This repository has been archived by the owner on Apr 8, 2023. It is now read-only.
-
Notifications
You must be signed in to change notification settings - Fork 343
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
Showing
47 changed files
with
1,028 additions
and
883 deletions.
There are no files selected for viewing
Some generated files are not rendered by default. Learn more about how customized files appear on GitHub.
Oops, something went wrong.
Some generated files are not rendered by default. Learn more about how customized files appear on GitHub.
Oops, something went wrong.
File renamed without changes.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Empty file.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
22 changes: 22 additions & 0 deletions
22
OpenNSFW/src/androidTest/java/com/zwy/opennsfw/ExampleInstrumentedTest.kt
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,22 @@ | ||
| package com.zwy.opennsfw | ||
|
|
||
| import android.support.test.InstrumentationRegistry | ||
| import android.support.test.runner.AndroidJUnit4 | ||
| import org.junit.Assert.assertEquals | ||
| import org.junit.Test | ||
| import org.junit.runner.RunWith | ||
|
|
||
| /** | ||
| * Instrumented test, which will execute on an Android device. | ||
| * | ||
| * See [testing documentation](http://d.android.com/tools/testing). | ||
| */ | ||
| @RunWith(AndroidJUnit4::class) | ||
| class ExampleInstrumentedTest { | ||
| @Test | ||
| fun useAppContext() { | ||
| // Context of the app under test. | ||
| val appContext = InstrumentationRegistry.getInstrumentation().targetContext | ||
| assertEquals("com.zwy.opennsfw.test", appContext.packageName) | ||
| } | ||
| } |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,2 @@ | ||
| <manifest | ||
| package="com.zwy.opennsfw"/> |
File renamed without changes.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,205 @@ | ||
| //package com.zwy.opennsfw | ||
| // | ||
| //import android.content.Context | ||
| //import android.content.res.AssetManager | ||
| //import android.graphics.Bitmap | ||
| //import android.graphics.Color | ||
| //import android.os.SystemClock | ||
| //import android.util.Log | ||
| //import org.tensorflow.lite.Interpreter | ||
| //import org.tensorflow.lite.gpu.GpuDelegate | ||
| //import java.io.FileInputStream | ||
| //import java.lang.Math.max | ||
| //import java.nio.ByteBuffer | ||
| //import java.nio.ByteOrder | ||
| //import java.nio.MappedByteBuffer | ||
| //import java.nio.channels.FileChannel | ||
| // | ||
| //class Classifier | ||
| //private constructor(assetManager: AssetManager, isGPU: Boolean?, numThreads: Int) { | ||
| // | ||
| // /** | ||
| // * 数据宽高 | ||
| // */ | ||
| // private val INPUT_WIDTH = 224 | ||
| // | ||
| // /** | ||
| // * 数据宽高 | ||
| // */ | ||
| // private val INPUT_HEIGHT = 224 | ||
| // | ||
| // /** | ||
| // * 通道 | ||
| // */ | ||
| // private val BYTES_PER_CHANNEL_NUM = 4 | ||
| // | ||
| // /** | ||
| // * Resize后的数据源 | ||
| // */ | ||
| // private val intValues = IntArray(INPUT_WIDTH * INPUT_HEIGHT) | ||
| // | ||
| // /** | ||
| // * 载入模型的客户端 | ||
| // */ | ||
| // private var tfliteModel: MappedByteBuffer? = null | ||
| // | ||
| // /** | ||
| // * GPU代理 | ||
| // */ | ||
| // private var gpuDelegate: GpuDelegate? = null | ||
| // | ||
| // /** | ||
| // * Tensorflow Lite | ||
| // */ | ||
| // private var tflite: Interpreter? = null | ||
| // | ||
| // /** | ||
| // * 喂入模型的最终数据源 | ||
| // */ | ||
| // private val imgData: ByteBuffer? | ||
| // | ||
| // | ||
| // init { | ||
| // tfliteModel = loadModelFile(assetManager) | ||
| // val tfliteOptions = Interpreter.Options() | ||
| // if (isGPU == true) { | ||
| // gpuDelegate = GpuDelegate() | ||
| // tfliteOptions.addDelegate(gpuDelegate) | ||
| // } | ||
| // tfliteOptions.setNumThreads(numThreads) | ||
| // tflite = Interpreter(tfliteModel!!, tfliteOptions) | ||
| // | ||
| // val tensor = tflite!!.getInputTensor(tflite!!.getInputIndex("input")) | ||
| // val stringBuilder = (" \n" | ||
| // + "dataType : " + | ||
| // tensor.dataType() + | ||
| // "\n" + | ||
| // "numBytes : " + | ||
| // tensor.numBytes() + | ||
| // "\n" + | ||
| // "numDimensions : " + | ||
| // tensor.numDimensions() + | ||
| // "\n" + | ||
| // "numElements : " + | ||
| // tensor.numElements() + | ||
| // "\n" + | ||
| // "shape : " + | ||
| // tensor.shape().size) | ||
| // Log.d(TAG, stringBuilder) | ||
| // | ||
| // imgData = ByteBuffer.allocateDirect( | ||
| // DIM_BATCH_SIZE | ||
| // * INPUT_WIDTH | ||
| // * INPUT_HEIGHT | ||
| // * DIM_PIXEL_SIZE | ||
| // * BYTES_PER_CHANNEL_NUM | ||
| // ) | ||
| // | ||
| // imgData!!.order(ByteOrder.LITTLE_ENDIAN) | ||
| // Log.d(TAG, "Tensorflow Lite Image Classifier Initialization Success.") | ||
| // } | ||
| // | ||
| // /** | ||
| // * Memory-map the model file in Assets. | ||
| // */ | ||
| // private fun loadModelFile(assetManager: AssetManager): MappedByteBuffer { | ||
| // val context:Context | ||
| // val fileDescriptor = assetManager.openFd("nsfw.tflite") | ||
| // val inputStream = FileInputStream(fileDescriptor.fileDescriptor) | ||
| // val fileChannel = inputStream.channel | ||
| // val startOffset = fileDescriptor.startOffset | ||
| // val declaredLength = fileDescriptor.declaredLength | ||
| // return fileChannel.map(FileChannel.MapMode.READ_ONLY, startOffset, declaredLength) | ||
| // } | ||
| // | ||
| // | ||
| // /** | ||
| // * Writes Image data into a `ByteBuffer`. | ||
| // */ | ||
| // private fun convertBitmapToByteBuffer(bitmap_: Bitmap) { | ||
| // if (imgData == null || bitmap_ == null) { | ||
| // return | ||
| // } | ||
| // imgData.rewind() | ||
| // val W = bitmap_.width | ||
| // val H = bitmap_.height | ||
| // | ||
| // val w_off = max((W - INPUT_WIDTH) / 2, 0) | ||
| // val h_off = max((H - INPUT_HEIGHT) / 2, 0) | ||
| // | ||
| // //把每个像素的颜色值转为int 存入intValues | ||
| // bitmap_.getPixels(intValues, 0, INPUT_WIDTH, h_off, w_off, INPUT_WIDTH, INPUT_HEIGHT) | ||
| // // Convert the image to floating point. | ||
| // val startTime = SystemClock.uptimeMillis() | ||
| // for (color in intValues) { | ||
| // val r1 = Color.red(color) | ||
| // val g1 = Color.green(color) | ||
| // val b1 = Color.blue(color) | ||
| // | ||
| // val rr1 = r1 - 123 | ||
| // val gg1 = g1 - 117 | ||
| // val bb1 = b1 - 104 | ||
| // | ||
| // imgData.putFloat(bb1.toFloat()) | ||
| // imgData.putFloat(gg1.toFloat()) | ||
| // imgData.putFloat(rr1.toFloat()) | ||
| // } | ||
| // val endTime = SystemClock.uptimeMillis() | ||
| // Log.d(TAG, "Timecost to put values into ByteBuffer: " + (endTime - startTime) + "ms") | ||
| // } | ||
| // | ||
| // fun run(bitmap: Bitmap): NsfwBean { | ||
| // | ||
| // val bitmap_256 = Bitmap.createScaledBitmap(bitmap, 256, 256, true) | ||
| // | ||
| // //Writes image data into byteBuffer | ||
| // convertBitmapToByteBuffer(bitmap_256) | ||
| // | ||
| // val startTime = SystemClock.uptimeMillis() | ||
| // // out | ||
| // val outArray = Array(1) { FloatArray(2) } | ||
| // | ||
| // tflite!!.run(imgData, outArray) | ||
| // | ||
| // val endTime = SystemClock.uptimeMillis() | ||
| // | ||
| // Log.d(TAG, "SFW score :" + outArray[0][0] + ",NSFW score :" + outArray[0][1]) | ||
| // Log.d(TAG, "Timecost to run model inference: " + (endTime - startTime) + "ms") | ||
| // return NsfwBean(outArray[0][0], outArray[0][1]) | ||
| // } | ||
| // | ||
| // /** | ||
| // * Closes the interpreter and model to release resources. | ||
| // */ | ||
| // fun close() { | ||
| // if (tflite != null) { | ||
| // tflite!!.close() | ||
| // tflite = null | ||
| // Log.d(TAG, "Tensorflow Lite Image Classifier close.") | ||
| // } | ||
| // if (gpuDelegate != null) { | ||
| // gpuDelegate!!.close() | ||
| // Log.d(TAG, "Tensorflow Lite Image gpuDelegate close.") | ||
| // gpuDelegate = null | ||
| // } | ||
| // tfliteModel = null | ||
| // Log.d(TAG, "Tensorflow Lite destroyed.") | ||
| // } | ||
| // | ||
| // companion object { | ||
| // | ||
| // val TAG = "open_nsfw_android" | ||
| // /** | ||
| // * Dimensions of inputs. | ||
| // */ | ||
| // private val DIM_BATCH_SIZE = 1 | ||
| // | ||
| // private val DIM_PIXEL_SIZE = 3 | ||
| // | ||
| // fun create(assetManager: AssetManager, isAddGpuDelegate: Boolean?, numThreads: Int): Classifier { | ||
| // return Classifier(assetManager, isAddGpuDelegate!!, numThreads) | ||
| // } | ||
| // | ||
| // } | ||
| // | ||
| //} |
Oops, something went wrong.