dataset | The Open Images dataset | Dataset library

 by   openimages Python Version: Current License: Apache-2.0

kandi X-RAY | dataset Summary

kandi X-RAY | dataset Summary

dataset is a Python library typically used in Artificial Intelligence, Dataset applications. dataset has no bugs, it has no vulnerabilities, it has a Permissive License and it has high support. However dataset build file is not available. You can download it from GitHub.

As of V4, the Open Images Dataset moved to a new site.
Support
    Quality
      Security
        License
          Reuse

            kandi-support Support

              dataset has a highly active ecosystem.
              It has 4137 star(s) with 608 fork(s). There are 210 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 34 open issues and 53 have been closed. On average issues are closed in 77 days. There are no pull requests.
              It has a positive sentiment in the developer community.
              The latest version of dataset is current.

            kandi-Quality Quality

              dataset has 0 bugs and 0 code smells.

            kandi-Security Security

              dataset has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              dataset code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              dataset 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.

            kandi-Reuse Reuse

              dataset releases are not available. You will need to build from source code and install.
              dataset has no build file. You will be need to create the build yourself to build the component from source.
              dataset saves you 133 person hours of effort in developing the same functionality from scratch.
              It has 334 lines of code, 12 functions and 5 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed dataset and discovered the below as its top functions. This is intended to give you an instant insight into dataset implemented functionality, and help decide if they suit your requirements.
            • Download all images
            • Ensure that all images in the image list are correctly normalized
            • Read image list file
            • Enogenize a single image
            • Preprocess an image
            • Loads the label map file
            • Load label map
            Get all kandi verified functions for this library.

            dataset Key Features

            No Key Features are available at this moment for dataset.

            dataset Examples and Code Snippets

            Create a csv dataset from a csv file .
            pythondot img1Lines of Code : 296dot img1License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def make_csv_dataset_v2(
                file_pattern,
                batch_size,
                column_names=None,
                column_defaults=None,
                label_name=None,
                select_columns=None,
                field_delim=",",
                use_quote_delim=True,
                na_value="",
                header=True,
                num_epochs=  
            Create a task from a given dataset id .
            pythondot img2Lines of Code : 157dot img2License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def _from_dataset_id(processing_mode,
                                 service,
                                 dataset_id,
                                 element_spec,
                                 job_name=None,
                                 consumer_index=None,
                                 num_consumers=N  
            Apply a function to each element in a dataset .
            pythondot img3Lines of Code : 145dot img3License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def bucket_by_sequence_length(element_length_func,
                                          bucket_boundaries,
                                          bucket_batch_sizes,
                                          padded_shapes=None,
                                          padding_values=None,  

            Community Discussions

            QUESTION

            How do I unpack tuple format in R?
            Asked 2022-Mar-12 at 08:23

            Here is the dataset.

            ...

            ANSWER

            Answered 2022-Mar-11 at 11:17

            Here's a way using separate_rows:

            Source https://stackoverflow.com/questions/71437352

            QUESTION

            react-chartjs-2 with chartJs 3: Error "arc" is not a registered element
            Asked 2022-Mar-09 at 11:20

            I am working on a React app where i want to display charts. I tried to use react-chartjs-2 but i can't find a way to make it work. when i try to use Pie component, I get the error: Error: "arc" is not a registered element.

            I did a very simple react app:

            • npx create-react-app my-app
            • npm install --save react-chartjs-2 chart.js

            Here is my package.json:

            ...

            ANSWER

            Answered 2021-Nov-24 at 15:13

            Chart.js is treeshakable since chart.js V3 so you will need to import and register all elements you are using.

            Source https://stackoverflow.com/questions/70098392

            QUESTION

            TypeError: load() missing 1 required positional argument: 'Loader' in Google Colab
            Asked 2022-Mar-04 at 11:01

            I am trying to do a regular import in Google Colab.
            This import worked up until now.
            If I try:

            ...

            ANSWER

            Answered 2021-Oct-15 at 21:11

            Found the problem.
            I was installing pandas_profiling, and this package updated pyyaml to version 6.0 which is not compatible with the current way Google Colab imports packages.
            So just reverting back to pyyaml version 5.4.1 solved the problem.

            For more information check versions of pyyaml here.
            See this issue and formal answers in GitHub

            ##################################################################
            For reverting back to pyyaml version 5.4.1 in your code, add the next line at the end of your packages installations:

            Source https://stackoverflow.com/questions/69564817

            QUESTION

            AttributeError: Can't get attribute 'new_block' on
            Asked 2022-Feb-25 at 13:18

            I was using pyspark on AWS EMR (4 r5.xlarge as 4 workers, each has one executor and 4 cores), and I got AttributeError: Can't get attribute 'new_block' on . Below is a snippet of the code that threw this error:

            ...

            ANSWER

            Answered 2021-Aug-26 at 14:53

            I had the same error using pandas 1.3.2 in the server while 1.2 in my client. Downgrading pandas to 1.2 solved the problem.

            Source https://stackoverflow.com/questions/68625748

            QUESTION

            Configuring compilers on Mac M1 (Big Sur, Monterey) for Rcpp and other tools
            Asked 2022-Feb-10 at 21:07

            I'm trying to use packages that require Rcpp in R on my M1 Mac, which I was never able to get up and running after purchasing this computer. I updated it to Monterey in the hope that this would fix some installation issues but it hasn't. I tried running the Rcpp check from this page but I get the following error:

            ...

            ANSWER

            Answered 2022-Feb-10 at 21:07
            Background

            Currently (2022-02-05), CRAN builds R binaries for Apple silicon using Apple clang (from Command Line Tools for Xcode 12.4) and an experimental build of gfortran.

            If you obtain R from CRAN (i.e., here), then you need to replicate CRAN's compiler setup on your system before building R packages that contain C/C++/Fortran code from their sources (and before using Rcpp, etc.). This requirement ensures that your package builds are compatible with R itself.

            A further complication is the fact that Apple clang doesn't support OpenMP, so you need to do even more work to compile programs that make use of multithreading. You could circumvent the issue by building R itself and all R packages from sources with LLVM clang, which does support OpenMP, but this approach is onerous and "for experts only". There is another approach that has been tested by a few people, including Simon Urbanek, the maintainer of R for macOS. It is experimental and also "for experts only", but seems to work on my machine and is simpler than trying to build R yourself.

            Instructions for obtaining a working toolchain

            Warning: These instructions come with no warranty and could break at any time. They assume some level of familiarity with C/C++/Fortran program compilation, Makefile syntax, and Unix shells. As usual, sudo at your own risk.

            I will try to address compilers and OpenMP support at the same time. I am going to assume that you are starting from nothing. Feel free to skip steps you've already taken, though you might find a fresh start helpful.

            I've tested these instructions on a machine running Big Sur, and at least one person has tested them on a machine running Monterey. I would be glad to hear from others.

            1. Download an R binary from CRAN here and install. Be sure to select the binary built for Apple silicon.

            2. Run

            Source https://stackoverflow.com/questions/70638118

            QUESTION

            Group and create three new columns by condition [Low, Hit, High]
            Asked 2022-Feb-10 at 16:22

            I have a large dataset (~5 Mio rows) with results from a Machine Learning training. Now I want to check to see if the results hit the "target range" or not. Lets say this range contains all values between -0.25 and +0.25. If it's inside this range, it's a Hit, if it's below Low and on the other side High.

            I now would create this three columns Hit, Low, High and calculate for each row which condition applies and put a 1 into this col, the other two would become 0. After that I would group the values and sum them up. But I suspect there must be a better and faster way, such as calculate it directly while grouping. I'm happy for any idea.

            Data ...

            ANSWER

            Answered 2022-Feb-10 at 16:13

            You could use cut to define the groups and pivot_table to reshape:

            Source https://stackoverflow.com/questions/71068392

            QUESTION

            Create new column based on existing columns whose names are stored in another column (dplyr)
            Asked 2022-Jan-22 at 06:07

            Consider the following dataset:

            ...

            ANSWER

            Answered 2022-Jan-21 at 20:14

            A tidyverse option would be rowwise with extraction using cur_data()

            Source https://stackoverflow.com/questions/70807088

            QUESTION

            Select previous and next N rows with the same value as a certain row
            Asked 2022-Jan-21 at 10:05

            I construct the following panel data with keys id and time:

            ...

            ANSWER

            Answered 2022-Jan-12 at 07:01

            As far as I understood, here's a dplyr suggestion:

            Source https://stackoverflow.com/questions/70677147

            QUESTION

            Is it possible to combine a ggplot legend and table
            Asked 2022-Jan-07 at 03:57

            I was wondering if anyone knows a way to combine a table and ggplot legend so that the legend appears as a column in the table as shown in the image. Sorry if this has been asked before but I haven't been able to find a way to do this.

            Edit: attached is code to produce the output below (minus the legend/table combination, which I am trying to produce, as I stitched that together in Powerpoint)

            ...

            ANSWER

            Answered 2021-Dec-31 at 13:24

            This is an interesting problem. The short answer: Yes, it's possible. But I don't see a way around hard coding the position of table and legend, which is ugly.

            The suggestion below requires hard coding in three places. I am using {ggpubr} for the table, and {cowplot} for the stitching.

            Another problem arises from the legend key spacing for vertical legends. This is still a rather unresolved issue for other keys than polygons, to my knowledge. The associated GitHub issue is closed The legend spacing is not a problem any more. Ask teunbrand, and he knows the answer.

            Some other relevant comments in the code.

            Source https://stackoverflow.com/questions/70511777

            QUESTION

            Merge separate divergent size and fill (or color) legends in ggplot showing absolute magnitude with the size scale
            Asked 2021-Dec-13 at 03:52

            I am plotting some multivariate data where I have 3 discrete variables and one continuous. I want the size of each point to represent the magnitude of change rather than the actual numeric value. I figured that I can achieve that by using absolute values. With that in mind I would like to have negative values colored blue, positive red and zero with white. Than to make a plot where the legend would look like this:

            I came up with dummy dataset which has the same structure as my dataset, to get a reproducible example:

            ...

            ANSWER

            Answered 2021-Dec-08 at 03:15

            One potential solution is to specify the values manually for each scale, e.g.

            Source https://stackoverflow.com/questions/70269045

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

            Vulnerabilities

            No vulnerabilities reported

            Install dataset

            You can download it from GitHub.
            You can use dataset 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 .
            Find more information at:

            Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items

            Find more libraries
            CLONE
          • HTTPS

            https://github.com/openimages/dataset.git

          • CLI

            gh repo clone openimages/dataset

          • sshUrl

            git@github.com:openimages/dataset.git

          • Stay Updated

            Subscribe to our newsletter for trending solutions and developer bootcamps

            Agree to Sign up and Terms & Conditions

            Share this Page

            share link