[workload] Fixed some errors when loading model files of Super Resolu…

…tion, Emotion Analysis and Facial Landmark Detection examples.
intel · Oct 9, 2019 · 84355a7 · 84355a7
1 parent 95ce8d8
commit 84355a7
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Showing 4 changed files with 20 additions and 14 deletions.
diff --git a/workload/resources/main.js b/workload/resources/main.js
@@ -9,7 +9,7 @@ const BenchmarkClass = {
 };
 
 async function main() {
-  let ctx = showCanvasElement.getContext("2d");  
+  let ctx = showCanvasElement.getContext("2d");
   ctx.drawImage(imageElement, 0, 0);
   inputElement.setAttribute('disabled', true);
   pickBtnElement.setAttribute('class', 'btn btn-primary disabled');
@@ -31,7 +31,7 @@ async function main() {
         let selectedOpt = preferSelectElement.options[preferSelectElement.selectedIndex];
         let backendName = configuration[key];
         if (configuration[key].indexOf('WebNN') === 0) {
-          backendName += ` + ${getNativeAPI(selectedOpt.value)}(${selectedOpt.text})`;
+          backendName += ` (Preference: ${selectedOpt.text})`;
         }
         logger.log(`${key.padStart(12)}: ${backendName}`);
       } else {

diff --git a/workload/resources/utils.js b/workload/resources/utils.js
@@ -146,7 +146,7 @@ async function loadModelAndLabels(model, label=null) {
     arrayBuffer = await this.loadUrl(url + model, true);
   }
   bytes = new Uint8Array(arrayBuffer);
-  if (label.toLowerCase().startsWith("https://") || label.toLowerCase().startsWith("http://")) {
+  if (label != null && (label.toLowerCase().startsWith("https://") || label.toLowerCase().startsWith("http://"))) {
     text = await this.loadUrl(label);
   } else {
     text = label ? await this.loadUrl(url + label) : null;

diff --git a/workload/resources/utils_ea.js b/workload/resources/utils_ea.js
@@ -4,7 +4,7 @@ class EABenchmark extends Benchmark {
     super(...arguments);
     this.faceDetector = null;
     this.modelName = modelName;
-    this.modelInfoDict = getModelInfoDict(emotionAnalysisModels, 'Simple CNN 7(TFlite)');
+    this.modelInfoDict = getModelInfoDict(emotionAnalysisModels, 'Simple CNN 7 (TFlite)');
     this.model = null;
     this.inputTensor = null;
     this.inputSize = null;
@@ -18,18 +18,21 @@ class EABenchmark extends Benchmark {
     let model = faceDetectionModels.filter(f => f.modelName == this.modelName);
     inputCanvas.setAttribute("width", model[0].inputSize[1]);
     inputCanvas.setAttribute("height", model[0].inputSize[0]);
-    model[0].modelFile = '../examples' + model[0].modelFile.slice(2);
+    let modelFile = model[0].modelFile;
+    if (!modelFile.toLowerCase().startsWith("https://") && !modelFile.toLowerCase().startsWith("http://")) {
+      model[0].modelFile = '../examples/util/' + model[0].modelFile;
+    }
     this.faceDetector = new FaceDetecor(inputCanvas);
     await this.faceDetector.loadModel(model[0]);
     await this.faceDetector.init(this.backend.replace('WebNN', 'WebML'), preferSelect.value);
-    model[0].modelFile = '..' + model[0].modelFile.slice(11);
+    model[0].modelFile = modelFile;
   }
 
   async getFaceDetectResult() {
     let detectResult = await this.faceDetector.getFaceBoxes(imageElement);
     return detectResult;
   }
-  
+
   async setInputOutput(box) {
     let inputCanvas = document.createElement('canvas');
     let width = this.modelInfoDict.inputSize[1];
@@ -45,8 +48,8 @@ class EABenchmark extends Benchmark {
     inputCanvas.setAttribute("width", width);
     inputCanvas.setAttribute("height", height);
     let canvasContext = inputCanvas.getContext('2d');
-    canvasContext.drawImage(imageElement, box[0], box[2], 
-                            box[1] - box[0], box[3] - box[2], 0, 0, 
+    canvasContext.drawImage(imageElement, box[0], box[2],
+                            box[1] - box[0], box[3] - box[2], 0, 0,
                             width, height);
     let pixels = canvasContext.getImageData(0, 0, width, height).data;
     if (norm) {
@@ -143,7 +146,7 @@ class EABenchmark extends Benchmark {
     // drawImage
     let ctx = canvas.getContext('2d');
     ctx.drawImage(image, 0, 0, canvas.width, canvas.height);
-  
+
     // drawFaceBox
     face_boxes.forEach((box, i) => {
       let xmin = box[0] / image.height * canvas.height;

diff --git a/workload/resources/utils_fld.js b/workload/resources/utils_fld.js
@@ -17,11 +17,14 @@ class FLDBenchmark extends Benchmark {
     let model = faceDetectionModels.filter(f => f.modelName == this.modelName);
     inputCanvas.setAttribute("width", model[0].inputSize[1]);
     inputCanvas.setAttribute("height", model[0].inputSize[0]);
-    model[0].modelFile = '../examples' + model[0].modelFile.slice(2);
+    let modelFile = model[0].modelFile;
+    if (!modelFile.toLowerCase().startsWith("https://") && !modelFile.toLowerCase().startsWith("http://")) {
+       model[0].modelFile = '../examples/util/' + model[0].modelFile;
+    }
     this.faceDetector = new FaceDetecor(inputCanvas);
     await this.faceDetector.loadModel(model[0]);
     await this.faceDetector.init(this.backend.replace('WebNN', 'WebML'), preferSelect.value);
-    model[0].modelFile = '..' + model[0].modelFile.slice(11);
+    model[0].modelFile = modelFile;
   }
 
   async getFaceDetectResult() {
@@ -46,8 +49,8 @@ class FLDBenchmark extends Benchmark {
     inputCanvas.setAttribute("width", width);
     inputCanvas.setAttribute("height", height);
     let canvasContext = inputCanvas.getContext('2d');
-    canvasContext.drawImage(imageElement, box[0], box[2], 
-                            box[1]-box[0], box[3]-box[2], 0, 0, 
+    canvasContext.drawImage(imageElement, box[0], box[2],
+                            box[1]-box[0], box[3]-box[2], 0, 0,
                             inputCanvas.width,
                             inputCanvas.height);
     let pixels = canvasContext.getImageData(0, 0, width, height).data;