Remove abstract pre/postprocess from BaseModel

JakubGonera · JakubGonera · commit 59e2fbfd03c1 · 2025-03-10T12:36:30.000+01:00
diff --git a/android/src/main/java/com/swmansion/rnexecutorch/models/BaseModel.kt b/android/src/main/java/com/swmansion/rnexecutorch/models/BaseModel.kt
@@ -52,8 +52,4 @@ abstract class BaseModel<Input, Output>(
   }
 
   abstract fun runModel(input: Input): Output
-
-  protected abstract fun preprocess(input: Input): EValue
-
-  protected abstract fun postprocess(output: Array<EValue>): Output
 }
diff --git a/android/src/main/java/com/swmansion/rnexecutorch/models/StyleTransferModel.kt b/android/src/main/java/com/swmansion/rnexecutorch/models/StyleTransferModel.kt
@@ -20,13 +20,13 @@ class StyleTransferModel(
     return Size(height.toDouble(), width.toDouble())
   }
 
-  override fun preprocess(input: Mat): EValue {
+  fun preprocess(input: Mat): EValue {
     originalSize = input.size()
     Imgproc.resize(input, input, getModelImageSize())
     return ImageProcessor.matToEValue(input, module.getInputShape(0))
   }
 
-  override fun postprocess(output: Array<EValue>): Mat {
+  fun postprocess(output: Array<EValue>): Mat {
     val tensor = output[0].toTensor()
     val modelShape = getModelImageSize()
     val result = ImageProcessor.eValueToMat(tensor.dataAsFloatArray, modelShape.width.toInt(), modelShape.height.toInt())
diff --git a/android/src/main/java/com/swmansion/rnexecutorch/models/classification/ClassificationModel.kt b/android/src/main/java/com/swmansion/rnexecutorch/models/classification/ClassificationModel.kt
@@ -19,12 +19,12 @@ class ClassificationModel(
     return Size(height.toDouble(), width.toDouble())
   }
 
-  override fun preprocess(input: Mat): EValue {
+  fun preprocess(input: Mat): EValue {
     Imgproc.resize(input, input, getModelImageSize())
     return ImageProcessor.matToEValue(input, module.getInputShape(0))
   }
 
-  override fun postprocess(output: Array<EValue>): Map<String, Float> {
+  fun postprocess(output: Array<EValue>): Map<String, Float> {
     val tensor = output[0].toTensor()
     val probabilities = softmax(tensor.dataAsFloatArray.toTypedArray())
 
diff --git a/android/src/main/java/com/swmansion/rnexecutorch/models/objectDetection/SSDLiteLargeModel.kt b/android/src/main/java/com/swmansion/rnexecutorch/models/objectDetection/SSDLiteLargeModel.kt
@@ -29,7 +29,7 @@ class SSDLiteLargeModel(
     return Size(height.toDouble(), width.toDouble())
   }
 
-  override fun preprocess(input: Mat): EValue {
+  fun preprocess(input: Mat): EValue {
     this.widthRatio = (input.size().width / getModelImageSize().width).toFloat()
     this.heightRatio = (input.size().height / getModelImageSize().height).toFloat()
     Imgproc.resize(input, input, getModelImageSize())
@@ -42,7 +42,7 @@ class SSDLiteLargeModel(
     return postprocess(modelOutput)
   }
 
-  override fun postprocess(output: Array<EValue>): Array<Detection> {
+  fun postprocess(output: Array<EValue>): Array<Detection> {
     val scoresTensor = output[1].toTensor()
     val numel = scoresTensor.numel()
     val bboxes = output[0].toTensor().dataAsFloatArray
diff --git a/android/src/main/java/com/swmansion/rnexecutorch/models/ocr/Detector.kt b/android/src/main/java/com/swmansion/rnexecutorch/models/ocr/Detector.kt
@@ -25,7 +25,7 @@ class Detector(
     return modelImageSize
   }
 
-  override fun preprocess(input: Mat): EValue {
+  fun preprocess(input: Mat): EValue {
     originalSize = Size(input.cols().toDouble(), input.rows().toDouble())
     val resizedImage =
       ImageProcessor.resizeWithPadding(
@@ -42,7 +42,7 @@ class Detector(
     )
   }
 
-  override fun postprocess(output: Array<EValue>): List<OCRbBox> {
+  fun postprocess(output: Array<EValue>): List<OCRbBox> {
     val outputTensor = output[0].toTensor()
     val outputArray = outputTensor.dataAsFloatArray
     val modelImageSize = getModelImageSize()
diff --git a/android/src/main/java/com/swmansion/rnexecutorch/models/ocr/Recognizer.kt b/android/src/main/java/com/swmansion/rnexecutorch/models/ocr/Recognizer.kt
@@ -19,9 +19,9 @@ class Recognizer(
     return Size(height.toDouble(), width.toDouble())
   }
 
-  override fun preprocess(input: Mat): EValue = ImageProcessor.matToEValueGray(input)
+  fun preprocess(input: Mat): EValue = ImageProcessor.matToEValueGray(input)
 
-  override fun postprocess(output: Array<EValue>): Pair<List<Int>, Double> {
+  fun postprocess(output: Array<EValue>): Pair<List<Int>, Double> {
     val modelOutputHeight = getModelOutputSize().height.toInt()
     val tensor = output[0].toTensor().dataAsFloatArray
     val numElements = tensor.size
diff --git a/android/src/main/java/com/swmansion/rnexecutorch/models/ocr/VerticalDetector.kt b/android/src/main/java/com/swmansion/rnexecutorch/models/ocr/VerticalDetector.kt
@@ -26,7 +26,7 @@ class VerticalDetector(
     return modelImageSize
   }
 
-  override fun preprocess(input: Mat): EValue {
+  fun preprocess(input: Mat): EValue {
     originalSize = Size(input.cols().toDouble(), input.rows().toDouble())
     val resizedImage =
       ImageProcessor.resizeWithPadding(
@@ -43,7 +43,7 @@ class VerticalDetector(
     )
   }
 
-  override fun postprocess(output: Array<EValue>): List<OCRbBox> {
+  fun postprocess(output: Array<EValue>): List<OCRbBox> {
     val outputTensor = output[0].toTensor()
     val outputArray = outputTensor.dataAsFloatArray
     val modelImageSize = getModelImageSize()
diff --git a/android/src/main/java/com/swmansion/rnexecutorch/models/speechToText/BaseS2TDecoder.kt b/android/src/main/java/com/swmansion/rnexecutorch/models/speechToText/BaseS2TDecoder.kt
@@ -28,13 +28,13 @@ abstract class BaseS2TDecoder(
 
   abstract fun getInputShape(inputLength: Int): LongArray
 
-  override fun preprocess(input: ReadableArray): EValue {
+  fun preprocess(input: ReadableArray): EValue {
     val inputArray = input.getArray(0)!!
     val preprocessorInputShape = this.getInputShape(inputArray.size())
     return EValue.from(Tensor.fromBlob(createFloatArray(inputArray), preprocessorInputShape))
   }
 
-  override fun postprocess(output: Array<EValue>): Int {
+  fun postprocess(output: Array<EValue>): Int {
     TODO("Not yet implemented")
   }
 }
diff --git a/android/src/main/java/com/swmansion/rnexecutorch/models/speechToText/MoonshineEncoder.kt b/android/src/main/java/com/swmansion/rnexecutorch/models/speechToText/MoonshineEncoder.kt
@@ -14,13 +14,13 @@ class MoonshineEncoder(
 ) : BaseModel<ReadableArray, WritableArray>(reactApplicationContext) {
   override fun runModel(input: ReadableArray): WritableArray = this.postprocess(this.module.forward(this.preprocess(input)))
 
-  override fun preprocess(input: ReadableArray): EValue {
+  fun preprocess(input: ReadableArray): EValue {
     val size = input.size()
     val preprocessorInputShape = longArrayOf(1, size.toLong())
     return EValue.from(Tensor.fromBlob(createFloatArray(input), preprocessorInputShape))
   }
 
-  public override fun postprocess(output: Array<EValue>): WritableArray {
+  public fun postprocess(output: Array<EValue>): WritableArray {
     val outputWritableArray: WritableArray = Arguments.createArray()
     output[0].toTensor().dataAsFloatArray.map {
       outputWritableArray.pushDouble(
diff --git a/android/src/main/java/com/swmansion/rnexecutorch/models/speechToText/WhisperEncoder.kt b/android/src/main/java/com/swmansion/rnexecutorch/models/speechToText/WhisperEncoder.kt
@@ -24,7 +24,7 @@ class WhisperEncoder(
     return this.postprocess(hiddenState)
   }
 
-  override fun preprocess(input: ReadableArray): EValue {
+  fun preprocess(input: ReadableArray): EValue {
     val waveformFloatArray = ArrayUtils.createFloatArray(input)
 
     val stftResult = this.stft.fromWaveform(waveformFloatArray)
@@ -33,7 +33,7 @@ class WhisperEncoder(
     return EValue.from(inputTensor)
   }
 
-  public override fun postprocess(output: Array<EValue>): WritableArray {
+  public fun postprocess(output: Array<EValue>): WritableArray {
     val outputWritableArray: WritableArray = Arguments.createArray()
 
     output[0].toTensor().dataAsFloatArray.map {

Original file line number	Diff line number	Diff line change
`@@ -52,8 +52,4 @@ abstract class BaseModel<Input, Output>(`
`52`	`52`	`}`
`53`	`53`
`54`	`54`	`abstract fun runModel(input: Input): Output`
`55`		`-`
`56`		`- protected abstract fun preprocess(input: Input): EValue`
`57`		`-`
`58`		`- protected abstract fun postprocess(output: Array<EValue>): Output`
`59`	`55`	`}`
Original file line number	Diff line number	Diff line change
`@@ -20,13 +20,13 @@ class StyleTransferModel(`
`20`	`20`	`return Size(height.toDouble(), width.toDouble())`
`21`	`21`	`}`
`22`	`22`
`23`		`- override fun preprocess(input: Mat): EValue {`
	`23`	`+ fun preprocess(input: Mat): EValue {`
`24`	`24`	`originalSize = input.size()`
`25`	`25`	`Imgproc.resize(input, input, getModelImageSize())`
`26`	`26`	`return ImageProcessor.matToEValue(input, module.getInputShape(0))`
`27`	`27`	`}`
`28`	`28`
`29`		`- override fun postprocess(output: Array<EValue>): Mat {`
	`29`	`+ fun postprocess(output: Array<EValue>): Mat {`
`30`	`30`	`val tensor = output[0].toTensor()`
`31`	`31`	`val modelShape = getModelImageSize()`
`32`	`32`	`val result = ImageProcessor.eValueToMat(tensor.dataAsFloatArray, modelShape.width.toInt(), modelShape.height.toInt())`
Original file line number	Diff line number	Diff line change
`@@ -19,12 +19,12 @@ class ClassificationModel(`
`19`	`19`	`return Size(height.toDouble(), width.toDouble())`
`20`	`20`	`}`
`21`	`21`
`22`		`- override fun preprocess(input: Mat): EValue {`
	`22`	`+ fun preprocess(input: Mat): EValue {`
`23`	`23`	`Imgproc.resize(input, input, getModelImageSize())`
`24`	`24`	`return ImageProcessor.matToEValue(input, module.getInputShape(0))`
`25`	`25`	`}`
`26`	`26`
`27`		`- override fun postprocess(output: Array<EValue>): Map<String, Float> {`
	`27`	`+ fun postprocess(output: Array<EValue>): Map<String, Float> {`
`28`	`28`	`val tensor = output[0].toTensor()`
`29`	`29`	`val probabilities = softmax(tensor.dataAsFloatArray.toTypedArray())`
`30`	`30`
Original file line number	Diff line number	Diff line change
`@@ -25,7 +25,7 @@ class Detector(`
`25`	`25`	`return modelImageSize`
`26`	`26`	`}`
`27`	`27`
`28`		`- override fun preprocess(input: Mat): EValue {`
	`28`	`+ fun preprocess(input: Mat): EValue {`
`29`	`29`	`originalSize = Size(input.cols().toDouble(), input.rows().toDouble())`
`30`	`30`	`val resizedImage =`
`31`	`31`	`ImageProcessor.resizeWithPadding(`
`@@ -42,7 +42,7 @@ class Detector(`
`42`	`42`	`)`
`43`	`43`	`}`
`44`	`44`
`45`		`- override fun postprocess(output: Array<EValue>): List<OCRbBox> {`
	`45`	`+ fun postprocess(output: Array<EValue>): List<OCRbBox> {`
`46`	`46`	`val outputTensor = output[0].toTensor()`
`47`	`47`	`val outputArray = outputTensor.dataAsFloatArray`
`48`	`48`	`val modelImageSize = getModelImageSize()`
Original file line number	Diff line number	Diff line change
`@@ -26,7 +26,7 @@ class VerticalDetector(`
`26`	`26`	`return modelImageSize`
`27`	`27`	`}`
`28`	`28`
`29`		`- override fun preprocess(input: Mat): EValue {`
	`29`	`+ fun preprocess(input: Mat): EValue {`
`30`	`30`	`originalSize = Size(input.cols().toDouble(), input.rows().toDouble())`
`31`	`31`	`val resizedImage =`
`32`	`32`	`ImageProcessor.resizeWithPadding(`
`@@ -43,7 +43,7 @@ class VerticalDetector(`
`43`	`43`	`)`
`44`	`44`	`}`
`45`	`45`
`46`		`- override fun postprocess(output: Array<EValue>): List<OCRbBox> {`
	`46`	`+ fun postprocess(output: Array<EValue>): List<OCRbBox> {`
`47`	`47`	`val outputTensor = output[0].toTensor()`
`48`	`48`	`val outputArray = outputTensor.dataAsFloatArray`
`49`	`49`	`val modelImageSize = getModelImageSize()`
Original file line number	Diff line number	Diff line change
`@@ -28,13 +28,13 @@ abstract class BaseS2TDecoder(`
`28`	`28`
`29`	`29`	`abstract fun getInputShape(inputLength: Int): LongArray`
`30`	`30`
`31`		`- override fun preprocess(input: ReadableArray): EValue {`
	`31`	`+ fun preprocess(input: ReadableArray): EValue {`
`32`	`32`	`val inputArray = input.getArray(0)!!`
`33`	`33`	`val preprocessorInputShape = this.getInputShape(inputArray.size())`
`34`	`34`	`return EValue.from(Tensor.fromBlob(createFloatArray(inputArray), preprocessorInputShape))`
`35`	`35`	`}`
`36`	`36`
`37`		`- override fun postprocess(output: Array<EValue>): Int {`
	`37`	`+ fun postprocess(output: Array<EValue>): Int {`
`38`	`38`	`TODO("Not yet implemented")`
`39`	`39`	`}`
`40`	`40`	`}`
Original file line number	Diff line number	Diff line change
`@@ -24,7 +24,7 @@ class WhisperEncoder(`
`24`	`24`	`return this.postprocess(hiddenState)`
`25`	`25`	`}`
`26`	`26`
`27`		`- override fun preprocess(input: ReadableArray): EValue {`
	`27`	`+ fun preprocess(input: ReadableArray): EValue {`
`28`	`28`	`val waveformFloatArray = ArrayUtils.createFloatArray(input)`
`29`	`29`
`30`	`30`	`val stftResult = this.stft.fromWaveform(waveformFloatArray)`
`@@ -33,7 +33,7 @@ class WhisperEncoder(`
`33`	`33`	`return EValue.from(inputTensor)`
`34`	`34`	`}`
`35`	`35`
`36`		`- public override fun postprocess(output: Array<EValue>): WritableArray {`
	`36`	`+ public fun postprocess(output: Array<EValue>): WritableArray {`
`37`	`37`	`val outputWritableArray: WritableArray = Arguments.createArray()`
`38`	`38`
`39`	`39`	`output[0].toTensor().dataAsFloatArray.map {`