ml-cvnets
PixelLib
ml-cvnets | PixelLib | |
---|---|---|
4 | 3 | |
1,681 | 1,014 | |
1.4% | - | |
4.8 | 0.0 | |
6 months ago | 7 months ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
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ml-cvnets
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Apple Researchers Introduce ByteFormer: An AI Model That Consumes Only Bytes And Does Not Explicitly Model The Input Modality - MarkTechPost
https://github.com/apple/ml-cvnets/tree/main/examples/byteformer - Where the code will be located once uploaded
- CVNets - A library for training computer vision networks
- CVNets – A library for training computer vision networks
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Apple ML Researchers Introduce ‘MobileViT’: A Light-Weight And General-Purpose Vision Transformer For Mobile Devices
Github: https://github.com/apple/ml-cvnets
PixelLib
- YOLOv6: Redefine state-of-the-art for object detection
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To separate objects detected from a video using PixelLib
This is the code, found from the reference here.
- New Project In Computer Vision For Beginner
What are some alternatives?
semantic-segmentation-pytorch - Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
Human-Segmentation-PyTorch - Human segmentation models, training/inference code, and trained weights, implemented in PyTorch
PaddleViT - :robot: PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
sahi - Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
dytox - Dynamic Token Expansion with Continual Transformers, accepted at CVPR 2022
FasterRCNN - Clean and readable implementations of Faster R-CNN in PyTorch and TensorFlow 2 with Keras.
SINet - Camouflaged Object Detection, CVPR 2020 (Oral)
rembg-greenscreen - Rembg Video Virtual Green Screen Edition
EfficientFormer - EfficientFormerV2 [ICCV 2023] & EfficientFormer [NeurIPs 2022]
mask-rcnn - Mask-RCNN training and prediction in MATLAB for Instance Segmentation
dgcnn.pytorch - A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)
fashion-segmentation - A tensorflow model for segmentation of fashion items out of multiple product images