fix json parse bug in neuralNetworkData loadData

src/NeuralNetwork/NeuralNetwork.js

@@ -206,7 +206,9 @@ class NeuralNetwork {
     if (filesOrPath instanceof FileList) {
       const files = Array.from(filesOrPath);
       // find the correct files
-      const model = files.find((file) => file.name.includes(".json") && !file.name.includes("_meta"));
+      const model = files.find(
+        (file) => file.name.includes(".json") && !file.name.includes("_meta")
+      );
       const weights = files.find((file) => file.name.includes(".bin"));
       // load the model
       this.model = await tf.loadLayersModel(
@@ -218,7 +220,7 @@ class NeuralNetwork {
           // Override the weights path from the JSON weightsManifest
           weightUrlConverter: (weightFileName) => {
             return filesOrPath.weights || weightFileName;
-          }
+          },
         })
       );
     } else {

src/NeuralNetwork/NeuralNetworkData.js

@@ -1,7 +1,7 @@
 import * as tf from "@tensorflow/tfjs";
 import axios from "axios";
 import { saveBlob } from "../utils/io";
-import modelLoader from '../utils/modelLoader';
+import modelLoader from "../utils/modelLoader";
 import nnUtils from "./NeuralNetworkUtils";
 
 class NeuralNetworkData {
@@ -532,7 +532,6 @@ class NeuralNetworkData {
    */
   async loadDataFromUrl(dataUrl, inputs, outputs) {
     try {
-
       if (dataUrl.endsWith(".csv")) {
         await this.loadCSV(dataUrl, inputs, outputs);
       } else if (dataUrl.endsWith(".json")) {
@@ -643,23 +642,21 @@ class NeuralNetworkData {
           );
         }
       } else {
-        loadedData = await axios.get(filesOrPath, { responseType: "text" });
-        const text = JSON.stringify(loadedData.data);
-        if (nnUtils.isJsonOrString(text)) {
-          loadedData = JSON.parse(text);
+        let response = await axios.get(filesOrPath, { responseType: "text" });
+
+        if (nnUtils.isJsonOrString(response.data)) {
+          loadedData = JSON.parse(response.data);
         } else {
-          console.log(
-            "Whoops! something went wrong. Either this kind of data is not supported yet or there is an issue with .loadData"
+          console.error(
+            "🟪 ml5.js error: `NeuralNetwork.loadData` only accepts JSON data."
           );
         }
       }
-
       this.data.raw = this.findEntries(loadedData);
-
       // check if a data or entries property exists
       if (!this.data.raw.length > 0) {
-        console.log(
-          'data must be a json object containing an array called "data" '
+        console.error(
+          "🟪 ml5.js error: `NeuralNetwork.loadData` only accepts JSON objects with a 'data' property."
         );
       }
     } catch (error) {
@@ -716,7 +713,7 @@ class NeuralNetworkData {
         file.name.includes("_meta.json")
       );
       if (!file) {
-        console.warn('no model_meta.json file found in FileList');
+        console.warn("no model_meta.json file found in FileList");
         return;
       }
       const text = await file.text();

src/NeuralNetwork/index.js

@@ -1,7 +1,10 @@
 import * as tf from "@tensorflow/tfjs";
 import callCallback from "../utils/callcallback";
 import handleArguments from "../utils/handleArguments";
-import { imgToPixelArray, isInstanceOfSupportedElement, } from "../utils/imageUtilities";
+import {
+  imgToPixelArray,
+  isInstanceOfSupportedElement,
+} from "../utils/imageUtilities";
 import NeuralNetwork from "./NeuralNetwork";
 import NeuralNetworkData from "./NeuralNetworkData";
 
@@ -22,7 +25,6 @@ const DEFAULTS = {
 };
 class DiyNeuralNetwork {
   constructor(options, callback) {
-
     // Is there a better way to handle a different
     // default learning rate for image classification tasks?
     if (options.task === "imageClassification") {
@@ -227,11 +229,7 @@ class DiyNeuralNetwork {
   async loadDataFromUrl() {
     const { dataUrl, inputs, outputs } = this.options;
 
-    await this.neuralNetworkData.loadDataFromUrl(
-      dataUrl,
-      inputs,
-      outputs
-    );
+    await this.neuralNetworkData.loadDataFromUrl(dataUrl, inputs, outputs);
 
     // once the data are loaded, create the metadata
     // and prep the data for training
@@ -512,7 +510,10 @@ class DiyNeuralNetwork {
       finishedTrainingCb = optionsOrCallback;
     }
 
-    return callCallback(this.trainInternal(options, whileTrainingCb), finishedTrainingCb);
+    return callCallback(
+      this.trainInternal(options, whileTrainingCb),
+      finishedTrainingCb
+    );
   }
 
   /**
@@ -579,9 +580,7 @@ class DiyNeuralNetwork {
     // then use those to create your architecture
     if (!this.neuralNetwork.isLayered) {
       // TODO: don't update this.options.layers - Linda
-      this.options.layers = this.createNetworkLayers(
-        this.options.layers
-      );
+      this.options.layers = this.createNetworkLayers(this.options.layers);
     }
 
     // if the model does not have any layers defined yet
@@ -1150,7 +1149,10 @@ class DiyNeuralNetwork {
    */
   saveData(name, callback) {
     const args = handleArguments(name, callback);
-    return callCallback(this.neuralNetworkData.saveData(args.name), args.callback);
+    return callCallback(
+      this.neuralNetworkData.saveData(args.name),
+      args.callback
+    );
   }
 
   /**
@@ -1182,13 +1184,16 @@ class DiyNeuralNetwork {
    */
   async save(name, callback) {
     const args = handleArguments(name, callback);
-    const modelName = args.string || 'model';
+    const modelName = args.string || "model";
 
     // save the model
-    return callCallback(Promise.all([
-      this.neuralNetwork.save(modelName),
-      this.neuralNetworkData.saveMeta(modelName)
-    ]), args.callback);
+    return callCallback(
+      Promise.all([
+        this.neuralNetwork.save(modelName),
+        this.neuralNetworkData.saveMeta(modelName),
+      ]),
+      args.callback
+    );
   }
 
   /**
@@ -1200,10 +1205,13 @@ class DiyNeuralNetwork {
    * @return {Promise<void[]>}
    */
   async load(filesOrPath, callback) {
-    return callCallback(Promise.all([
-      this.neuralNetwork.load(filesOrPath),
-      this.neuralNetworkData.loadMeta(filesOrPath)
-    ]), callback);
+    return callCallback(
+      Promise.all([
+        this.neuralNetwork.load(filesOrPath),
+        this.neuralNetworkData.loadMeta(filesOrPath),
+      ]),
+      callback
+    );
   }
 
   /**