diff --git a/entry/src/main/ets/MainAbility/pages/FashionMnist.ets b/entry/src/main/ets/MainAbility/pages/FashionMnist.ets new file mode 100644 index 0000000..c25f48c --- /dev/null +++ b/entry/src/main/ets/MainAbility/pages/FashionMnist.ets @@ -0,0 +1,112 @@ +import * as tf from "@ohos/tfjs" +import router from '@system.router'; + +let model; +/* https://colab.research.google.com/drive/1s5TM5Fn9If1co8drd4Jf7YvY6Zc5OHBn?usp=sharing + Model is trained in Colab and is converted to json format using tfjs_converter +*/ +// This model can Identify if the input image contains the following +const fashion_mnist_labels = ["T-shirt/top", // index 0 + "Trouser", // index 1 + "Pullover", // index 2 + "Dress", // index 3 + "Coat", // index 4 + "Sandal", // index 5 + "Shirt", // index 6 + "Sneaker", // index 7 + "Bag", // index 8 + "Ankle boot"] // index 9 + +@Entry +@Component +struct MobileNet { + @State message: string = 'Fashion Mnist' + @State digit: string = 'Predicted digit: ' + @State label: string = 'Predicted label: ' + build() { + Row() { + Column() { + Text(this.message) + .fontSize(50) + .fontWeight(FontWeight.Bold) + Row(){ + Button("Load") + .onClick(async() => { + + console.log("Started loading the model"); + try { + model = await tf.loadGraphModel('/models/fashion'); + }catch(err){ + console.log("Error: "+ err) + } + console.log("Loaded model") + + }).margin('25px') + } + Row() { + Image($r("app.media.pullover")) + .objectFit(ImageFit.Cover) + .width(100) + .height(100) + .margin('25px') + .onClick(async() => { + + const digit = tf.tensor([[[0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0]], [[0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0]], [[0.0], [0.0], [0.0], [0.0], [0.0], 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[0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0]], [[0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0]], [[0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0]]]).reshape([-1,28,28,1]) + console.log("Prediction Started") + const pred = await model.predict(digit) as tf.Tensor; + console.log("Predict Complete") + console.log('pred: ' + pred.dataSync()) + + try { + const index = await pred.as1D().argMax() as tf.Tensor; + console.log("Predicted Digit: " + index.dataSync()) + this.digit = "Prediceted Digit: " + index.dataSync() + this.label = "Predicted Label" + fashion_mnist_labels[index.dataSync()[0]] + } + catch(err){ + console.log("Error: " + err) + } + }) + + } + Text(this.digit) + .fontSize(25) + .fontWeight(FontWeight.Bold) + Text(this.label) + .fontSize(25) + .fontWeight(FontWeight.Bold) + Button("Back") + .onClick(()=>{ + router.back(); + }) + .margin(40) + } + .width('100%') + } + .height('100%') + } +} diff --git a/entry/src/main/ets/MainAbility/pages/index.ets b/entry/src/main/ets/MainAbility/pages/index.ets index 75ecfa0..c8d07d9 100644 --- a/entry/src/main/ets/MainAbility/pages/index.ets +++ b/entry/src/main/ets/MainAbility/pages/index.ets @@ -211,10 +211,14 @@ struct Index { .onClick(() => { router.push({ uri: 'pages/SelfieSegmentation' }) }).margin('25px') - Button("hand detection") // Load pretrained hand detection model + Button("hand detection") // Load pretrained hand detection model .onClick(() => { router.push({ uri: 'pages/handpose' }) }).margin('25px') + Button("Fashion Mnist") // Load pretrained Fashion Mnist model + .onClick(() => { + router.push({ uri: 'pages/FashionMnist' }) + }).margin('25px') } .width('100%') } diff --git a/entry/src/main/resources/base/media/pullover.jpg b/entry/src/main/resources/base/media/pullover.jpg new file mode 100644 index 0000000..f3eaa4c Binary files /dev/null and b/entry/src/main/resources/base/media/pullover.jpg differ diff --git a/entry/src/main/resources/base/media/tshirt.png b/entry/src/main/resources/base/media/tshirt.png new file mode 100644 index 0000000..b7e9930 Binary files /dev/null and b/entry/src/main/resources/base/media/tshirt.png differ diff --git a/tfjs-core/src/io/res_system.ets b/tfjs-core/src/io/res_system.ets index 0583d1d..4c5aa63 100644 --- a/tfjs-core/src/io/res_system.ets +++ b/tfjs-core/src/io/res_system.ets @@ -209,6 +209,9 @@ export class NodeFileSystem implements IOHandler { else if (path==('/handpose')){ myData = await import('@ohos/tfjs-models/models/handpose/model.json'); } + else if(path==('/fashion')){ + myData = await import('@ohos/tfjs-models/models/fashion/model.json'); + } console.info("myData " + myData); let data = JSON.parse((JSON.stringify(myData))); console.info(data.format); @@ -389,6 +392,37 @@ export class NodeFileSystem implements IOHandler { }) }); } + else if(path ==('/fashion')){ + import('@ohos/tfjs-models/models/fashion/model.json').then(({default: myData}) => { + console.info("myData " + myData); + Promise.resolve(JSON.parse((JSON.stringify(myData)))) + .then(data => { + /*console.info(data); + console.info(data.modelTopology);*/ + console.info(data.format); + + const modelTopology = data.modelTopology; + if (modelTopology == null) { + console.info("myData modelTopology null "); + reject(new Error(`modelTopology field is missing from file `)); + return; + } + const weightsManifest = data.weightsManifest; + if (weightsManifest == null) { + console.info("myData weightsManifest null "); + reject(new Error(`weightManifest field is missing from file `)); + return; + } + /*const modelArtifactsPromise = getModelArtifactsForJSON( + data, (weightsManifest) => this.loadWeights(weightsManifest)); + resolve(modelArtifactsPromise);*/ + + return getModelArtifactsForJSON( + data, + (weightsManifest) => this.loadWeights(weightsManifest, "")); + }) + }); + } }); } @@ -453,7 +487,10 @@ export class NodeFileSystem implements IOHandler { } else if (path==('/handpose')){ jsonOfWeights = await import('@ohos/tfjs-models/models/handpose/weights.json'); - } + } + else if(path==('/fashion')){ + jsonOfWeights = await import('@ohos/tfjs-models/models/fashion/weights.json'); + } let jsonObj = JSON.parse(JSON.stringify(jsonOfWeights)) let jsonArray = [] for (var item in jsonObj) { diff --git a/tfjs-models/models/fashion/model.json b/tfjs-models/models/fashion/model.json new file mode 100644 index 0000000..11de55b --- /dev/null +++ b/tfjs-models/models/fashion/model.json @@ -0,0 +1 @@ +{"format": "graph-model", "generatedBy": "2.8.2", "convertedBy": "TensorFlow.js Converter v1.7.0", "signature": {"inputs": {"conv2d_22_input": {"name": "conv2d_22_input:0", "dtype": "DT_FLOAT", "tensorShape": {"dim": [{"size": "-1"}, {"size": "28"}, {"size": "28"}, {"size": "1"}]}}}, "outputs": {"activation_35": {"name": "Identity:0", "dtype": "DT_FLOAT", "tensorShape": {"dim": [{"size": "-1"}, {"size": "10"}]}}}}, "modelTopology": {"node": [{"name": "StatefulPartitionedCall/sequential_6/flatten_6/Const", "op": "Const", "attr": {"dtype": {"type": "DT_INT32"}, "value": {"tensor": {"dtype": "DT_INT32", "tensorShape": {"dim": [{"size": "2"}]}}}}}, {"name": "StatefulPartitionedCall/sequential_6/dense_12/MatMul/ReadVariableOp", "op": "Const", "attr": {"dtype": {"type": "DT_FLOAT"}, "value": {"tensor": {"dtype": "DT_FLOAT", "tensorShape": {"dim": [{"size": "1024"}, {"size": "512"}]}}}}}, {"name": "StatefulPartitionedCall/sequential_6/dense_12/BiasAdd/ReadVariableOp", "op": "Const", "attr": {"dtype": {"type": "DT_FLOAT"}, "value": {"tensor": {"dtype": "DT_FLOAT", "tensorShape": {"dim": [{"size": "512"}]}}}}}, {"name": 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