDED, Worker.State.FAILED).contains(newValue)) {
if (pendingTask.get() == task)
pendingTask.set(null);
}
});
// Setting the pending task prompts it to be run (so we need to do it after attaching
// the listener, in case it ends really quickly)
pendingTask.set(task);
}
});
}
Expand Down