|about 2 months ago||5 days ago|
|MIT License||Apache License 2.0|
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
2 projects | reddit.com/r/backtickbot | 26 Sep 2021
I'm using Omniboard (https://github.com/vivekratnavel/omniboard) with Sacred (https://github.com/IDSIA/sacred) for tracking experiments. You can specify custom Observers in Sacred so the model metrics and logs will be saved to a local directory or to a remote DB (e.g., MongoDB). I use a MongoDB database hosted on Atlas. Unlike other suggested options, Sacred and Omniboard are free. Atlas free tier comes with 512MB of free storage which is a huge amount if you're uploading only log files to it.
[D] Facebook Visdom vs Google Tensorboard for Pytorch
5 projects | reddit.com/r/MachineLearning | 26 Sep 2021
I'm using Omniboard (https://github.com/vivekratnavel/omniboard) with Sacred (https://github.com/IDSIA/sacred) for tracking experiments. You can specify custom Observers in Sacred so the model metrics and logs will be saved to a local directory or to a remote DB (e.g., MongoDB). I use a MongoDB database hosted on Atlas. Unlike other suggested options, Sacred and Omniboard are free. Atlas free tier comes with 512MB of free storage which is a huge amount if you're uploading only log files to it. ex = Experiment() ex.observers.append(FileStorageObserver(EXPERIMENTS_ROOT)) ex.observers.append(MongoObserver(url=MONGODB_URL, db_name='sacred'))
Can someone tell me good libraries you use on a day to day basis that increases your research productivity in ML/AI?
1 project | reddit.com/r/MLQuestions | 24 May 2021
sacred helped me log my experiments. I did setup my environment only once 4 years ago, and since then I have a list of all my training runs with the hyperparameters and results.
[D] How to be more productive while doing Deep Learning experiments?
10 projects | reddit.com/r/MachineLearning | 25 Feb 2021
For 1, setup an experiment tracking framework. I found Sacred to be helpful https://github.com/IDSIA/sacred.
Which deep learning method/architecture has been (or can be) useful in the detection of light smokes (or similar objects with less-defined edges, shapes, and sizes)?
1 project | reddit.com/r/MLQuestions | 24 Dec 2021
There is also another open source package great for semantic segmentation (comes with a model zoo). https://github.com/facebookresearch/detectron2
What are some approaches to visual object tracking for robots?
2 projects | reddit.com/r/computervision | 9 Dec 2021
Can anyone teach us how to build a e-bike detection model?
1 project | reddit.com/r/deeplearning | 5 Sep 2021
Try checking out Facebook’s Detecteon2 for Mask-RCNN (https://github.com/facebookresearch/detectron2). They have a really useful Google Colab tutorial that goes over training a model for identifying just balloons, however their model has an option for adding multiple classes (i.e. e-bike, bike, human, etc.). Mask-RCNN is pretty good at object detection and while it is more than what you need for classification, it’s useful for training on a smaller image dataset
3 projects | reddit.com/r/computervision | 28 Aug 2021
You can see the inference times for the various models here: https://github.com/facebookresearch/detectron2/blob/master/MODEL_ZOO.md
[D] Good quality code repos on deep learning
6 projects | reddit.com/r/MachineLearning | 27 Aug 2021
You might like: https://github.com/facebookresearch/detectron2
Facebook AI's DINO | Official PyTorch Code Explained In-Depth!
1 project | reddit.com/r/learnmachinelearning | 25 Aug 2021
Detect frames having Paper in a Video
2 projects | reddit.com/r/computervision | 18 Aug 2021
if you need to extract the boundaries of the paper you could use detectron2 maskrccn (https://github.com/facebookresearch/detectron2)
Show HN: Object Detection in an Hour
1 project | news.ycombinator.com | 7 Aug 2021
^ probably not, since they use detectron2, but given the labeled images are really the core part of this, there’s no reason you can’t use them on a different mode that is compatible.
Mask r cnn using Resnext backbone
1 project | reddit.com/r/deeplearning | 18 Jul 2021
My first Pypi Package (make-voc-dataset)
3 projects | reddit.com/r/Python | 23 Jun 2021
Majority of the current Deep Learning Frameworks like MMDetection or Detectron2 support the VOC Formatted Data / COCO Formatted Data
What are some alternatives?
mmdetection - OpenMMLab Detection Toolbox and Benchmark
MLflow - Open source platform for the machine learning lifecycle
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
openpose - OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
pytorch-lightning - The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
rembg - Rembg is a tool to remove images background.
U-2-Net - The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."
car-damage-detection - Detectron2 for car damage detection using custom dataset
deep-text-recognition-benchmark - Text recognition (optical character recognition) with deep learning methods.
ai-background-remove - Cut out objects and remove backgrounds from pictures with artificial intelligence
pytorch-image-models - PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more