car-behavioral-cloning | convolutional network for end-to-end driving | Machine Learning library

by naokishibuya Python Version: Current License: MIT

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kandi X-RAY | car-behavioral-cloning Summary

car-behavioral-cloning is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. car-behavioral-cloning has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However car-behavioral-cloning build file is not available. You can download it from GitHub.

In this project, I use a neural network to clone car driving behavior. It is a supervised regression problem between the car steering angles and the road images in front of a car. Those images were taken from three different camera angles (from the center, the left and the right of the car). The network is based on The NVIDIA model, which has been proven to work in this problem domain. As image processing is involved, the model is using convolutional layers for automated feature engineering.

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car-behavioral-cloning has a low active ecosystem.

It has 208 star(s) with 140 fork(s). There are 15 watchers for this library.

It had no major release in the last 6 months.

There are 10 open issues and 20 have been closed. On average issues are closed in 22 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of car-behavioral-cloning is current.

Quality

car-behavioral-cloning has no bugs reported.

Security

car-behavioral-cloning has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

car-behavioral-cloning is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

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car-behavioral-cloning releases are not available. You will need to build from source code and install.

car-behavioral-cloning has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed car-behavioral-cloning and discovered the below as its top functions. This is intended to give you an instant insight into car-behavioral-cloning implemented functionality, and help decide if they suit your requirements.

Train a model
Augment image
Pick an image
Load an image
Flip image
Generate a random brightness
Randomly rotate image
Generate a random shadow
Generator for training images
Calls telemetry
Send a steering control
Convert RGB image to YUV
Resize an image
Crop an image
Preprocess an image
Build a model
Load training data
Connects to given socket

Get all kandi verified functions for this library.

car-behavioral-cloning Key Features

No Key Features are available at this moment for car-behavioral-cloning.

car-behavioral-cloning Examples and Code Snippets

No Code Snippets are available at this moment for car-behavioral-cloning.

Community Discussions

Trending Discussions on car-behavioral-cloning

must have same datatype, got tf.uint8 != tf.float32 (behavioral cloning simulator)

QUESTION

must have same datatype, got tf.uint8 != tf.float32 (behavioral cloning simulator)

Asked 2020-Dec-12 at 15:31

While trying the project of car behavioral cloning, I successfully trained my model and generated the file model-001.h5. now in order to test the model, it must successfully drive the vehicle in Udacity self-driving simulator this is done by running the drive.py and the generated model-001.h5 file

...

ANSWER

Answered 2020-Dec-12 at 15:22

It'd be helpful to see on what line you get an error.

It's not obvious to me where the "if statement to change the incoming data to float format" that you refer to is. I see that the model is called on whatever image is loaded, in whatever datatype it comes from. I predict that the image is stored as uint8, the most efficient storage for a (0,255) colour representation.

So try:

image = np.asarray(image, dtype=np.float32)

To create an array of the correct datatype for your model, which I am presuming is tf.float32.

Source https://stackoverflow.com/questions/65266507

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install car-behavioral-cloning

You need an anaconda or miniconda to use the environment setting. Or you can manually install the required libraries (see the contents of the environment*.yml files) using pip.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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