vision_transformers and convolution-vision-transformers
These are ecosystem siblings—one provides a general framework for applying Vision Transformers across multiple computer vision tasks, while the other implements a specific architectural variant (CvT) that could be integrated into or compared against such frameworks.
About vision_transformers
sovit-123/vision_transformers
Vision Transformers for image classification, image segmentation, and object detection.
This project helps computer vision practitioners train models to automatically identify objects, classify images, or segment images into meaningful regions. You provide it with images or video data, and it outputs a trained model capable of performing these tasks or shows the detected objects/classifications on your input. It's designed for machine learning engineers, data scientists, and researchers working with visual data.
About convolution-vision-transformers
rishikksh20/convolution-vision-transformers
PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers
This project offers a PyTorch implementation of the Convolutional Vision Transformer (CvT) neural network architecture. It takes image data as input and produces classifications, enabling advanced computer vision tasks. This is for researchers and machine learning engineers who need to experiment with or apply state-of-the-art image recognition models.
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