AgML VS PixelLib

Compare AgML vs PixelLib and see what are their differences.

AgML

AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations. (by Project-AgML)
Deep Learning Agriculture Pytorch Dataset image-classification object-detection semantic-segmentation Computer Vision synthetic-data
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PixelLib

Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/ (by ayoolaolafenwa)
Computer Vision Machine Learning Artificial intelligence image-segmentation semantic-segmentation instance-segmentation video-segmentation deeplab Deeplearning maskr-cnn Tensorflow Deep Learning pointrend Pytorch convolutional-neural-networks Segmentation object-detection
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AgML PixelLib
1 3
156 1,017
5.8% -
7.5 0.0
15 days ago 7 months ago
Python Python
Apache License 2.0 MIT License
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.

AgML

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

PixelLib

Posts with mentions or reviews of PixelLib. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-06-29.

What are some alternatives?

When comparing AgML and PixelLib you can also consider the following projects:

gluon-cv - Gluon CV Toolkit

Human-Segmentation-PyTorch - Human segmentation models, training/inference code, and trained weights, implemented in PyTorch

ScanRefer - [ECCV 2020] ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language

sahi - Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/cvat-ai/cvat]

FasterRCNN - Clean and readable implementations of Faster R-CNN in PyTorch and TensorFlow 2 with Keras.

pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

rembg-greenscreen - Rembg Video Virtual Green Screen Edition

Entity - EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation

mask-rcnn - Mask-RCNN training and prediction in MATLAB for Instance Segmentation

labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.

fashion-segmentation - A tensorflow model for segmentation of fashion items out of multiple product images

AgML vs gluon-cv PixelLib vs Human-Segmentation-PyTorch AgML vs ScanRefer PixelLib vs sahi AgML vs cvat PixelLib vs FasterRCNN AgML vs pytorch-grad-cam PixelLib vs rembg-greenscreen AgML vs Entity PixelLib vs mask-rcnn AgML vs labelme2coco PixelLib vs fashion-segmentation