leaderj1001/BottleneckTransformers
Bottleneck Transformers for Visual Recognition
This project helps machine learning engineers improve the accuracy of their visual recognition models. It takes standard image datasets and outputs a more precise classification model. This is for professionals building and deploying computer vision systems, such as those in autonomous vehicles, medical imaging, or security.
279 stars. No commits in the last 6 months.
Use this if you are developing computer vision models and want to enhance classification accuracy, especially when working with convolutional neural networks like ResNet.
Not ideal if you are not working with visual data or are looking for a simple, out-of-the-box solution without model fine-tuning.
Stars
279
Forks
49
Language
Python
License
MIT
Category
Last pushed
Mar 14, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/leaderj1001/BottleneckTransformers"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Kohulan/DECIMER-Image_Transformer
DECIMER Image Transformer is a deep-learning-based tool designed for automated recognition of...
sovit-123/vision_transformers
Vision Transformers for image classification, image segmentation, and object detection.
fcakyon/video-transformers
Easiest way of fine-tuning HuggingFace video classification models
qubvel/transformers-notebooks
Inference and fine-tuning examples for vision models from 🤗 Transformers
rishikksh20/convolution-vision-transformers
PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers