Types of output used by OutputPlaceholder.
//@input Component.MLComponent mlComponent//@input string outputName//@input Component.Image outputImagescript.mlComponent.onLoadingFinished = onLoadingFinished;function onLoadingFinished() { var output = script.mlComponent.getOutput(script.outputName); if (output.mode == MachineLearning.OutputMode.Data) { var outputData = output.data; for (var i = 0; i < outputData.length; i++) { print(outputData[i]); } } else { var texture = output.texture; script.outputImage.mainPass.baseTex = texture; }} Copy
//@input Component.MLComponent mlComponent//@input string outputName//@input Component.Image outputImagescript.mlComponent.onLoadingFinished = onLoadingFinished;function onLoadingFinished() { var output = script.mlComponent.getOutput(script.outputName); if (output.mode == MachineLearning.OutputMode.Data) { var outputData = output.data; for (var i = 0; i < outputData.length; i++) { print(outputData[i]); } } else { var texture = output.texture; script.outputImage.mainPass.baseTex = texture; }}
//@input vec2 outputSize = {1, 1}//@input string outputName = "probs"var outputChannels = 200;var outputBuilder = MachineLearning.createOutputBuilder();outputBuilder.setName(script.outputName);outputBuilder.setShape(new vec3(script.outputSize.x, script.outputSize.y, outputChannels));outputBuilder.setOutputMode(MachineLearning.OutputMode.Data);var outputPlaceholder = outputBuilder.build(); Copy
//@input vec2 outputSize = {1, 1}//@input string outputName = "probs"var outputChannels = 200;var outputBuilder = MachineLearning.createOutputBuilder();outputBuilder.setName(script.outputName);outputBuilder.setShape(new vec3(script.outputSize.x, script.outputSize.y, outputChannels));outputBuilder.setOutputMode(MachineLearning.OutputMode.Data);var outputPlaceholder = outputBuilder.build();
The output will be in the form of a Float32Array.
The output will be in the form of a Texture.
Types of output used by OutputPlaceholder.
Example