This solves the autonomous driving issue which is supported by deep learning technology. Given a video, it splits into images and predicts the angle of turning for each frame.

Overview

Self Driving Car

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

Objective

Given images of road you need to predict its degree of turning.

Inspiration πŸ—Ό

  1. Udacity Self driving car
  2. End to End Learning for Self-Driving Cars

Code Requirements πŸ¦„

  • pip install requirements.txt

Dataset 1

Approximately 45,500 images, 2.2GB. One of the original datasets I made in 2017. Data was recorded around Rancho Palos Verdes and San Pedro California.

Link

Data format is as follows: filename.jpg angle

Dataset 2

Approximately 63,000 images, 3.1GB. Data was recorded around Rancho Palos Verdes and San Pedro California.

Link

Data format is as follows: filename.jpg angle,year-mm-dd hr:min:sec:millisec

if you use second dataset, you need to convert it in the form of filename.jpg angle

Use python train.py to train the model

Use python run.py to run the model on a live webcam feed

Use python run_dataset_C.py to run the model on the dataset

You will see

video

Use python app.py if you want to see running it on flask then enter into the url http://127.0.0.1:5000/.After that you see

image

when you click show demo

image

File Organization πŸ—„οΈ

β”œβ”€β”€ selfDrivingCar (Current Directory)
        β”œβ”€β”€ deploy
        β”œβ”€β”€ static
        β”œβ”€β”€ templates
        β”œβ”€β”€ app.py
        β”œβ”€β”€ driving_data.py
        β”œβ”€β”€ modelckpt
        β”œβ”€β”€ model.py
        β”œβ”€β”€ requirements.txt
        β”œβ”€β”€ run_dataset_C.py
        β”œβ”€β”€ steering_wheel_image.jpg
        β”œβ”€β”€ train.py
        └── Readme.Md

References πŸ”±

πŸ”— Links

portfolio linkedin

Owner
Sagor Saha
Machine learning enthusiast
Sagor Saha
PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech

PortaSpeech - PyTorch Implementation PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech. Model Size Module Nor

Keon Lee 279 Jan 04, 2023
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

Daniel Bourke 3.4k Jan 07, 2023
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation

ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation This repository contains the source code of our paper, ESPNet (acc

Sachin Mehta 515 Dec 13, 2022
[SDM 2022] Towards Similarity-Aware Time-Series Classification

SimTSC This is the PyTorch implementation of SDM2022 paper Towards Similarity-Aware Time-Series Classification. We propose Similarity-Aware Time-Serie

Daochen Zha 49 Dec 27, 2022
Implementation of Graph Convolutional Networks in TensorFlow

Graph Convolutional Networks This is a TensorFlow implementation of Graph Convolutional Networks for the task of (semi-supervised) classification of n

Thomas Kipf 6.6k Dec 30, 2022
Churn prediction

Churn-prediction Churn-prediction Data preprocessing:: Label encoder is used to normalize the categorical variable Data Transformation:: For each data

1 Sep 28, 2022
Learning to Predict Gradients for Semi-Supervised Continual Learning

Learning to Predict Gradients for Semi-Supervised Continual Learning Code for project: "Learning to Predict Gradients for Semi-Supervised Continual Le

Yan Luo 2 Mar 05, 2022
Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave

Note: the current releases of this toolbox are a beta release, to test working with Haskell's, Python's, and R's code repositories. Metrics provides i

Ben Hamner 1.6k Dec 26, 2022
Libraries, tools and tasks created and used at DeepMind Robotics.

dm_robotics: Libraries, tools, and tasks created and used for Robotics research at DeepMind. Package overview Package Summary Transformations Rigid bo

DeepMind 273 Jan 06, 2023
TLDR: Twin Learning for Dimensionality Reduction

TLDR (Twin Learning for Dimensionality Reduction) is an unsupervised dimensionality reduction method that combines neighborhood embedding learning with the simplicity and effectiveness of recent self

NAVER 105 Dec 28, 2022
A template repository for submitting a job to the Slurm Cluster installed at the DISI - University of Bologna

Cluster di HPC con GPU per esperimenti di calcolo (draft version 1.0) Per poter utilizzare il cluster il primo passo Γ¨ abilitare l'account istituziona

20 Dec 16, 2022
Keywords : Streamlit, BertTokenizer, BertForMaskedLM, Pytorch

Next Word Prediction Keywords : Streamlit, BertTokenizer, BertForMaskedLM, Pytorch 🎬 Project Demo βœ” Application is hosted on Streamlit. You can see t

Vivek7 3 Aug 26, 2022
TextureGAN in Pytorch

TextureGAN This code is our PyTorch implementation of TextureGAN [Project] [Arxiv] TextureGAN is a generative adversarial network conditioned on sketc

Patsorn 147 Dec 14, 2022
NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size Xuanyi Dong, Lu Liu, Katarzyna Musial, Bogdan Gabrys in IEEE Transactions o

D-X-Y 137 Dec 20, 2022
A Fast and Accurate One-Stage Approach to Visual Grounding, ICCV 2019 (Oral)

One-Stage Visual Grounding ***** New: Our recent work on One-stage VG is available at ReSC.***** A Fast and Accurate One-Stage Approach to Visual Grou

Zhengyuan Yang 118 Dec 05, 2022
Weighing Counts: Sequential Crowd Counting by Reinforcement Learning

LibraNet This repository includes the official implementation of LibraNet for crowd counting, presented in our paper: Weighing Counts: Sequential Crow

Hao Lu 18 Nov 05, 2022
Rule Based Classification Project

Kural Tabanlı Sınıflandırma ile Potansiyel Müşteri Getirisi Hesaplama İş Problemi: Bir oyun şirketi müşterilerinin bazı âzelliklerini kullanaraknseviy

Şafak 1 Jan 12, 2022
Finite-temperature variational Monte Carlo calculation of uniform electron gas using neural canonical transformation.

CoulombGas This code implements the neural canonical transformation approach to the thermodynamic properties of uniform electron gas. Building on JAX,

FermiFlow 9 Mar 03, 2022
A hand tracking demo made with mediapipe where you can control lights with pinching your fingers and moving your hand up/down.

HandTrackingBrightnessControl A hand tracking demo made with mediapipe where you can control lights with pinching your fingers and moving your hand up

Teemu Laurila 19 Feb 12, 2022
YOLOv7 - Framework Beyond Detection

πŸ”₯πŸ”₯πŸ”₯πŸ”₯ YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! πŸ”₯πŸ”₯πŸ”₯

JinTian 3k Jan 01, 2023