XMem
[ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model (by hkchengrex)
yolov7
Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors (by WongKinYiu)
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| XMem | yolov7 | |
|---|---|---|
| 10 | 32 | |
| 1,187 | 10,273 | |
| - | - | |
| 7.9 | 8.8 | |
| 17 days ago | 5 days ago | |
| Python | Jupyter Notebook | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 only |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
XMem
Posts with mentions or reviews of XMem.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-25.
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Track-Anything: a flexible and interactive tool for video object tracking and segmentation, based on Segment Anything and XMem.
Nvm just found the occlusion video on https://github.com/hkchengrex/XMem holy shit
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[D] Most important AI Paper´s this year so far in my opinion + Proto AGI speculation at the end
XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model ( Added because of the Atkinson-Shiffrin Memory Model ) Paper: https://arxiv.org/abs/2207.07115 Github: https://github.com/hkchengrex/XMem
- [D] Most Popular AI Research July 2022 pt. 2 - Ranked Based On GitHub Stars
- Most Popular AI Research July 2022 pt. 2 - Ranked Based On GitHub Stars
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I trained a neural net to watch Super Smash Bros
Yeah MiVOS would speed up your tagging a lot. I also was curious if you saw XMem which just came out. I found that worked really well too.
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[R] Unicorn: 🦄 : Towards Grand Unification of Object Tracking(Video Demo)
Have you check XMem?
yolov7
Posts with mentions or reviews of yolov7.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-30.
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Train a ML model able to identify animal species
If you want something off-the-shelf, try YoloV7.
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[D] Extracting the class labels and bounding boxes for objects, from a YOLO7 model after converting to an ONNX model
(Please note, this is a re-post of my original question here, I think this subreddit might be more appropriate for asking this question)At work, we use Unity, we have a project that needs object detection and classification. We decided to use this YOLO7 model (for non-technical reasons, It had to be the exact same model as the company does have pre-trained weights for this exact model). However, Unity only supports ONNX so I exported the model as an ONNX model, using the code provided in the repo:
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DL for the Web: Repository of Models
Github Projects offering pretrained weights and train / run scripts. Example
- [D] yolov7 not finding GPU device: Solution
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yolov7-pose: What does the output layers of an exported onnx model mean?
I played around with the demo code of human pose estimation of the yolov7 model (https://github.com/WongKinYiu/yolov7/tree/pose) and wanted to convert this to onnx format in order to continue in a C++ environment.
- [P] Any object detection library
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I made the “AI invisibility cloak." Ask AI expert Tom Goldstein about security and safety of AI systems, and how to hack them.
I would add that Yolo has evolved over time, and variants of the architecture continue to come out today. Here's one that came out this summer: https://github.com/WongKinYiu/yolov7
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What is the correct strides when add decoding level to a mlmodel converted from yolov7
there is a trained custom model with yolov7 that was converted to mlmodel with export.py (from the yolov7 repository: https://github.com/WongKinYiu/yolov7).
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Use YOLOv5 tensorflow.js models to speed up annotation
Hi u/DDDqp! YOLOv7 is for sure on my list. Problem is that, as it is right now YOLOv7 does not offer export to tensorflow.js. I actually created the issue by asking if they plan to add that export: https://github.com/WongKinYiu/yolov7/issues/885 No response yet. But I think it is more than possible. I can even work on that export for them. If they would have exported to tfjs, than I most certainly can work on the NPM package.
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DeepSort with PyTorch(support yolo series)
WongKinYiu/yolov7
What are some alternatives?
When comparing XMem and yolov7 you can also consider the following projects:
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
edgetpu - Coral issue tracker (and legacy Edge TPU API source)
edgetpu-yolo - Minimal-dependency Yolov5 export and inference demonstration for the Google Coral EdgeTPU
YOLOv4 - Port of YOLOv4 to C# + TensorFlow
darknet - Convolutional Neural Networks
BCNet - Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]
CATNet - 🛰️ Learning to Aggregate Multi-Scale Context for Instance Segmentation in Remote Sensing Images (arXiv 2021)
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
YOLOv6 - YOLOv6: a single-stage object detection framework dedicated to industrial applications.
Cream - This is a collection of our NAS and Vision Transformer work. [Moved to: https://github.com/microsoft/AutoML]
yolact - A simple, fully convolutional model for real-time instance segmentation.
deeplab2 - DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a unified and state-of-the-art TensorFlow codebase for dense pixel labeling tasks.