modelzoo | learned models for use in autonomous driving applications | Machine Learning library

by autowarefoundation Python Version: v1.1.0 License: Apache-2.0

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

kandi X-RAY | modelzoo Summary

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

A collection of machine-learned models for use in autonomous driving applications.

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Quality

Security

License

Reuse

Support

modelzoo has a low active ecosystem.

It has 53 star(s) with 15 fork(s). There are 7 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 6 have been closed. On average issues are closed in 33 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of modelzoo is v1.1.0

Quality

modelzoo has 0 bugs and 0 code smells.

Security

modelzoo has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

modelzoo code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

modelzoo 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

modelzoo releases are available to install and integrate.

modelzoo 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 modelzoo and discovered the below as its top functions. This is intended to give you an instant insight into modelzoo implemented functionality, and help decide if they suit your requirements.

Tune a tensorflow model .
Compile the given model .
Get a network from the given info .
Preprocess the compiler .
Generate a configuration file .
Perform the tuning preprocessing .
Process a yaml file .

Get all kandi verified functions for this library.

modelzoo Key Features

No Key Features are available at this moment for modelzoo.

modelzoo Examples and Code Snippets

Autoware Model Zoo,Contributing Models,Setup LFS Tracking

Python

Lines of Code : 4

License : Permissive (Apache-2.0)

Copy

$ git lfs track

$ git lfs track "*.tflite"
$ git add .gitattributes
$ git commit -m "tflite files are now tracked by LFS"

Autoware Model Zoo,Cloning The Model Zoo

Python

Lines of Code : 4

License : Permissive (Apache-2.0)

Copy

$ GIT_LFS_SKIP_SMUDGE=1 git clone https://github.com/autowarefoundation/modelzoo.git
$ cd modelzoo
$ git lfs install
$ git lfs pull

Autoware Model Zoo,Contributing Models,Folder Structure

Python

Lines of Code : 1

License : Permissive (Apache-2.0)

Copy

autoware-model-zoo//_//

Community Discussions

Trending Discussions on modelzoo

Inference Discrepancy between PyTorch and DJL implementation via Kotlin

Tensorflow 2 Object Detection API - Official Models: What is VAL_JSON_FILE?

Problem with Tensorflow package when it's used by Lucid package

QUESTION

Inference Discrepancy between PyTorch and DJL implementation via Kotlin

Asked 2021-Apr-19 at 19:53

I have a PyTorch model trained on the 17flowers dataset, and converted via PyTorch's tracing to a JIT model. I have tested the inference output for the PyTorch model and the JIT converted model, and the results are equivalent there. This leads me to believe there is an issue with my implementation of the DJL framework.

There is an issue when I attempt to utilized DJL for inference utilizing the converted JIT model, which is necessary for DJL. I am not getting 100% match, which I expected.

The Kotlin implementation for djl.ai is straightforward and essentially follows the instructions here.

I have a sanitized version of the Kotlin code below:

...

ANSWER

Answered 2021-Apr-18 at 18:58

The discrepancy most likely comes from image pre-processing:

Source https://stackoverflow.com/questions/67066218

QUESTION

Tensorflow 2 Object Detection API - Official Models: What is VAL_JSON_FILE?

Asked 2021-Mar-31 at 19:38

To use any of the Object Detection models from TensorFlow's Official Models in the ModelZoo, there is a variable called "VAL_JSON_FILE", which is used for the params_override argument. For my use case, I am performing transfer learning on RetinaNet. The command and arguments are found below:

...

ANSWER

Answered 2021-Mar-31 at 19:38

https://gregsdennis.github.io/Manatee.Json/usage/schema/validation.html
This link is somewhat relevant and can provide you with more info on JSON validation. It seems to me like it's a testing (validation) of the JSON objects; checking whether it matches types.

Have you tried to run the learning without that file? I'm not certain but it could be an optional file, or there is a default one already without necessary changes needed.

Source https://stackoverflow.com/questions/66893995

QUESTION

Problem with Tensorflow package when it's used by Lucid package

Asked 2020-Apr-15 at 23:35

So I am trying to use the code in this link:

...

ANSWER

Answered 2020-Apr-15 at 23:35

As for today, lucid does not work with tensorflow2.0 and later versions. However, you can use tf1.15 or any older version and this should solve it.

Source https://stackoverflow.com/questions/61218853

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

Vulnerabilities

No vulnerabilities reported

Install modelzoo

git lfs identify the files to track by their filename extension. To check what extensions are already tracked in this zoo:.

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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