ultralytics
harlequin
ultralytics | harlequin | |
---|---|---|
27 | 13 | |
22,973 | 2,471 | |
7.1% | - | |
9.8 | 9.3 | |
4 days ago | 4 days ago | |
Python | Python | |
GNU Affero General Public License v3.0 | MIT License |
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.
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
harlequin
- DBeaver – open-source Database client
- FLaNK Stack 29 Jan 2024
- FLaNK Weekly 08 Jan 2024
- Harlequin: SQL IDE for Your Terminal
- Harlequin: DuckDB IDE for the terminal
- Harlequin.sh DuckDB IDE for your terminal
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Show HN: Harlequin, the DuckDB IDE for Your Terminal
For the past four months I've been working (part-time, this is OSS after all) on Harlequin, a SQL IDE for DuckDB that runs in your terminal. I built this because I work in Data, and I found myself often reaching for the DuckDB CLI to quickly query CSV or Parquet data, but then hitting a wall when using the DuckDB CLI as my queries got more complex and my result sets got larger.
Harlequin is a drop-in replacement for the DuckDB CLI that runs in any terminal (even over SSH), but adds a browsable data catalog, full-powered text editor (with multiple buffer support), and a scrollable results viewer that can display thousands of records.
Harlequin is written in Python, using the Textual framework. It's licensed under MIT.
Today I released v1.0.0, and I'm excited to share Harlequin with HN for the first time. You can try it out with `pip install harlequin`, or visit https://harlequin.sh for docs and other info.
- FLaNK Stack Weekly for 07August2023
What are some alternatives?
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.
hugging-chat-api - HuggingChat Python API🤗
super-gradients - Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
opensms - Open-source solution to programmatically send and receive SMS using your own SIM cards
yolo_tracking - BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models
llama2_aided_tesseract - Enhance Tesseract OCR output for scanned PDFs by applying Large Language Model (LLM) corrections, complete with options for text validation and hallucination filtering.
GroundingDINO - Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
OpenBuddy - Open Multilingual Chatbot for Everyone
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/Auto-GPT]
examples - Analyze the unstructured data with Towhee, such as reverse image search, reverse video search, audio classification, question and answer systems, molecular search, etc.
yolov8_onnx_python - YOLOv8 inference using Python
textadept - Textadept is a fast, minimalist, and remarkably extensible cross-platform text editor for programmers.