aiqc
mmcv
Our great sponsors
| aiqc | mmcv | |
|---|---|---|
| 7 | 4 | |
| 102 | 5,596 | |
| - | 2.1% | |
| 4.9 | 7.8 | |
| 9 months ago | 5 days ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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.
aiqc
- AIQC: End-to-end deep learning on your desktop or server
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Prediction Algorithm
Please ⭐ on https://github.com/aiqc/aiqc
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[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.
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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.
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[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
mmcv
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMCV: OpenMMLab foundational library for computer vision.
- Mmcv - Openmmlab computer vision foundation
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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:
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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.
What are some alternatives?
guildai - Experiment tracking, ML developer tools
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
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