Software Alternatives & Reviews

Labelbox VS NumPy

Compare Labelbox VS NumPy and see what are their differences

Labelbox logo Labelbox

Build computer vision products for the real world

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Labelbox Landing page
    Landing page //
    2023-08-20

A complete solution for your training data problem with fast labeling tools, human workforce, data management, a powerful API and automation features.

  • NumPy Landing page
    Landing page //
    2023-05-13

Labelbox videos

Review App : Labelbox

More videos:

  • Review - Machine Learning Support Engineer at Labelbox
  • Review - Bounding box annotation with Labelbox

NumPy videos

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Category Popularity

0-100% (relative to Labelbox and NumPy)
Data Labeling
100 100%
0% 0
Data Science And Machine Learning
Image Annotation
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

Share your experience with using Labelbox and NumPy. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Labelbox and NumPy

Labelbox Reviews

  1. Unreliable

    Service goes down often. Very slow team. Slow support.

    🏁 Competitors: Diffgram
    👎 Cons:    Slow|Bad support

Top Video Annotation Tools Compared 2022
However, Labelbox only accepts .mp4 files into their platform, and only their most basic annotation modes have the full scope of video annotation options. When annotating videos with segmentation masks, annotators must step through each frame to view their work – there is no playback option.
Source: innotescus.io

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Labelbox. While we know about 107 links to NumPy, we've tracked only 8 mentions of Labelbox. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Labelbox mentions (8)

  • Ask HN: Who is hiring? (October 2022)
    Labelbox | Remote | Frontend / WebGL, Backend, Engineering Managers | https://labelbox.com Labelbox is building the training data platform to power breakthroughs in machine learning. We provide an end to end solutions for the full AI lifecycle from creating catalogs of unstructured data all the way to building the tools for humans to label the data to teach machines. Why choose us? - Source: Hacker News / over 1 year ago
  • Model Assisted Labeling using Label box
    Hey, I have currently developed a U-Net model for segmentation and I am trying to use the model assisted labeling feature on LabelBox to annotate some masks, so I can save time on relabeling. I am just wondering if anyone is familiar with this feature or can give me a step by step guideline on how to go about doing this. I went through the examples on their GitHub but I’m honestly still very confused. Any help... Source: over 1 year ago
  • What MDR is doing: a Machine Learning perspective
    By now, I hope you see where I'm going with this. What is MDR doing? They're creating the labelled data used to train severance chips. They get a raw download of human brains in encoded format, and go about manually labelling the different pieces based on their most basic elements. Then, based on this manually labelled data, an algorithm can be trained to create a severance chip. MDR is basically Labelbox for... Source: almost 2 years ago
  • [D] Any recommendations for image annotation software .
    LabelBox - they provide free versions for research. Source: almost 2 years ago
  • Video box annotation tool for Google Cloud Video Intelligence autoML CSV format ?
    Doing some progress, labelbox.com allows me to do the Video annotation, and access all data through python SDK/API... Working on converting myself to CSV GCP format :-). Source: about 2 years ago
View more

NumPy mentions (107)

  • Element-wise vs Matrix vs Dot multiplication
    In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 1 month ago
  • JSON in data science projects: tips & tricks
    Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / about 2 months ago
  • Introducing Flama for Robust Machine Learning APIs
    Numpy: A library for scientific computing in Python. - Source: dev.to / 4 months ago
  • A Comprehensive Guide to NumPy Arrays
    Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago
  • Beginning Python: Project Management With PDM
    A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
View more

What are some alternatives?

When comparing Labelbox and NumPy, you can also consider the following products

Playment - Playment is a fully-managed solution offering training data for AI, transcription, data collection and enrichment services at scale.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

V7 - Pixel perfect image labeling for industrial, medical, and large scale dataset creation. Create ground truth 10 times faster.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Supervisely - Supervisely helps people with and without machine learning expertise to create state-of-the-art...

OpenCV - OpenCV is the world's biggest computer vision library