Top 23 Python image-classification Projects
🖍️ LabelImg is a graphical image annotation tool and label object bounding boxes in imagesProject mention: Anyone know of a free tool to help with preparing the JSON file for CreateMl Object Detection? | reddit.com/r/swift | 2021-12-12
Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125Project mention: Data augmentation strategies for object detection? Could you point me to good resources or best practices you know of? | reddit.com/r/computervision | 2021-10-30
You can definitely look at Albumentation - we had a ton of success working with this library https://github.com/albumentations-team/albumentations
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Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in PytorchProject mention: [D] Surprisingly Simple SOTA Self-Supervised Pretraining - Masked Autoencoders Are Scalable Vision Learners by Kaiming He et al. explained (5-minute summary by Casual GAN Papers) | reddit.com/r/MachineLearning | 2021-11-17
nah, it is really simple. here is the code https://github.com/lucidrains/vit-pytorch/blob/main/vit_pytorch/mae.py
Label Studio is a multi-type data labeling and annotation tool with standardized output formatProject mention: [D] Portals for outsourcing preliminary data labeling | reddit.com/r/MachineLearning | 2022-01-13
Not exactly for this solution, but I have really liked this tool. https://labelstud.io/ It is open source and can be self hosted if needed
AutoGluon: AutoML for Text, Image, and Tabular DataProject mention: What will the data science job market be like in 5 years? | reddit.com/r/datascience | 2021-08-14
Some AutoML is getting pretty good, AutoGluon is very solid for tabular data. That being said you still need to have your data in tabular format and deployment still requires some effort.
A treasure chest for visual recognition powered by PaddlePaddleProject mention: Baidu AI Research Team Introduces ‘PP-ShiTu’: A Practical Lightweight Image Recognition System | reddit.com/r/machinelearningnews | 2021-11-07
Quick 5 Min Read | Paper | Github
Implementation of EfficientNet model. Keras and TensorFlow Keras.Project mention: I made an image recognition model written in NodeJs | reddit.com/r/webdev | 2021-02-24
EfficientNet a lightweight convolutional neural network architecture achieving the state-of-the-art accuracy with an order of magnitude fewer parameters and FLOPS, on both ImageNet and five other commonly used transfer learning datasets.
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[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operatorProject mention: [R] Involution: Inverting the Inherence of Convolution for Visual Recognition | reddit.com/r/MachineLearning | 2021-05-10
PDF Link | Landing Page | Read as web page on arXiv Vanity
OpenMMLab Image Classification Toolbox and BenchmarkProject mention: how to recognize digits from this pics(i have many of them) so kindly suggest generic that can work for other similar images. I have searched alot for the source code on github but not found the correct solution. most of these solutions were incorrect while other were incomplete. Kindly help me :( | reddit.com/r/computervision | 2021-02-09
MMClassification or TIMM would be good starting points for training a classification model.
SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]Project mention: Any reference or idea about how to train unsupervised CNN model ? | reddit.com/r/deeplearning | 2021-04-13
Tensorflow implementation of "Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network"Project mention: [R] ResNet strikes back: An improved training procedure in timm. There has been significant progress on best practices for training neural nets since ResNet's introduction in 2015. With such advances, a vanilla ResNet-50 reaches 80.4% top-1 accuracy on ImageNet without extra data or distillation. | reddit.com/r/MachineLearning | 2021-10-04
As far as i know, the assemble-ResNet-50 (https://github.com/clovaai/assembled-cnn) gets 82.8% top-1, though they make some (minor) changes to ResNet-50 architecture.
Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in PytorchProject mention: “Transformer in Transformer” paper explained! | reddit.com/r/computervision | 2021-03-04
A thirdparty implementation of " Transformer in Transformer": https://github.com/lucidrains/transformer-in-transformer
A script in python to organize your images by similarity.
A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.Project mention: Answer: Resizing image and its bounding box | dev.to | 2021-07-03
Another way of doing this is to use CHITRA
PyTorch Implementation of CvT: Introducing Convolutions to Vision TransformersProject mention: CvT: Introducing Convolutions to Vision Transformers | reddit.com/r/computervision | 2021-03-30
Unofficial implementation of MLP-Mixer: An all-MLP Architecture for VisionProject mention: [R] MLP-Mixer: An all-MLP Architecture for Vision | reddit.com/r/ResearchML | 2021-05-05
My implementation: https://github.com/rishikksh20/MLP-Mixer-pytorch
A lightweight package for converting your labelme annotations into COCO object detection format.Project mention: What's A Simple Custom Segmentation Pipeline? | reddit.com/r/computervision | 2021-02-12
I would also suggest labelme, it's pretty easy to use. Just type "labelme" in the shell after pip installing and you will see the GUI. There are tools to convert to coco format (like https://github.com/fcakyon/labelme2coco) if needed, for instance for Detectron2.
One-click image sorting/labelling scriptProject mention: How are custom (bounding box) object datasets collected in research/practice? Thinking about making an iOS app to help if this is tedious. | reddit.com/r/computervision | 2021-05-23
I first altered the image-sorter2 code to do multi-classes and save to CSV file instead of moving files to directories. I then implemented the YOLOv5 algorithm in the image viewing, so that it would predict where the people were in the image. I could then label where the people were by box number and label their activity. It ends up being pretty quick to label images this way.
Implementation of Convolutional enhanced image TransformerProject mention: [2103.11816] Incorporating Convolution Designs into Visual Transformers | reddit.com/r/PaperArchive | 2021-03-26
Scripts for training an AI to play the endless runner Subway Surfers using a supervised machine learning approach by imitation and a convolutional neural network (CNN) for image classificationProject mention: Started programming with cs50x last and ai50 this year - I expanded one of the psets to make an ai play a game | reddit.com/r/cs50 | 2021-09-24
Python library for data augmentation in object detection or image classification model trainingProject mention: New image augmentation library for TF Dataset + TPU | reddit.com/r/tensorflow | 2021-09-14
Using Pytorch to Create Deep Learning Models.Project mention: Using PyTorch to Create Deep Learning Models. | reddit.com/r/deeplearning | 2021-12-08
I've created a repository full of PyTorch codes for different deep learning models, please finish check out and any feedback is appreciated.https://github.com/kumarUjjawal/pytorch_deep_learning/tree/master
GitHub Action automating the entire process of image classification with Microsoft Azure Custom Vision Service
Python image-classification related posts
[D] Surprisingly Simple SOTA Self-Supervised Pretraining - Masked Autoencoders Are Scalable Vision Learners by Kaiming He et al. explained (5-minute summary by Casual GAN Papers)
1 project | reddit.com/r/MachineLearning | 17 Nov 2021
Baidu AI Research Team Introduces ‘PP-ShiTu’: A Practical Lightweight Image Recognition System
1 project | reddit.com/r/machinelearningnews | 7 Nov 2021
[R] ResNet strikes back: An improved training procedure in timm. There has been significant progress on best practices for training neural nets since ResNet's introduction in 2015. With such advances, a vanilla ResNet-50 reaches 80.4% top-1 accuracy on ImageNet without extra data or distillation.
1 project | reddit.com/r/MachineLearning | 4 Oct 2021
Baidu Research Introduces PP-LCNet: A Lightweight CPU Convolutional Neural Network With Better Accuracy And Performance
1 project | reddit.com/r/ArtificialInteligence | 3 Oct 2021
New image augmentation library for TF Dataset + TPU
1 project | reddit.com/r/tensorflow | 14 Sep 2021
[P] New image augmentation library for TF + TPU
1 project | reddit.com/r/MachineLearning | 13 Sep 2021
[D] Training vision transformers on a specific dataset from scratch
1 project | reddit.com/r/MachineLearning | 6 Aug 2021
What are some of the best open-source image-classification projects in Python? This list will help you:
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