def main():
sensorName = "SKYCAM"
dateTimeNow = datetime.datetime.now()
subFolder = mSR.getWritePathSnaps(sensorName, dateTimeNow)
onboardCapture = True
try:
currentImage, imagePath = mSCR.getSnapShotXU4(subFolder)
start = time.time()
modelName = 'naiveBayesModel.sav'
oneDImage, imageShape = mSCR.generateFeatures(currentImage, imagePath)
print("Loading Classifier")
loadedModel = pickle.load(open(modelName, 'rb'))
print("Done Loading")
predictionBinary, prediction = mSCR.getPredictionMatrix(
loadedModel, oneDImage)
print("Writing Resulting Images ...")
binaryImage = mSCR.writeBinaryImageXU4(predictionBinary, imageShape,
imagePath, onboardCapture)
sensorDictionary = mSCR.getResultsXU4(currentImage, binaryImage,
predictionBinary, prediction,
imagePath, dateTimeNow)
mSR.sensorFinisher(dateTimeNow, sensorName, sensorDictionary)
mSCR.timeTaken("Preiction time is ", start)
except:
print("TRY AGAIN")
def MCAMWrite(inputImage,imagePath,dateTime):
inputImage_RGB = inputImage
inputImage_HSV = mpclr.rgb_to_hsv(inputImage)
RGB_for_LAB = io.imread(imagePath)
inputImage_LAB = color.rgb2lab(RGB_for_LAB)
Image_Array_RGB = np.array(inputImage_RGB)
Image_Array_HSV = np.array(inputImage_HSV)
Image_Array_LAB = np.array(inputImage_LAB)
# Record the original shape
Image_Shape = Image_Array_RGB.shape
# Make a 1-dimensional view of arrays
One_D_Image_Red = np.transpose(np.matrix(Image_Array_RGB[:, :, 0].ravel()))
One_D_Image_Green = np.transpose(np.matrix(Image_Array_RGB[:, :, 1].ravel()))
One_D_Image_Blue = np.transpose(np.matrix(Image_Array_RGB[:, :, 2].ravel()))
# Recasting to support negative integers
One_D_Image_Red = One_D_Image_Red.astype(np.int16)
One_D_Image_Green = One_D_Image_Green.astype(np.int16)
One_D_Image_Blue = One_D_Image_Blue.astype(np.int16)
One_D_Image_H = np.transpose(np.matrix(Image_Array_HSV[:, :, 0].ravel()))
One_D_Image_S = np.transpose(np.matrix(Image_Array_HSV[:, :, 1].ravel()))
One_D_Image_V = np.transpose(np.matrix(Image_Array_HSV[:, :, 2].ravel()))
One_D_Image_L = np.transpose(np.matrix(Image_Array_LAB[:, :, 0].ravel()))
One_D_Image_A = np.transpose(np.matrix(Image_Array_LAB[:, :, 1].ravel()))
One_D_Image_B = np.transpose(np.matrix(Image_Array_LAB[:, :, 2].ravel()))
sensorDictionary = OrderedDict([
("dateTime" ,str(dateTime)),
("redAvg" ,np.sum(One_D_Image_Red)/len(One_D_Image_Red)),
("greenAvg" ,np.sum(One_D_Image_Green)/len(One_D_Image_Red)),
("blueAvg" ,np.sum(One_D_Image_Blue)/len(One_D_Image_Red)),
("hueAvg" ,np.sum(One_D_Image_H)/len(One_D_Image_Red)),
("saturationAvg" ,np.sum(One_D_Image_S)/len(One_D_Image_Red)),
("valueAvg" ,np.sum(One_D_Image_V)/len(One_D_Image_Red)),
("l_Avg" ,np.sum(One_D_Image_L)/len(One_D_Image_Red)),
("a_Avg" ,np.sum(One_D_Image_A)/len(One_D_Image_Red)),
("b_Avg" ,np.sum(One_D_Image_B)/len(One_D_Image_Red)),
])
mSR.sensorFinisher(dateTime,"MCAM",sensorDictionary)