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Dataset_generation.py
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Dataset_generation.py
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# coding: utf-8
# In[3]:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import cv2
# In[4]:
Image_height, Image_width, Image_channels = 66, 200, 3
Input_shape = (Image_height, Image_width, Image_channels)
# In[5]:
def get_image(path):
img = cv2.imread(path)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
return img
# In[6]:
def resize_img(img):
new_img = cv2.resize(img, (Image_width, Image_height))
return new_img
# In[7]:
def crop_img(img):
# new_img = img[70:-25, :, :]
new_img = img[60:-25,:,:]
return new_img
# In[8]:
def process_img(path):
img = get_image(path)
img = crop_img(img)
img = resize_img(img)
img = img/255.0
return img
def process(image):
img = crop_img(image)
img = resize_img(img)
img = img/255.0
return img
# In[9]:
def choose_img(row, steering):
ch = np.random.choice(3)
img = process_img(row[ch])
steering_angle = float(steering)
if ch == 1:
steering_angle += 0.2
if ch == 2:
steering_angle -= 0.2
return img, steering_angle
# In[10]:
def generate_data():
ds = pd.read_csv('/home/siddharth/Downloads/beta-simulator-linux/train_data/driving_log.csv')
data = ds.values
X = data[:,:3]
Y = data[:,3]
data_X = np.empty((X.shape[0], Image_height, Image_width, Image_channels))
data_Y = np.empty((Y.shape[0]))
for ix in range(X.shape[0]):
img, steering = choose_img(X[ix], Y[ix])
data_X[ix] = img
data_Y[ix] = steering
return data_X, data_Y