digantamisra98/Mish
Official Repository for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]
- Stars
- 1.3k
- Forks
- 129
- Open issues
- 0
- Last push
- 3mo ago
About Mish
Mish is a free, open-source computer vision tool by digantamisra98, written mainly in Jupyter Notebook. Official Repository for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]. It has 1.3k GitHub stars and 129 forks, and was last updated 3mo ago. It's released under the MIT license, a standard open-source license.
- License
- MIT
- Language
- Jupyter Notebook
- Stars
- 1,300
- Last update
- 3mo ago
- Runs on Mac
- Not stated
- GPU
- Not stated
- Paid API key
- Not stated
- Self-hostable
- Not stated
Similar free tools
ultralytics63k stars · Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
deep-learning-drizzle13k stars · Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
supervision51k stars · We write your reusable computer vision tools. 💜
pytorch-grad-cam13k stars · Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
label-studio29k stars · Label Studio is a multi-type data labeling and annotation tool with standardized output format
Mish FAQ
Is Mish free?
Yes. Mish is open source and free to use. It's released under the MIT license, a standard open-source license.
Does Mish run on a Mac?
The project doesn't say. Check its installation guide before you start.
Does Mish need a GPU?
The project doesn't state hardware needs. AI models generally run much faster with a GPU.
Is Mish still maintained?
It was last updated 3mo ago. Check recent issues on GitHub to judge how active it is.
What are alternatives to Mish?
Similar free, open-source tools include ultralytics, yolov5, deep-learning-drizzle, supervision.