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YOLO-World: Real-Time Open-Vocabulary Object Detection
- AndrewKemendo 1y agoWe’ve tested this in our production environment on mobile robots (think quadcopter and ground UGV) and it works really nicely
- TechDebtDevin 1y agoIf this is military related, im terrified of the future. Sci-fi movies with crazy drones from back when are no longer that cute.
- jiggawatts 1y agoThe truly scary part is that it’s a straightforward evolution from this to 1000 fps hyperspectral sensors. There will be no hiding from these things and no possibility of evasion. They’ll have agility exceeding champion drone pilots and be too small to even see or hear until it’s far too late. Life in the Donbass trenches is already hell. We’ll find a way to make it worse.
- MoonGhost 1y agoThen it should be possible to use them to counter and defend. Think of AI powered interceptor drones patrolling the area, anti-drone light machine guns.
- collingreen 1y agoAs long as you keep paying your gemini anti-drone bill and don't set account limits you'll be fine! </s>
- AndrewKemendo 1y agoYou’re right to be terrified
- echelon 1y ago7 years ago, this felt like science fiction: https://www.youtube.com/watch?v=HipTO_7mUOw https://www.youtube.com/watch?v=HipTO_7mUOw Now that we've seen the use of drones in the Ukraine war, 10k+ drone light shows, Waymo's autonomous cars, and tons of AI advancements in signals processing and planning, this seems obvious.
- yard2010 1y agoThis is important. I don't want to live on this planet anymore.
- Flemlo 1y agoWe have nuclear weapons. We already achieved complete destruction potential. Drones don't change much. It's potentially better for us civilians if drones get used to attack a lot more targeted (think Putin). This should lead to narrow policies which might be less aggressive
- MoonGhost 1y ago> potentially better for us civilians if drones get used to attack a lot more targeted (think Putin Putin is well protected, way better than US presidents and candidates. With lower prices and barriers it can actually be you, or any low profile target. Luckily real terrorist are mostly uneducated.
- bevenky 1y agoIs this OSS?
- T-A 1y agohttps://github.com/AILab-CVC/YOLO-World https://github.com/AILab-CVC/YOLO-World
- fc417fc802 1y agoUnclear exactly what you're asking. The linked paper describes an algorithm (patent status unclear). That paper happens to link to a GPL licensed implementation whose authors explicitly solicit business licensing inquiries. The related model weights are available on Hugging Face (license unclear). Notably the HF readme file contains conflicting claims. The metadata block specifies apache while the body specifies GPL. https://github.com/AILab-CVC/YOLO-World https://github.com/AILab-CVC/YOLO-World https://huggingface.co/spaces/stevengrove/YOLO-World/tree/main https://huggingface.co/spaces/stevengrove/YOLO-World/tree/ma...
- sigmoid10 1y agoThe paper says it is based on YOLOv8, which uses the even stricter AGPL-3.0. That means you can use it commercially, but all derived code (even in a cloud service) must be made open source as well.
- fc417fc802 1y agoI assume they refer to the academic basis for the algorithm rather than the implementation itself. Slightly unrelated, how does AGPL work when applied to model weights? It seems plausible that a service could be structured to have pluggable models on the backend. Would that be sufficient to avoid triggering it?
- kouteiheika 1y agoThey probably mean the algorithm, but nevertheless the YOLO models are relatively simple so if you know what you're doing it's pretty easy to reimplement them from scratch and avoid the AGPL license for code. I did so once for the YOLOv11 model myself, so I assume any researcher worth their salt would also be able to do so too if they wanted to commercialize a similar architecture.
- ed 1y agoNeat. Wonder how this compares to Segment Anything (SAM), which also does zero-shot segmentation and performs pretty well in my experience.
- ipsum2 1y agoSAM doesn't do open vocabulary i.e. it segments things without knowing the name of the object, so you can't ask it to do "highlight the grapes", you have to give it an example of a grape first.
- stevepotter 1y agoTry this: https://github.com/luca-medeiros/lang-segment-anything https://github.com/luca-medeiros/lang-segment-anything
- ipsum2 1y agoThis uses GroundingDINO for open vocabulary, separate model. Useful nonetheless, but means you're running a lot of model inference for a single image.
- deleted 1y ago[deleted]
- RugnirViking 1y agoYOLO is way faster. We used to run both, with YOLO finding candidate bounding boxes and SAM segmenting just those. For what it's worth, YOLO has been a standard in image processing for ages at this point, with dozens of variations on the algorithm (yolov3, yolov5, yolov6, etc) and this is yet another new one. Looks great tho SAM wouldn't run under 1000ms per frame for most reasonable image sizes
- euazOn 1y agoJust as a quick demo, here is an example of YOLO-World combined with EfficientSAM: https://youtu.be/X7gKBGVz4vs?t=980 https://youtu.be/X7gKBGVz4vs?t=980
- silentsea90 1y agoQ. Any of you know models that do well at deleting objects from an image i.e. inpainting with mask with intention to replace mask with background? Whatever I've tried so far leaves a smudge (eg. LaMa)
- GaggiX 1y agoThere are plenty of Stable Diffusion based models that are capable of inpainting, of course they are heavier to run than LaMa.
- silentsea90 1y agoMy question wasn't about inpainting but eraser inpainting models. Most inpainting models replace objects instead of erasing them even though the prompt shares an intent to delete
- deleted 1y ago[deleted]
- jokethrowaway 1y agoYou can build a pipeline where you use: GroundingDino (description to object detection) -> SAM (segmenting) -> Stable Diffusion model (inpainting, I do mainly real photo so I like to start with realisticVisionV60B1_v51HyperVAE-inpainting and then swap if I have some special use case) For higher quality at a higher cost of VRAM, you can also use Flux.1 Fill to do inpainting. Lastly, Flux.1 Kontext [dev] is going to be released soon and it promises to replace the entire flow (and with better prompt understanding). HN thread here: https://news.ycombinator.com/item?id=44128322 https://news.ycombinator.com/item?id=44128322
- silentsea90 1y agoThanks! I do use GroundingDino + SAM2, but haven't tried realisticVisionV60B1_v51HyperVAE-inpainting! Will do! And will try flux kontext too. Thanks!
- pavl 1y agoThis looks so good! Will it be available on replicate?
- greesil 1y agoI've got big plans for this for an automated geese scaring system
- zachflower 1y agoFunnily enough, that was my computer science capstone project back in 2010! I don’t know if our project sponsor ever got the company off the ground, but the basic idea was an automated system to scare geese off of golf courses without also activating in the middle of someone’s backswing.
- greesil 1y agoIf someone can sell it for $100 they'd make some serious money. The birds are fouling my pool, and the plastic owl does nothing. Right now I'm thinking it should make a loud noise, or launch a tennis ball randomly. The best part is I can have it disarm if it sees a person.
- joshwa 1y agoMy thought is just to rent it out for to rich folks with lawns for a few hundred bucks a week. My contraption will have thermal detection, AI target discrimination, and precision targeting with a laminar flow water stream. That’s the plan, anyways.
- mattlondon 1y agoSame here but for urban foxes. We had motion triggered sprinklers that worked great, but they did not differentiate between foxes and 4 year old children if I forgot to turn them off haha. We have more or less 360 degrees CCTV coverage of the garden via 7 or 8 CCTV cameras so rough plan is to have basic motion pixel detection to detect frames with something happening then fire those frames off for inference (rather than trying to stream all video feeds through the algorithm 24/7) and turn the sprinklers on. Hope to get to about 500ms end-to-end latency from detection to sprinklers/tap activated to cement the "causality" of stepping into the garden and then ~immediately getting soaked and scared in the foxes brains. Most latency will be for the water to physically move and make the sprinklers start, but that is another issue really. Probably will use a RPi 5 + AI Hat as the main local inference provider, and ZigBee controlled valve solenoid on the hose tap.
- serf 1y agonot to be a grump, but why was this posted recently? Has something changed? Yolo-world has been around for a bit now.
- deleted 1y ago[deleted]
- 3vidence 1y agoThe setback of YOLO architectures is that they use predefined object categories that are a part of the training process. If you want to adapt YOLO to a new domain you need to retrain it with your new category label. This work presents a version of YOLO that can work on new categories without needing to retrain the algorithm, but instead having a real-time "dictionary" of examples that you can seemlessly update. Seems like a very useful algorithm to me. Edit: apologies i misread your comment I thought it was asking why this is different that regular YOLO
- greesil 1y agoIt was new to me, serf. And judging by the number of upvotes, it was new to a few other people too.
- jimmydoe 1y agothis is one year old. wonder why post now.
- MoonGhost 1y agoOld stuff is often reposted here to attract attention. It mostly goes unnoticed.
- saithound 1y agoNeeds (2024) in the title.