type=int,
default=128)
parser.add_argument(
'--numberOfTrainingImages',
help=
'The maximum number of training images (Default: 0, which means no limit)',
type=int,
default=0)
args = parser.parse_args()
args.cuda = not args.disable_cuda and torch.cuda.is_available()
imageSize = ast.literal_eval(args.imageSize)
loader = Loader.Importer(
args.trainDirectory,
args.numberOfTrainingImages + args.numberOfValidationImages)
trainFilepathToClassDic, validationFilepathToClassDic = loader.SplitForTrainAndValidation(
args.numberOfTrainingImages, args.numberOfValidationImages)
trainFilepaths = [*trainFilepathToClassDic]
validationFilepaths = [*validationFilepathToClassDic]
print("len(trainFilepaths) = {}; len(validationFilepaths) = {}".format(
len(trainFilepaths), len(validationFilepaths)))
# Create a neural network and an optimizer
if args.architecture == 'ConvStack_3_3_32_7_2_32_7_2_32_7_2_12_256_0.5':
structureElements = ConvStackClassifier.ExtractStructureFromFilename(
args.architecture)
neuralNet = ConvStackClassifier.NeuralNet(structureElements[2],
structureElements[0],
structureElements[3],
help='The learning rate (Default: 0.001)',
type=float,
default=0.001)
parser.add_argument('--momentum',
help='The learning momentum (Default: 0.9)',
type=float,
default=0.9)
parser.add_argument('--minibatchSize',
help='The minibatch size (Default: 32)',
type=int,
default=32)
args = parser.parse_args()
args.cuda = not args.disable_cuda and torch.cuda.is_available()
loader = Loader.Importer(os.path.join(args.baseDirectory, 'train'))
testDirectory = os.path.join(args.baseDirectory, 'test')
imageFilepaths = [
os.path.join(testDirectory, f) for f in os.listdir(testDirectory)
if os.path.isfile(os.path.join(testDirectory, f))
]
#print ("imageFilepaths =", imageFilepaths)
# Create a neural network and an optimizer
if args.architecture == 'ConvStack_3_3_32_7_2_32_7_2_32_7_2_12_256_0.5':
structureElements = ConvStackClassifier.ExtractStructureFromFilename(
args.architecture)
neuralNet = ConvStackClassifier.NeuralNet(structureElements[2],
structureElements[0],
structureElements[3],
structureElements[4],
