computervision-recipes VS pix2seq

Compare computervision-recipes vs pix2seq and see what are their differences.

computervision-recipes

Best Practices, code samples, and documentation for Computer Vision. (by microsoft)
Machine Learning Computer Vision Deep Learning Python jupyter-notebook operationalization Kubernetes Azure Microsoft Data Science Tutorial Artificial intelligence image-classification Image processing similarity object-detection convolutional-neural-networks

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pix2seq

Pix2Seq codebase: multi-tasks with generative modeling (autoregressive and diffusion) (by google-research)
pix2seq object-detection Computer Vision vision-language Deep Learning Tensorflow2
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computervision-recipes pix2seq
1 1
9,115 810
- 4.0%
3.9 3.5
about 1 year ago 6 months ago
Jupyter Notebook Jupyter Notebook
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

computervision-recipes

Posts with mentions or reviews of computervision-recipes. We have used some of these posts to build our list of alternatives and similar projects.

pix2seq

Posts with mentions or reviews of pix2seq. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing computervision-recipes and pix2seq you can also consider the following projects:

fastdup - fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale.

TrainYourOwnYOLO - Train a state-of-the-art yolov3 object detector from scratch!

smletsexchangeconnector - SMLets PowerShell based Exchange Connector for controlling Microsoft System Center Service Manager 2016+

DeepLearningExamples - State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

Deep-Learning-Computer-Vision - My assignment solutions for Stanford’s CS231n (CNNs for Visual Recognition) and Michigan’s EECS 498-007/598-005 (Deep Learning for Computer Vision), version 2020.

tensorflow_Realtime_Multi-Person_Pose_Estimation - Multi-Person Pose Estimation project for Tensorflow 2.0 with a small and fast model based on MobilenetV3

One-Piece-Image-Classifier - A quick image classifier trained with manually selected One Piece images.

License-super-resolution - A License Plate Image Reconstruction Project in Tensorflow2

VIAME - Video and Image Analytics for Multiple Environments

LLVIP - LLVIP: A Visible-infrared Paired Dataset for Low-light Vision

MLB-Pitch-Identification-with-ML - Identify the name of a pitch being thrown using a machine learning model.

strv-ml-mask2face - Virtually remove a face mask to see what a person looks like underneath

computervision-recipes vs fastdup pix2seq vs TrainYourOwnYOLO computervision-recipes vs smletsexchangeconnector pix2seq vs DeepLearningExamples computervision-recipes vs Deep-Learning-Computer-Vision pix2seq vs tensorflow_Realtime_Multi-Person_Pose_Estimation computervision-recipes vs One-Piece-Image-Classifier pix2seq vs License-super-resolution computervision-recipes vs VIAME pix2seq vs LLVIP computervision-recipes vs MLB-Pitch-Identification-with-ML pix2seq vs strv-ml-mask2face