Commit 48452bdf authored by Artem Oppermann's avatar Artem Oppermann

final version

parent 528ce023
import numpy as np
import random
csv_path='./data.txt'
class Rectangle:
def __init__(self, x, y, width, height):
self.x=x
self.y=y
self.width=width
self.height=height
self.matrix_size=10
self.matrix=self._init_zeros_matrix()
self.fill()
def _init_zeros_matrix(self):
return np.zeros(shape=(self.matrix_size, self.matrix_size), dtype=np.float32)
def add_noise(self):
new_matrix=np.zeros(shape=(self.matrix_size, self.matrix_size), dtype=np.float32)
for i in range(10):
for j in range(10):
new_matrix[i][j]+=self.matrix[i][j]+np.random.poisson(lam=2.0)
return new_matrix
def fill(self):
for i in range(self.width):
for j in range(self.height):
self.matrix[self.x+i][self.y+j]=10.0
def get_matrix(self):
return self.matrix
def gen_data(n_samples):
rectangles={0:Rectangle(0,0,2,2),
1:Rectangle(3,3,2,2),
2:Rectangle(5,5,2,2),
3:Rectangle(7,7,2,2),}
data=[]
for i in range(0,n_samples):
label=i%4
rect=np.array(rectangles[label].add_noise())
rect_reshaped=np.reshape(rect,[1,100])
data_sample=[]
data_sample.append(rect_reshaped)
data_sample.append(label)
data.append(data_sample)
return data
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