public void LookupFalseTest() { GroundTruth.CreateGroundTruthLookup(); string[] imageArray = GroundTruth.GetImageKeys(); bool isHealthy = GroundTruth.Lookup("DSC00041.JPG"); Assert.IsFalse(isHealthy); }
public void GetImageKeysTest() { GroundTruth.CreateGroundTruthLookup(); string[] imageArray = GroundTruth.GetImageKeys(); int numEntries = imageArray.Length; int numPictures = 1787; Assert.IsTrue(numEntries == numPictures); }
/// <summary> /// This is the starting point of the server program. Here we assign the app a configuration and initialize Machine Learning engines. /// </summary> /// <param name="configuration">An IConfiguration object</param> public Startup(IConfiguration configuration) { Configuration = configuration; // Set Firebase URL: RestfulDBConnection.FIREBASE_URL = Configuration["FirebaseURL"]; // Initialize Machine Learning Components: MLModel.CreatePredictionEngine(); GroundTruth.CreateGroundTruthLookup(); // Get the Machine Learning Warmed Up: MLModel.Predict("https://firebasestorage.googleapis.com/v0/b/agricultureai-15ce0.appspot.com/o/DSC00025.JPG?alt=media"); }
public void getNumTrueAndFalse() { int numTrue = 0; int numFalse = 0; GroundTruth.CreateGroundTruthLookup(); string[] imageArray = GroundTruth.GetImageKeys(); int numImages = imageArray.Length; for (int i = 0; i < imageArray.Length; i++) { if (GroundTruth.Lookup((imageArray[i]).ToString()) == true) { numTrue++; } else { numFalse++; } } Assert.IsTrue((numFalse + numTrue) == numImages); }