lanenet-lane-detection | Unofficial implemention of lanenet model for real time lane detection | Machine Learning library

by MaybeShewill-CV Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | lanenet-lane-detection Summary

lanenet-lane-detection is a Python library typically used in Manufacturing, Utilities, Automotive, Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. lanenet-lane-detection has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub.

Unofficial implemention of lanenet model for real time lane detection using deep neural network model

Support

Quality

Security

License

Reuse

Support

lanenet-lane-detection has a medium active ecosystem.

It has 2021 star(s) with 845 fork(s). There are 55 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 548 have been closed. On average issues are closed in 103 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of lanenet-lane-detection is current.

Quality

lanenet-lane-detection has 0 bugs and 0 code smells.

Security

lanenet-lane-detection has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

lanenet-lane-detection code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

lanenet-lane-detection is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

lanenet-lane-detection releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

lanenet-lane-detection saves you 1572 person hours of effort in developing the same functionality from scratch.

It has 3485 lines of code, 153 functions and 27 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Compute the loss of the classification loss
2d convolution layer
Layer normalization layer
Build a relu layer
Builds the model
Builds the aggregation branch
Build a binary segmentation branch
Convolution block
Evaluate Lane
Apply morphological processing
Performs a DBSCAN cluster clustering
Performs embedding features clustering
Compute discriminative loss
Calculate the discriminative loss
Write examples to examples
Construct a tf train Feature
Generate a list of TFRecords
Augment gt_image for test cases
Update the configuration from a file
Update configuration options from a list
Train the model
Embed inference
Augment image
Process tusimple dataset
Convert a ckpt file into a tensorflow
Returns the next batch

Get all kandi verified functions for this library.

lanenet-lane-detection Key Features

No Key Features are available at this moment for lanenet-lane-detection.

lanenet-lane-detection Examples and Code Snippets

LaneNet-Lane-Detection,Train your own model

Python

Lines of Code : 12

License : Permissive (Apache-2.0)

Copy

python data_provider/lanenet_data_feed_pipline.py 
--dataset_dir ./data/training_data_example
--tfrecords_dir ./data/training_data_example/tfrecords

python tools/train_lanenet.py 
--net vgg 
--dataset_dir ./data/training_data_example
-m 0

python to

LaneNet-Lane-Detection,Installation

C++

Lines of Code : 9

License : No License

Copy

1.cd ROOT_DIR && git clone https://github.com/MaybeShewill-CV/MNN-LaneNet.git
2.Download the ckpt file path here https://www.dropbox.com/sh/yndoipxt6nbhg5g/AAAPxZDDO2N0HP0YonetamJoa?dl=0
and place the ckpt file into folder ./checkpoint

cd RO

LaneNet-Lane-Detection,Test model

Python

Lines of Code : 6

License : Permissive (Apache-2.0)

Copy

python tools/test_lanenet.py --weights_path ./model/tusimple_lanenet_vgg/tusimple_lanenet_vgg.ckpt 
--image_path ./data/tusimple_test_image/0.jpg

python tools/evaluate_lanenet_on_tusimple.py 
--image_dir ROOT_DIR/TUSIMPLE_DATASET/test_set/clips 
--w

Community Discussions

Trending Discussions on lanenet-lane-detection

How can I replace `plt.imsave` with `cmap` option set to `gray` with opencv operations?

QUESTION

How can I replace `plt.imsave` with `cmap` option set to `gray` with opencv operations?

Asked 2020-Jan-12 at 08:46

This is the source image I am working with:

I am using this github repository (the file I'm using is tools/test_lanenet.py) to do binary lane segmentation. now I get this image:

The second image is actually an image resulted from this command:

...

ANSWER

Answered 2020-Jan-12 at 07:36

Your images are not the same size. To mask the black/white image onto the color image, they need to align. I tried to simply crop them to the same minimum dimensions at the top left corner, but that did not align them properly.

However, this Python/OpenCV code will give you some idea how to start once you figure out how to align them.

Color Input:

B/W Lane Image:

Source https://stackoverflow.com/questions/59701484

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

Vulnerabilities

No vulnerabilities reported

Install lanenet-lane-detection

This software has only been tested on ubuntu 16.04(x64), python3.5, cuda-9.0, cudnn-7.0 with a GTX-1070 GPU. To install this software you need tensorflow 1.12.0 and other version of tensorflow has not been tested but I think it will be able to work properly in tensorflow above version 1.12. Other required package you may install them by.