GroundingDINO
super-gradients
GroundingDINO | super-gradients | |
---|---|---|
5 | 8 | |
5,075 | 4,343 | |
8.3% | 1.6% | |
6.3 | 9.5 | |
9 days ago | 6 days ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | 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.
GroundingDINO
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Autodistill: A new way to create CV models
Some of the foundation/base models include: * GroundedSAM (Segment Anything Model) * DETIC * GroundingDINO
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Is there a way to do segmentation of a person's clothing?
While Segment Anything can detect objects based on text prompts, that's not its strong suite. To get best results, folks usually combine it with Grounding DINO, which is a great object detection model. You run Grounding DINO with text prompt "skirt", this gives you a bounding box that you pass to Segment Anything, which gives you a segmentation mask that you can then use for inpainting with SD.
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Searching for Guidance on Developing an AI Bot for SSBU Training
Now, let's delve into the technological aspects of this project. The combination of Facebook's Segment Anything and Grounding Dino tools will automate annotations for image processing, which is key to this AI endeavor. I'm also intrigued by Mojo, a new programming language designed specifically for AI developers, which will soon be open-source.
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[D] Object Detection Machine Learning
Right now we are trying out grouding dino on this but it is giving a lot of noise and detecting things that are not cracks.
- [D] Data Annotation Done by Machine Learning/AI?
super-gradients
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Zero-Shot Prediction Plugin for FiftyOne
Most computer vision models are trained to predict on a preset list of label classes. In object detection, for instance, many of the most popular models like YOLOv8 and YOLO-NAS are pretrained with the classes from the MS COCO dataset. If you download the weights checkpoints for these models and run prediction on your dataset, you will generate object detection bounding boxes for the 80 COCO classes.
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Open Source Advent Fun Wraps Up!
23. SuperGradients | Github | tutorial
- FLaNK Stack Weekly 06 Nov 2023
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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
- FLaNK Stack for 15 May 2023
- GitHub - Deci-AI/super-gradients: Easily train or fine-tune SOTA co...GitHub - Deci-AI/super-gradients: Easily train or fine-tune SOTA co...
- Meet YOLO-NAS: An Open-Sourced YOLO-based Architecture Redefining State-of-the-Art in Object Detection
- FLiPN-FLaNK Stack Weekly May 8 2023
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.
ultralytics - NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
Detic - Code release for "Detecting Twenty-thousand Classes using Image-level Supervision".
SegGradCAM - SEG-GRAD-CAM: Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping
highstorm - Open Source Event Monitoring
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
openvino_notebooks - 📚 Jupyter notebook tutorials for OpenVINO™
SmashBot - The AI that beats you at Melee
pyvideotrans - Translate the video from one language to another and add dubbing. 将视频从一种语言翻译为另一种语言,并添加配音
LAVIS - LAVIS - A One-stop Library for Language-Vision Intelligence