SSH-Snake
ultralytics
| SSH-Snake | ultralytics | |
|---|---|---|
| 7 | 27 | |
| 1,818 | 23,574 | |
| - | 8.1% | |
| 7.7 | 9.8 | |
| 3 months ago | about 13 hours ago | |
| Shell | Python | |
| GNU Affero General Public License v3.0 | GNU Affero General Public License v3.0 |
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.
SSH-Snake
- FLaNK Weekly 08 Jan 2024
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SSH-Snake: Automated SSH-Based Network Traversal
Assuming you mean `known_hosts`, no. It uses various data sources to determine where to try to connect with discovered keys: https://github.com/MegaManSec/SSH-Snake/blob/main/SETTINGS.m... lists all of them (which can be enabled and disabled by the user). https://github.com/MegaManSec/SSH-Snake/blob/main/SETTINGS.m... is particularly interesting.
- Show HN: SSH-Snake: Automated SSH-Based Network Traversal
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A Canadian payroll dependency chart
Doing a bit more digging, it's using cytoscape[0] which is similar to graphviz. If you search your favorite search engine with "Cytoscape Session Viewer", you'll find many websites displaying the same type of graphs (select layout: circle).
FYI, circo doesn't always output a circle. I recently created https://github.com/MegaManSec/SSH-Snake/blob/main/tools/SSH-... using circo.
[0] https://cytoscape.org/
ultralytics
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The CEO of Ultralytics (yolov8) using LLMs to engage with commenters on GitHub
Yep, I noticed this a while ago. It posts easily identifiable ChatGPT responses. It also posts garbage wrong answers which makes it worse than useless. Totally disrespectful to the userbase.
https://github.com/ultralytics/ultralytics/issues/5748#issue...
- FLaNK Weekly 08 Jan 2024
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My kid sounds like ChatGPT, and soon yours might, too
There are obvious places it is being used that I have noticed organically. For instance, check out the answers in this repo:
https://github.com/ultralytics/ultralytics/issues/5748#issue...
If you read the answers there, the style of answering is always to repeat the question in a very specific way. Once you see it you can’t in-see it.
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
When browsing the state-of-the-art in object detection on Papers with Code, I found the YOLO model to be one of the most popular, accurate, and fastest. That being said, I would recommend having a look at Ultralytics, which provides the tools to evaluate, predict, and export the latest versions of YOLO models with only a few lines of code.
- Instance segmentation of small objects in grainy drone imagery
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Breaking the Myth: Object Detection Isn't Hard as Thought
YOLOv8 (You Only Look Once) is an open-source Computer Vision AI model released on January 10th, 2023. It’s called YOLO because it detects everything inside an image in a single pass. The new version can perform image detection, classification, instance segmentation, tracking, and pose estimation tasks.
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How I use "AI" to entertain my cat
Next, I needed to figure out, how can I access the stream, recognize an animal, then let Max know? There are tons of examples of recognizing an object via camera frames, but I ultimately found this python library called ultralytics that supports RTSP streams and classifying objects in the video frames using pre-built models. The docs looked like it would be pretty low effort, so after some experimentation, I was successful in having the ultralytics library recognize objects from my cheap camera!
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How to load the optimizer state_dicts in yolov8?
I have created an issue in their Github as well but so far not much help has been recieved. You can check that here
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Autodistill: A new way to create CV models
And the target models include: * YOLOv8 (You Only Look Once) * YOLO-NAS * YOLOv5 * and DETR
What are some alternatives?
dns.toys - A DNS server that offers useful utilities and services over the DNS protocol. Weather, world time, unit conversion etc.
segment-anything - The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
durdraw - Versatile ASCII and ANSI Art text editor for drawing in the Linux/Unix/macOS terminal, with animation, 256 and 16 colors, Unicode and CP437, and customizable themes
super-gradients - Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
container2wasm - Container to WASM converter
yolo_tracking - BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models
hyperfine - A command-line benchmarking tool
GroundingDINO - Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
csvlens - Command line csv viewer
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/Auto-GPT]
DeathStar - Uses Empire's (https://github.com/BC-SECURITY/Empire) RESTful API to automate gaining Domain and/or Enterprise Admin rights in Active Directory environments using some of the most common offensive TTPs.
yolov8_onnx_python - YOLOv8 inference using Python