mmcv
aiqc
Our great sponsors
mmcv | aiqc | |
---|---|---|
4 | 7 | |
5,596 | 102 | |
2.1% | - | |
7.8 | 4.9 | |
6 days ago | 9 months ago | |
Python | Python | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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.
mmcv
-
MMDeploy: Deploy All the Algorithms of OpenMMLab
MMCV: OpenMMLab foundational library for computer vision.
- Mmcv - Openmmlab computer vision foundation
-
An elegant and strong PyTorch Trainer
I opened source some works (AAAI 21 SeqNet, ICCV 21 MAED, etc) and earned more than 500 stars. After referring to some popular projects (detectron2, pytorch-image-models, and mmcv), based on my personal development experience, I developed a SIMPLE enough, GENERIC enough, and STRONG enough PyTorch Trainer: core-pytorch-utils, also named CPU. CPU covers most details in the process of training a deep neural network, including:
-
Why do practitioners still use regular tensorflow? [D]
Pretty much any custom layer, loss, ops, etc. For some of the most common ones used for objection detection, see here, examples include rotated iou/nms, deformable convolutions, focal loss variants, sync batch norm, etc.
aiqc
- AIQC: End-to-end deep learning on your desktop or server
-
Prediction Algorithm
Please ⭐ on https://github.com/aiqc/aiqc
-
[D] How do you manage Data Science experiments?
https://github.com/aiqc/AIQC Helps prepare data and tune params for keras and pytorch. Stupid easy and reproducible.
-
Why do practitioners still use regular tensorflow? [D]
Here are examples of how to do keras, tf, or pytorch in a parameterized queue. https://github.com/aiqc/aiqc
- AIQC seeking contributors to bring deep learning to open science.
-
[P] AIQC (deep learning framework) is now seeking collaborators.
AIQC is now open to collaborators! Link to low hanging fruit GitHub issues.
- Show HN: Framework for local, reproducible, batched deep learning for research
What are some alternatives?
pytorch-image-models - PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
guildai - Experiment tracking, ML developer tools
TensorFlow2.0_Notebooks - Implementation of a series of Neural Network architectures in TensorFow 2.0
pytorch-lightning - Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
mmrotate - OpenMMLab Rotated Object Detection Toolbox and Benchmark
mmdetection - OpenMMLab Detection Toolbox and Benchmark
mmrazor - OpenMMLab Model Compression Toolbox and Benchmark.
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
mmocr - OpenMMLab Text Detection, Recognition and Understanding Toolbox
mmhuman3d - OpenMMLab 3D Human Parametric Model Toolbox and Benchmark