GroundingDINO
LAVIS
GroundingDINO | LAVIS | |
---|---|---|
5 | 18 | |
5,075 | 8,781 | |
8.3% | 2.9% | |
6.3 | 6.3 | |
8 days ago | 23 days ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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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?
LAVIS
- FLaNK AI for 11 March 2024
- FLaNK 04 March 2024
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[D] Why is most Open Source AI happening outside the USA?
For multimodal, there's China (*many), then Salesforce.
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Need help for a colab notebook running Lavis blip2_instruct_vicuna13b?
Been trying for all day to get a working inference for this example: https://github.com/salesforce/LAVIS/tree/main/projects/instructblip
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most sane web3 job listing
There's also been big breakthroughs in computer vision. Not that long ago it was hard to recognize if a photo contained a bird; that's solved now by models like CLIP, Yolo, or Segment Anything. Now research has moved on to generating 3D scenes from images or interactively answering questions about images.
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I work at a non-tech company and have been asked to make software that is impossible. How do I explain it to my boss?
The new hotness is multimodal vision-language models like InstructBLIP that can interactively answer questions about images. Check out the examples in the github repo, I would not have thought this was possible a few years ago.
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Two-minute Daily AI Update (Date: 5/15/2023)
Salesforce’s BLIP family has a new member– InstructBLIP, a vision-language instruction-tuning framework using BLIP-2 models. It has achieved state-of-the-art zero-shot generalization performance on a wide range of vision-language tasks, substantially outperforming BLIP-2 and Flamingo. (Source)
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InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
Github
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Can I use my own art as a training set?
Most of my workflows are self-made. For captioning I used Blip-2 in a custom script I made that automates the process by going into directories and their sub-directories and creates a .txt file beside each image. This way I can keep my images organized in their proper directories, without having to put dump them all in a single place.
- FLiP Stack Weekly for 13-Feb-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.
pytorch-widedeep - A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch
Detic - Code release for "Detecting Twenty-thousand Classes using Image-level Supervision".
CLIP-Caption-Reward - PyTorch code for "Fine-grained Image Captioning with CLIP Reward" (Findings of NAACL 2022)
ultralytics - NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
sparseml - Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
robo-vln - Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"
SmashBot - The AI that beats you at Melee
DeepViewAgg - [CVPR'22 Best Paper Finalist] Official PyTorch implementation of the method presented in "Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation"
super-gradients - Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
linkis - Apache Linkis builds a computation middleware layer to facilitate connection, governance and orchestration between the upper applications and the underlying data engines.