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GroundingDINO
Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
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Grounded-Segment-Anything
Grounded-SAM: Marrying Grounding-DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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.
Grounded SAM is a project that tries to combine these steps in a single workflow, but I am not sure how far it has come along. Might be worth checking out, but it also isn't too difficult to combine the three models by hand.