face-parsing.PyTorch
mmsegmentation
| face-parsing.PyTorch | mmsegmentation | |
|---|---|---|
| 4 | 7 | |
| 2,092 | 7,414 | |
| - | 1.8% | |
| 0.0 | 8.2 | |
| 12 months ago | 5 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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face-parsing.PyTorch
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How to do Human Head Segmentation from images?
Segmentation of head / body - I'd either use mediapipe pose and make something cleverly cut where I wanted based on the landmarks, or I'd use pytorch face parsing if you want to be very exact. I found both of these fairly easy to get to run.
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[P] I made FaceShop! Instance segmentation + CGAN for editing faces (badly)
BiSeNet
Uses a mix of instance segmentation (BiSeNet) and conditional GAN, and is heavily inspired by the Pix2PixHD and DeepSIM papers. Will have more details when I wake up!
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[P] Face make up powerd by deep learning | change color of lips, eyes and eyeglasses
I've developed a demo of human face make-up. The main tech used is face parsing.To get lips, eyes and eyeglasses mask, I perform face parsing based on face-parsing.PyTorch. After that, color changing is done in HSV color space.
mmsegmentation
- [D] The MMSegmentation library from OpenMMLab appears to return the wrong results when computing basic image segmentation metrics such as the Jaccard index (IoU - intersection-over-union). It appears to compute recall (sensitivity) instead of IoU, which artificially inflates the performance metrics.
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Is there any ML model out there for room surfaces detection? (ceiling, floor, windows)
Segmentation models trained on datasets like ADE20k could probably be used for that, because it has separate classes for these things iirc. https://github.com/open-mmlab/mmsegmentation should have suitable pretrained models available.
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMSegmentation: OpenMMLab semantic segmentation toolbox and benchmark.
- Mmsegmentation - Openmmlab semantic segmentation toolbox and benchmark.
- Mmsegmentation – Openmmlab semantic segmentation toolbox and benchmark
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Semantic Segmentation models
This repo is amazing: https://github.com/open-mmlab/mmsegmentation
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What's A Simple Custom Segmentation Pipeline?
Mmsegmentation would be a good place to start for basic segmentation. They have lots of recent methods and pretained models you could fine-tune from. They also support quite a few datasets including VOC. There is a custom dataset format which looks straightforward to create.
What are some alternatives?
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
Swin-Transformer-Semantic-Segmentation - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.
pix2pixHD - Synthesizing and manipulating 2048x1024 images with conditional GANs
SemanticSegmentation - A framework for training segmentation models in pytorch on labelme annotations with pretrained examples of skin, cat, and pizza topping segmentation
Mask_RCNN - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
deepface - A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
PaddleSeg - Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.
CelebAMask-HQ - A large-scale face dataset for face parsing, recognition, generation and editing.
labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.