Speed Prediction

Predicting the Speed of a Vehicle from a Dashboard Camera Video
Alternatives To Speed Prediction
Project NameStarsDownloadsRepos Using ThisPackages Using ThisMost Recent CommitTotal ReleasesLatest ReleaseOpen IssuesLicenseLanguage
Tensorflow172,59032777an hour ago46October 23, 20192,267apache-2.0C++
An Open Source Machine Learning Framework for Everyone
Transformers88,74764911an hour ago91June 21, 2022622apache-2.0Python
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Pytorch64,575146an hour ago23August 10, 202211,522otherC++
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Keras57,7583309 hours ago68May 13, 2022371apache-2.0Python
Deep Learning for humans
Cs Video Courses53,706
10 days ago14
List of Computer Science courses with video lectures.
a month ago15gpl-3.0Python
Deepfakes Software For All
Tensorflow Examples42,312
5 months ago218otherJupyter Notebook
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
D2l Zh41,093
13 hours ago45March 25, 202224apache-2.0Python
100 Days Of Ml Code40,344
17 days ago61mit
100 Days of ML Coding
18 days ago510gpl-3.0Python
DeepFaceLab is the leading software for creating deepfakes.
Alternatives To Speed Prediction
Select To Compare

Alternative Project Comparisons

Enhancement of Vehicle Speed Estimation Based on Optical Flow and Deep Learning Approaches


In recent times, the subject of Intelligent vehicles has become very popular. The inspiration of this popularity cannot be discussed without mentioning computer vision and deep learning. This is because many vehicles, today, have all kinds of high-quality cameras installed on them to capture videos for different benefits. Object tracking and speed estimation are important tasks in video processing. Several methods for speed estimation have been proposed. This paper deals with speed estimation of a car from a video. We propose a method for estimating the speed of a car, with better accuracy, from a video captured by the car’s dashboard camera. The method uses two networks, one for estimating the displacement of the car, and the other for learning the speed labels. We perform experiments applying several image-processing techniques and using a lightweight and efficient optical flow estimation based deep learning approaches to achieve this goal. The proposed model is trained on the comma.ai speed challenge dataset and the results are evaluated and compared to other submissions on this challenge.

How to Setup And Test (Use) The Program

The entire process of running the program includes:

  1. Make sure the videos and the labels are in the “data/” folder.
  2. Make sure your PC/server meets the system setup requirements below:
  • CUDA enable GPU.
  • At least 8 Gigabytes of RAM size will not freeze the system.
  1. Make sure python3 and the required libraries which includes the following are installed: Pytorch (with cuda).
  • openCV
  • Numpy
  • Matplotlib.pyplot
  • keras
  • scikit-learn
  • flowiz
  • PIL.Image
  1. Run “python main.py” to convert videos (train.mp4 and test.mp4) to images and to optical flow.
  2. Run “python train_model.py” to train on training video data. May take at least 4 hours and at most 24 hours to train.
  3. Run “python test_model.py” to predict speed for the test.mp4 video. Note that you can ignore the steps 5 and 6, and run only this step for prediction using our already trained model. Thus, if you like to test our model only.
  4. After step f, the output is stored as in the root directory as a video named, “test_output.mp4”
Sample of our OutPut results

Video 1 Video 1 Video 1 Video 1

Paper link - Pending...

Popular Machine Learning Projects
Popular Deep Learning Projects
Popular Machine Learning Categories
Related Searches

Get A Weekly Email With Trending Projects For These Categories
No Spam. Unsubscribe easily at any time.
Machine Learning
Deep Learning
Optical Flow