EvalAI | cloud rocket bar_chart | Machine Learning library

by Cloud-CV Python Version: 1.1 License: Non-SPDX

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

kandi X-RAY | EvalAI Summary

EvalAI is a Python library typically used in Institutions, Learning, Education, Artificial Intelligence, Machine Learning applications. EvalAI has no bugs, it has no vulnerabilities and it has medium support. However EvalAI build file is not available and it has a Non-SPDX License. You can download it from GitHub.

If you are using EvalAI for hosting challenges, please cite the following technical report:.

Support

Quality

Security

License

Reuse

Support

EvalAI has a medium active ecosystem.

It has 1510 star(s) with 702 fork(s). There are 53 watchers for this library.

It had no major release in the last 12 months.

There are 170 open issues and 1000 have been closed. On average issues are closed in 171 days. There are 144 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of EvalAI is 1.1

Quality

EvalAI has 0 bugs and 0 code smells.

Security

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

EvalAI code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

EvalAI has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

EvalAI releases are available to install and integrate.

EvalAI 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.

EvalAI saves you 10309 person hours of effort in developing the same functionality from scratch.

It has 20962 lines of code, 573 functions and 320 files.

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

Top functions reviewed by kandi - BETA

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

Create a new challenge from a ZIP file
Start workers on AWS ECS service
Create a service manager for the given challenge
Generate client token
Create or update a GitHub challenge host
Helper function to get the value from a field
Download a file and write it to output_path
Validate the challenge config file
Send a submission message
Adds a participant team to a challenge team
Update submission data and visibility
Invite users to a challenge
Returns all entries in the leaderboard for the given leaderboard
Update leaderboard data
Update failed jobs and log messages
Finish an annotation file
Invite a participant to a team
Setup AWS EKS cluster
Finish submission file upload
Update a partially evaluated submission
Download all submissions
Submit a challenge
Update a submission
Returns the signed URL for a submission file
Create subnets for evaluation
Create a test evaluation cluster

Get all kandi verified functions for this library.

EvalAI Key Features

No Key Features are available at this moment for EvalAI.

EvalAI Examples and Code Snippets

Directory Structure

Python

Lines of Code : 27

License : No License

Copy

.
├── README.md
├── annotations                                 # Contains the annotations for Dataset splits
│   ├── test_annotations_devsplit.json          # Annotations of dev split
│   └── test_annotations_testsplit.json

Cascade Reasoning Network for Text-based Visual Question Answering,Training and Evaluation

Python

Lines of Code : 7

License : Non-SPDX (NOASSERTION)

Copy

# bash scripts/  
bash scripts/train_textvqa.sh 0,1 textvqa_debug

# bash scripts/    

bash scripts/val_textvqa.sh 0,1 textvqa_debug save/textvqa_debug/crn_textvqa_crn/best.ckpt val

bash scripts/val_textvqa.sh 0,1 textvqa_debug save/textvqa_debug/c

ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning (ICLR 2020),Setting up and using the repo

Python

Lines of Code : 3

License : No License

Copy

pip install transformers==2.3.0

git clone https://github.com/yuweihao/reclor.git

sh scripts/run_roberta_large.sh

Community Discussions

Trending Discussions on EvalAI

Css file not detecting the update of data-theme in html

QUESTION

Css file not detecting the update of data-theme in html

Asked 2020-Jan-02 at 04:18

I am adding the dark theme to my website so i added a toggle switch in my footer.html page and it add a variable name data-theme = 'dark' to the html. the scss files of footer and core scss files are changing as per the condition but the scss files in module is not . Here is my code

Footer.html

...

ANSWER

Answered 2020-Jan-02 at 04:18

Problem

Sass is a pre-processor for CSS.

Sass variables are nonexistant in the final outputted CSS. They are only available during the Sass preprocessing, and will not be printed in the final CSS. Any variable will be replaced by the value it represents.

Your inputed Sass:

Source https://stackoverflow.com/questions/59556172

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

Vulnerabilities

No vulnerabilities reported

Install EvalAI

Setting up EvalAI on your local machine is really easy. You can setup EvalAI using docker: The steps are:. If you are facing any issue during installation, please see our common errors during installation page.
Install docker and docker-compose on your machine.
Get the source code on to your machine via git. git clone https://github.com/Cloud-CV/EvalAI.git evalai && cd evalai
Build and run the Docker containers. This might take a while. docker-compose up --build
That's it. Open web browser and hit the URL http://127.0.0.1:8888. Three users will be created by default which are listed below - SUPERUSER- username: admin password: password HOST USER- username: host password: password PARTICIPANT USER- username: participant password: password