Pedestrian-Detection | Autonomous driving involves | Machine Learning library

 by   LeadingIndiaAI Python Version: Current License: MIT

kandi X-RAY | Pedestrian-Detection Summary

kandi X-RAY | Pedestrian-Detection Summary

Pedestrian-Detection is a Python library typically used in Manufacturing, Utilities, Automotive, Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. Pedestrian-Detection has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However Pedestrian-Detection build file is not available. You can download it from GitHub.

A Keras implementation of YOLOv3 (Tensorflow backend) on bdd100k dataset.
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            kandi-support Support

              Pedestrian-Detection has a low active ecosystem.
              It has 16 star(s) with 3 fork(s). There are no watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 3 open issues and 0 have been closed. On average issues are closed in 514 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of Pedestrian-Detection is current.

            kandi-Quality Quality

              Pedestrian-Detection has no bugs reported.

            kandi-Security Security

              Pedestrian-Detection has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              Pedestrian-Detection is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              Pedestrian-Detection releases are not available. You will need to build from source code and install.
              Pedestrian-Detection has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions are not available. Examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed Pedestrian-Detection and discovered the below as its top functions. This is intended to give you an instant insight into Pedestrian-Detection implemented functionality, and help decide if they suit your requirements.
            • Convert a text file to text format
            • K - means algorithm
            • Calculate the intersection of boxes
            • Save result to text file
            • Generate keras model
            • Darknet convolution layer
            • Layer - normalization function
            • Compute tiny yolo body
            • Create data from annotation lines
            • Preprocess the true boxes
            • Data generator
            • Calculate the loss for the given anchors
            • Compute the intersection of two boxes
            • Yolo head
            • Detect video
            • Generate a letterbox image
            • Detects the given image
            • Change all files in a directory
            • Convert label to detector
            • Detect image
            • Generate a stream of unique section names
            • Create a TinyYoV3 model
            • Parse command line arguments
            • Returns a list of class names
            • Read anchors from file
            • Create a YOLOv3 model
            Get all kandi verified functions for this library.

            Pedestrian-Detection Key Features

            No Key Features are available at this moment for Pedestrian-Detection.

            Pedestrian-Detection Examples and Code Snippets

            No Code Snippets are available at this moment for Pedestrian-Detection.

            Community Discussions

            QUESTION

            c4-pedestrian-detector.cpp:283:8: error: ‘Show_Detection_Steps’ was not declared in this scope
            Asked 2020-May-23 at 17:16

            I am trying to compile the CPP file present here and it is giving me the following error. I am new to this. Any help will be highly appreciated. Also, any other way to compile and run it will be helpful if I am making it wrong.

            ...

            ANSWER

            Answered 2020-May-23 at 17:16

            The code is indeed broken; Show_Detection_Steps is used before it is declared.

            Some compilers let you get away with it due to different methods of implementing templates, which is probably why the author missed it. But the code is, per the C++ language, broken.

            You should report this as a bug to the author, using the GitHub project page you linked to.

            Source https://stackoverflow.com/questions/61975715

            QUESTION

            The correct header file to access the cvLoadImage() function
            Asked 2018-Dec-04 at 11:56

            I'm trying to get the algorithm provided in this repository to work on windows. After countless issues, I'm only left with one unrecognized function cvLoadImage which is apprently depricated. I was instructed to work with the c++ API instead but the problem is that I will have to rewrite other parts of the code as well and I might end up breaking it.

            ...

            ANSWER

            Answered 2018-Dec-04 at 11:56

            Indeed, that is the old OpenCV C API. You will need to port the old C functions to the c++ OpenCV API, e.g.:

            etc.

            The code you're using is actually a mix of the old C API and the newer c++ API. It's just a matter of going through all the C API calls in that repo and manually port them to the c++ API. As you can see above, most of the time that is fairly intuitive. When in doubt search the OpenCV documentation.

            Additionally you should look into YOLOv2 for Pedestrian detection.

            Update:

            There are multiple forks of this repository and it looks like Berak already has already removed the C API calls. His changes were merged, so you should to pull the latest changes and rebuild:

            Source https://stackoverflow.com/questions/53537475

            QUESTION

            Python and openCV : HOG descriptor detect multiscale returns negative bounding box
            Asked 2017-Aug-28 at 11:58

            I am using OpenCV's HOG detector to detect pedestrians in a video. But the bounding boxes returned by it's detectMultiScale() have one negative value. I couldn't find anything helpful or useful so far on internet to understand and solve this problem. I do not even know why is this problem occurring. that's the output.

            ...

            ANSWER

            Answered 2017-Aug-28 at 11:58

            After trying almost everything on internet when I couldn't find answer anywhere I started analyzing this problem myself and found the solution to it.

            Source https://stackoverflow.com/questions/45448606

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

            Vulnerabilities

            No vulnerabilities reported

            Install Pedestrian-Detection

            You can download it from GitHub.
            You can use Pedestrian-Detection like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            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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            https://github.com/LeadingIndiaAI/Pedestrian-Detection.git

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            gh repo clone LeadingIndiaAI/Pedestrian-Detection

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            git@github.com:LeadingIndiaAI/Pedestrian-Detection.git

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