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data.py
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data.py
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from sklearn.datasets import load_digits
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
class Data:
__data = None
@staticmethod
def getData():
if Data.__data == None:
Data()
return Data.__data
def __init__(self,counter,X_pool,y_pool,learner,committee,accuracy,X_test,y_test,classlist,queries,image_data):
print("Inint called")
self.counter = counter
self.X_pool = X_pool
self.y_pool = y_pool
self.learner = learner
self.committee = committee
self.accuracy = list(accuracy)
self.X_test = X_test
self.y_test = y_test
self.classlist = classlist
self.queries = queries
self.image_data = image_data
self.image_name_list = []
self.image_instance_name = ""
self.image_instance = None
Data.__data = self
def setdata(self,params):
self.counter = params["counter"]
self.X_pool = params["X_pool"]
self.y_pool = params["y_pool"]
self.image_name_list = params["image_name_list"]
self.image_instance_name = params["image_instance_name"]
self.image_instance = params["image_instance"]
list = self.accuracy
list.append(params["accuracy"])
self.accuracy = list
Data.__data = self
def givedata(self):
params={}
params["counter"] = self.counter
params["X_pool"] = self.X_pool
params["y_pool"] = self.y_pool
params["learner"] = self.learner
params["committee"] = self.committee
params["accuracy"] = self.accuracy
return params