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A self driving car model for humans.

Autopilot This code helps in getting the steering angle of self driving car. The inspiraion is taken from Udacity Self driving car module as well End to End Learning for Self-Driving Cars module from NVIDIA The End to End Lear
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Category: Python / Deep Learning
Watchers: 26
Star: 461
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Last update: Sep 21, 2023
Resource links
https://github.com/akshaybahadur21/Autopilot

Autopilot

This code helps in getting the steering angle of self driving car. The inspiraion is taken from Udacity Self driving car module as well End to End Learning for Self-Driving Cars module from NVIDIA

The End to End Learning for Self-Driving Cars research paper can be found at (https://arxiv.org/abs/1604.07316) This repository uses convnets to predict steering angle according to the road.

  1. Autopilot Version 1
  2. Autopilot Version 2

Sourcerer

Code Requirements

You can install Conda for python which resolves all the dependencies for machine learning.

pip install requirements.txt

Description

An autonomous car (also known as a driverless car, self-driving car, and robotic car) is a vehicle that is capable of sensing its environment and navigating without human input. Autonomous cars combine a variety of techniques to perceive their surroundings, including radar, laser light, GPS, odometry, and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage

Autopilot V1 (Udacity Dataset based on Udacity Simulator)

Dataset

You can get the dataset at here

Python Implementation

  1. Network Used- Convolutional Network
  2. Inspiration - Udacity SDC and End to End Learning for Self-Driving Cars by Nvidia

If you face any problem, kindly raise an issue

Procedure

  1. First, run LoadData.py which will get dataset from folder and store it in a pickle file.
  2. Now you need to have the data, run TrainModel.py which will load data from pickle and augment it. After this, the training process begins.
  3. For testing it on the video, run DriveApp.py

Autopilot V2 (NVIDIA Dataset based on real world)

Dataset

Download the dataset at here and extract into the repository folder

Python Implementation

  1. Network Used- Convolutional Network
  2. Inspiration - End to End Learning for Self-Driving Cars by Nvidia

If you face any problem, kindly raise an issue

Procedure

  1. First, run LoadData_V2.py which will get dataset from folder and store it in a pickle file after preprocessing.
  2. Now you need to have the data, run Train_pilot.py which will load data from pickle. After this, the training process begins.
  3. For testing it on the video, run AutopilotApp_V2.py

References:

5 Open More issues
Closed

Error

i am getting error while running the code

opened Jan 4, 2020 by Shagun23 2
Closed

The video file run.mp4 is unavailable for AutoPilot_V2

opened Mar 6, 2019 by emHarshal 2
Closed

About the Lambda layer 

model.add(Lambda(lambda x: x / 127.5 - 1., input_shape=(image_x, image_y, 1)))

What does lambda layer actually do? Other words, why is it divided by 127.5 and -1 ?

opened Feb 22, 2022 by emredo 1
Closed

the video

where did you get that video from?please explain

opened May 5, 2021 by marcosdhiman 1
Closed

ValueError: too many values to unpack (expected 2) on LoadData_V2.py

Hello,

I have a problem when I run this code.

from future import division import cv2 import os import numpy as np import scipy import pickle import matplotlib.pyplot as plt from itertools import islice

LIMIT = None

DATA_FOLDER = 'driving_dataset' TRAIN_FILE = os.path.join(DATA_FOLDER, 'data.txt')

def preprocess(img): resized = cv2.resize((cv2.cvtColor(img, cv2.COLOR_RGB2HSV))[:, :, 1], (100, 100)) return resized

def return_data():

X = []
y = []
features = []

with open(TRAIN_FILE) as fp:
    for line in islice(fp, LIMIT):
        path, angle = line.strip().split()
        full_path = os.path.join(DATA_FOLDER, path)
        X.append(full_path)
        # using angles from -pi to pi to avoid rescaling the atan in the network
        y.append(float(angle) * scipy.pi / 180)

for i in range(len(X)):
    img = plt.imread(X[i])
    features.append(preprocess(img))

features = np.array(features).astype('float32')
labels = np.array(y).astype('float32')

with open("features", "wb") as f:
    pickle.dump(features, f, protocol=4)
with open("labels", "wb") as f:
    pickle.dump(labels, f, protocol=4)

return_data()

The error is : Traceback (most recent call last): File "LoadData_V2.py", line 45, in <module> return_data() File "LoadData_V2.py", line 27, in return_data path, angle = line.strip().split() ValueError: too many values to unpack (expected 2)

Can you help me, please?

Cordially,

Santosh

opened Jan 26, 2021 by ssantoshp 1
Closed

run.mp4 for V2

I'm not able to find the 'run.mp4' file for AutopilotApp_V2.py.

opened Jan 4, 2021 by ankithkumark 1
Open

Too Slow rendering of both steering and car video.

null

opened Mar 24, 2023 by styxOO7 3
Open

파이참

null

opened Dec 31, 2022 by MijuP 0
Open

ValueError: bad marshal data (unknown type code)

i am facing this error while running DriveApp.py. please guide me

opened Jul 22, 2022 by imraj20 0
Open

unable to install dependencies

i wasn't able to install dependencies my conda prompt was showing this

(base) C:\Users\lenovo\Documents\Autopilot-master>pip install requirements.txt ERROR: Could not find a version that satisfies the requirement requirements.txt ERROR: No matching distribution found for requirements.txt

opened Jul 26, 2021 by skywalkercr7 0
Open

Steering not turning for the Autopilotv2 and i am using the same run video and same code

opened Apr 28, 2019 by vineethamurali 17

Contents

    sagar448 Implementing a self driving car using a 3D Driving Simulator. CNN will be used for training
    felipessalvatore A deep neural network based self-driving car, that combines Lego Mindstorms NXT with the computational power of a Raspberry Pi 3.
    udacity A self-driving car simulator built with Unity
    spicavigo Udacity's Self Driving Car Simulator (Challenge #2)
    tawnkramer This provides a sandbox simulator for training a self-driving car. This uses Unity for simulation and Python with Keras and Tensorflow for training. Recently updated to work on Python 3.4+ and Keras 2+
    autorope Open source hardware and software platform to build a small scale self driving car.
    adityaguptai A End to End CNN Model which predicts the steering wheel angle based on the video/image
    kevinhughes27 self-driving MarioKart with TensorFlow
    llSourcell This is the code for "How to Simulate a Self-Driving Car" by Siraj Raval on Youtube
    duckietown Self-driving car simulator for the Duckietown universe
    udacity The Udacity open source self-driving car project
    littlemountainman Self driving car lane and path detection
    daohu527 A curated list of all awesome things related to self-driving car.
    Daniel-Krzyczkowski Cars Island is a fake car rental company which used Microsoft Azure cloud services to implement the system for managing car renting.
    Jasonnor Autonomous car simulator (based on JavaScript & WebGL) implemented by fuzzy control system, genetic algorithm and particle swarm optimization.
    akhenakh My Own Car System, a Go & Qt application for your car
    renzuzu FIvem - Project Cars - Enable your player to build their dream car from Shell. Included Advanced Chopshop and Car Builder Job.
    oguzhnatly 🚗 Apple CarPlay for Flutter Apps. Aims to make it safe to use apps made with Flutter in the car by integrating with CarPlay.
    autonomousdrivingkr Awesome Autonomous Driving
    commaai dataset and code for 2016 paper "Learning a Driving Simulator"
    woven-planet ML Prediction, Planning and Simulation for Self-Driving
    Share this repo

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