mmyolo
mmselfsup
| mmyolo | mmselfsup | |
|---|---|---|
| 1 | 5 | |
| 2,708 | 3,084 | |
| 3.2% | 0.7% | |
| 4.5 | 5.3 | |
| 3 days ago | 10 months ago | |
| Python | Python | |
| GNU General Public License v3.0 only | Apache License 2.0 |
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mmyolo
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMYOLO: OpenMMLab YOLO series toolbox and benchmark
mmselfsup
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMSelfSup: OpenMMLab self-supervised learning toolbox and benchmark.
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Does anyone know how a loss curve like this can happen? Details in comments
For some reason, the loss goes up shaply right at the start and slowly goes back down. I am self-supervised pretraining an image modeling with DenseCL using mmselfsup (https://github.com/open-mmlab/mmselfsup). This shape happened on the Coco-2017 dataset and my custom dataset. As you can see, it happens consistently for different runs. How could the loss increase so sharply and is it indicative of an issue with the training? The loss peaks before the first epoch is finished. Unfortunately, the library does not support validation.
- Defect Detection using RPI
- [D] State-of-the-Art for Self-Supervised (Pre-)Training of CNN architectures (e.g. ResNet)?
- Rebirth! OpenSelfSup is upgraded to MMSelfSup
What are some alternatives?
mmdetection - OpenMMLab Detection Toolbox and Benchmark
Unsupervised-Semantic-Segmentation - Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals. [ICCV 2021]
mmrotate - OpenMMLab Rotated Object Detection Toolbox and Benchmark
anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
mmtracking - OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.
calibrated-backprojection-network - PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
mmpretrain - OpenMMLab Pre-training Toolbox and Benchmark
mmagic - OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc.
hcaptcha-challenger - 🥂 Gracefully face hCaptcha challenge with MoE(ONNX) embedded solution.
barlowtwins - Implementation of Barlow Twins paper
segment-anything-video - MetaSeg: Packaged version of the Segment Anything repository
Revisiting-Contrastive-SSL - Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]