class ALLoneAPI():
""" ALLoneAPI RPI4 CNN Core Class
Core class for the oneAPI RPI4 Acute Lymphoblastic Leukemia Classifier.
"""
def __init__(self):
""" Initializes the class. """
self.Helpers = Helpers("Core")
self.Core = Model()
self.Helpers.logger.info("ALLoneAPI RPI4 CNN initialization complete.")
def do_load_model(self):
""" Loads the model """
self.Core.load_model_and_weights()
def do_classify(self):
""" Loads model and classifies test data """
self.do_load_model()
self.Core.test_classifier()
def do_server(self):
""" Loads the API server """
self.do_load_model()
self.Server = Server(self.Core)
self.Server.start()
def do_http_classify(self):
""" Loads model and classifies test data """
self.Core.test_http_classifier()
class COVID19DN():
""" COVID19DN Class
Core COVID-19 Tensorflow DenseNet Classifier wrapper class using Tensroflow 2.
"""
def __init__(self):
""" Initializes the class. """
self.Helpers = Helpers("Core")
self.Model = Model()
self.Helpers.logger.info(
"COVID19DN Tensorflow initialization complete.")
def do_data(self):
""" Sorts the training data. """
self.Data = Data()
self.Data.process_data(
self.Data.paths_n_labels())
def do_train(self):
""" Creates & trains the model. """
self.Model.do_model(self.Data)
self.Model.do_train()
self.Model.do_evaluate()
def do_load_model(self):
""" Loads the model """
self.Model.load_model_and_weights()
def do_classify(self):
""" Loads model and classifies test data """
self.do_load_model()
self.Model.test_classifier()
def do_server(self):
""" Loads the API server """
self.do_load_model()
self.Server = Server(self.Model)
self.Server.start()
def do_http_classify(self):
""" Loads model and classifies test data """
self.Model.test_http_classifier()
class AllDS2020():
""" AllDS2020 CNN Class
Core AllDS2020 CNN Tensorflow 2.0 class.
"""
def __init__(self):
""" Initializes the class. """
self.Helpers = Helpers("Core")
self.Core = Model()
self.Helpers.logger.info("AllDS2020 CNN initialization complete.")
def do_train(self):
""" Creates & trains the model. """
self.Core.do_data()
self.Core.do_network()
self.Core.do_train()
self.Core.do_evaluate()
def do_load_model(self):
""" Loads the model """
self.Core.load_model_and_weights()
def do_classify(self):
""" Loads model and classifies test data """
self.do_load_model()
self.Core.test_classifier()
def do_server(self):
""" Loads the API server """
self.do_load_model()
self.Server = Server(self.Core)
self.Server.start()
def do_http_classify(self):
""" Loads model and classifies test data """
self.Core.test_http_classifier()
class ALLoneAPI():
""" ALLoneAPI CNN
Core class for the OneAPI Acute Lymphoblastic Leukemia Classifier CNN.
"""
def __init__(self):
""" Initializes the class. """
self.Helpers = Helpers("Core")
self.Core = Model()
self.Helpers.logger.info("Class initialization complete.")
def do_train(self):
""" Creates & trains the model. """
self.Core.do_data()
self.Core.do_network()
self.Core.do_train()
self.Core.do_evaluate()
def do_load_model(self):
""" Loads the model """
self.Core.load_model_and_weights()
def do_classify(self):
""" Loads model and classifies test data """
self.do_load_model()
self.Core.test_classifier()
def do_server(self):
""" Loads the API server """
self.do_load_model()
self.Server = Server(self.Core)
self.Server.start()
def do_http_classify(self):
""" Loads model and classifies test data """
self.Core.test_http_classifier()
class AllDS2020():
""" AllDS2020 CNN For Raspberry Pi 4 Class
Core AllDS2020 CNN For Raspberry Pi 4 Tensorflow 2.0 class.
"""
def __init__(self):
""" Initializes the class. """
self.Helpers = Helpers("Core")
self.Core = Model()
self.Helpers.logger.info("AllDS2020 CNN initialization complete.")
def do_load_model(self):
""" Loads the model """
self.Core.load_model_and_weights()
def do_classify(self):
""" Loads model and classifies test data """
self.do_load_model()
self.Core.test_classifier()
def do_server(self):
""" Loads the API server """
self.do_load_model()
self.Server = Server(self.Core)
self.Server.start()
def do_http_classify(self):
""" Loads model and classifies test data """
self.Core.test_http_classifier()
class AllDS2020():
""" AllDS2020 Wrapper Class
Core wrapper class for the Tensorflow 2.0 AllDS2020 classifier.
"""
def __init__(self):
self.Helpers = Helpers("Core")
self.optimizer = "Adam"
self.mode = "Local"
self.do_augmentation = True
def do_data(self):
""" Creates/sorts dataset. """
self.Data = Data(self.optimizer, self.do_augmentation)
self.Data.data_and_labels_sort()
if self.do_augmentation == False:
self.Data.data_and_labels_prepare()
else:
self.Data.data_and_labels_augmentation_prepare()
self.Data.shuffle()
self.Data.get_split()
def do_model(self):
""" Creates & trains the model.
Replicates the networked and data splits outlined in the Acute Leukemia Classification
Using Convolution Neural Network In Clinical Decision Support System paper
using Tensorflow 2.0.
https://airccj.org/CSCP/vol7/csit77505.pdf
"""
self.Model = Model(self.optimizer, self.do_augmentation)
self.Model.build_network(self.Data.X_train, self.Data.X_test,
self.Data.y_train, self.Data.y_test)
self.Model.compile_and_train()
self.Model.save_model_as_json()
self.Model.save_weights()
def do_evaluate(self):
""" Predictions & Evaluation """
self.Model.predictions()
self.Model.evaluate_model()
def do_metrics(self):
""" Predictions & Evaluation """
self.Model.visualize_metrics()
self.Model.confusion_matrix()
self.Model.figures_of_merit()
def do_create_model(self):
""" Loads the model """
self.Model = Model(self.optimizer, self.do_augmentation)
def do_load_model(self):
""" Loads the model """
self.Model.load_model_and_weights()
def do_classify(self):
""" Loads model and classifies test data """
self.do_create_model()
self.do_load_model()
self.Model.test_classifier()
def do_http_classify(self):
""" Loads model and classifies test data """
self.do_create_model()
self.Model.test_http_classifier()
class COVID19DN():
""" COVID19DN Class
Core COVID-19 Tensorflow DenseNet Classifier wrapper class using Tensroflow 2.
"""
def __init__(self):
""" Initializes the class. """
self.Helpers = Helpers("Core")
self.Helpers.logger.info(
"COVID-19 Tensorflow DenseNet Classifier initialization complete.")
def life(self):
""" Sends vital statistics to HIAS """
cpu = psutil.cpu_percent()
mem = psutil.virtual_memory()[2]
hdd = psutil.disk_usage('/').percent
tmp = psutil.sensors_temperatures()['cpu-thermal'][0].current
r = requests.get('http://ipinfo.io/json?token=' +
self.Helpers.confs["iotJumpWay"]["key"])
data = r.json()
location = data["loc"].split(',')
self.Helpers.logger.info("COVID19DN Life (TEMPERATURE): " + str(tmp) +
"\u00b0")
self.Helpers.logger.info("COVID19DN Life (CPU): " + str(cpu) + "%")
self.Helpers.logger.info("COVID19DN Life (Memory): " + str(mem) + "%")
self.Helpers.logger.info("COVID19DN Life (HDD): " + str(hdd) + "%")
self.Helpers.logger.info("COVID19DN Life (LAT): " + str(location[0]))
self.Helpers.logger.info("COVID19DN Life (LNG): " + str(location[1]))
# Send iotJumpWay notification
self.iotJumpWayDevice.devicePub(
"Life", {
"CPU": cpu,
"Memory": mem,
"Diskspace": hdd,
"Temperature": tmp,
"Latitude": location[0],
"Longitude": location[1]
})
threading.Timer(60.0, self.life).start()
def iotjumpway_client(self):
""" Starts iotJumpWay Client. """
# Initiates the iotJumpWay connection class
self.iotJumpWayDevice = iotJumpWay({
"host":
self.Helpers.confs["iotJumpWay"]["host"],
"port":
self.Helpers.confs["iotJumpWay"]["port"],
"lid":
self.Helpers.confs["iotJumpWay"]["loc"],
"zid":
self.Helpers.confs["iotJumpWay"]["zne"],
"did":
self.Helpers.confs["iotJumpWay"]["id"],
"dn":
self.Helpers.confs["iotJumpWay"]["name"],
"un":
self.Helpers.confs["iotJumpWay"]["mqtt"]["username"],
"pw":
self.Helpers.confs["iotJumpWay"]["mqtt"]["password"]
})
self.iotJumpWayDevice.connect()
def threading(self):
""" Creates required module threads. """
# Life thread
Thread(target=self.life, args=()).start()
threading.Timer(60.0, self.life).start()
def do_train(self):
""" Creates & trains the model. """
# Load the model class
self.Model = Model()
# Create the model
self.Model.do_model()
# Train the model
self.Model.do_train()
# Validate the model
self.Model.do_evaluate()
def do_load_model(self):
""" Loads the model """
# Load the model and weights
self.Model.load_model_and_weights()
def do_classify(self):
""" Loads model and classifies test data """
# Load the model class
self.Model = Model()
# Load the model
self.do_load_model()
# Classify the test data
self.Model.test_classifier()
def do_server(self):
""" Loads the API server """
# Load the model class
self.Model = Model()
# Load the model
self.do_load_model()
# Load the server class
self.Server = Server(self.Model)
# Start the server
self.Server.start()
def do_http_classify(self):
""" Loads model and classifies test data """
# Load the model class
self.Model = Model()
# Classify the test data via the server
self.Model.test_http_classifier()