Computer Vision Annotation Tool (CVAT)
AWS SageMaker Ground Truth
Labelbox
Supervisely
Universal Data Tool
Segments.ai
V7
SuperAnnotate
Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
Computer Vision Annotation Tool (CVAT) PandasBased on our record, Pandas seems to be a lot more popular than Computer Vision Annotation Tool (CVAT). While we know about 199 links to Pandas, we've tracked only 14 mentions of Computer Vision Annotation Tool (CVAT). 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.
Another powerful resource is CVAT, the Computer Vision Annotation Tool which supports both image and video annotations with advanced capabilities such as interpolation of shapes between frames, making it highly suitable for computer vision. - Source: dev.to / 5 months ago
CVAT has an open source repo under MIT license: https://github.com/opencv/cvat I've not worked with it directly but it might be a good place to start. Source: 5 months ago
An open source annotation tool that integrates object detectors is CVAT https://github.com/opencv/cvat however, using your own detector might require some coding. There is an integration for yolov5, but without modification it only loads the pretrained models. Source: about 1 year ago
This integration is currently available in the open-source version of Computer Vision Annotation Tool (http://github.com/opencv/cvat)! Please use it for your computer vision projects to segment images faster. - Source: Hacker News / about 1 year ago
You can download the CVAT docker from a github (Link) and install it yourself, keeping all data local. And here are two options - locally on your personal computer (or company server) or in your own cloud (there are instructions on how to do this with AWS). - Source: dev.to / about 1 year ago
It's also possible for you to give a package an alias by using the as keyword. For instance, you could use the pandas package as pd like this:. - Source: dev.to / 3 days ago
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 21 days ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 14 days ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / 2 months ago
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 5 months ago
AWS SageMaker Ground Truth - Build highly accurate training datasets using machine learning and reduce data labeling costs by up to 70%.
NumPy - NumPy is the fundamental package for scientific computing with Python
Labelbox - Build computer vision products for the real world
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
