ttach
DeepLabCut
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ttach | DeepLabCut | |
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1 | 12 | |
941 | 4,269 | |
- | 1.9% | |
0.0 | 8.7 | |
9 months ago | 7 days ago | |
Python | Python | |
MIT License | GNU Lesser General Public License v3.0 only |
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ttach
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Setting up Google Colab for Deep Learning
While Colab usually comes pre-installed with most of the basic dependencies like Tensorflow, PyTorch, scikit-learn, pandas and many more, there are chances that you have to install external packages at times. You can do that using the !pip install command. For example we can install the ttach library which is used for augmentation of images during test phase. This can be done using:
DeepLabCut
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Landmark tracking / Pose estimation model training in TensorFlow :
Use DeepLabCut, I also strongly suggest that you should fund their work: https://github.com/DeepLabCut/DeepLabCut
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DeepLabCut alternatives - leap, DeepPoseKit, APT, sleap, and anipose
6 projects | 15 Jul 2022
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Help: Using CV to recognize angles and lines from a picture
DeepLabCut is also worth mentioning here
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Backyard AI dog poop detector walkthrough
1 - Detecting the dog's body parts was the most difficult portion of this, and thankfully I stumbled upon DeepLabCut (https://github.com/DeepLabCut/DeepLabCut) which enables training a model to track a specific animal(s) posture. In the video, this is basically the dots that are overlayed on top of the dog, and follower her around. DeepLabCut is basically just saying that this is where it thinks it recognizes "spine" and "tail".
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Built a dog poop detector for my backyard
I used https://github.com/DeepLabCut/DeepLabCut for the core dog tracking capability, then I wrote the code that analyzes the posture (output by the model, trained via DeepLabCut) of the dog.
I built a dog poop detector for my backyard using DeepLabCut (https://github.com/DeepLabCut/DeepLabCut) and some janky poop detection heuristics I wrote that processed on the detected posture of my dog, if it's in the frame of my security camera. If it detects my dog pooping, it will record the location in a CSV and draw all the locations on an up to date image of my backyard.
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[P] Built a dog poop detector for my backyard
Also, check out DeepLabCut. My project wouldn't have been possible without it, and it's really cool: https://github.com/DeepLabCut/DeepLabCut
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I want to create a pill counter using points instead of bounding boxes. What model should I train from?
Well you could try DeepLabCut - https://github.com/DeepLabCut/DeepLabCut
- DeepLabCut: Deep-learning based markerless pose estimation for all animals
- Can AI make 3d model using my 2d photos ?
What are some alternatives?
albumentations - 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/2078-2489/11/2/125
DeepPoseKit - a toolkit for pose estimation using deep learning
TTNet-Real-time-Analysis-System-for-Table-Tennis-Pytorch - Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
autoalbument - AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
lightweight-human-pose-estimation.pytorch - Fast and accurate human pose estimation in PyTorch. Contains implementation of "Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose" paper.
deepsegment - A sentence segmenter that actually works!
sleap - A deep learning framework for multi-animal pose tracking.
pointnet2 - PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
OpenCV - Open Source Computer Vision Library
mmrazor - OpenMMLab Model Compression Toolbox and Benchmark.
Hekate-Toolbox - A toolbox for Hekate