WALDOv3.0 complete pack
W.A.L.D.O. AI
Whereabouts Ascertainment for Low-lying Detectable Objects
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Welcome to the set of WALDO v3.0 AI models
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WHAT IS WALDO?
WALDO is a a set of detection AI models, based on a large YOLO-v8 backbone and my own
synthetic data pipeline. The model is capable of detecting these classes
of items in overhead imagery ranging in altitude from about 30 feet to
satellite imagery!
Output classes:
0 -> 'LightVehicle' --> all kinds of civilan cars, including pickup trucks, vans etc... 🚗🏎️🚓🚐🚑 </br>
1 -> 'Person' --> people! all kinds of people including ones that are on bikes or swimming in the sea 🧍♀️🕺💃🧜🏽♀️🏂🧞</br>
2 -> 'Building' --> all kinds of buildings 🕌🏛️🏭🏡</br>
3 -> 'UPole' --> utility poles, power poles, anything thin and sticking up that you should avoid with a drone 🎏</br>
4 -> 'Boat' --> boats, ships, canoes, kayaks, surf boards... all the floaty stuff 🚢🏄</br>
5 -> 'Bike' --> bikes, mopeds, motorbikes, all stuff with 2 wheels 🚲</br>
6 -> 'Container' --> shipping containers, including on the back of an articulated truck... 📦🏗️</br>
7 -> 'Truck' --> large commercial vehicles including articulated trucks or big box-on-chassis delivery trucks 🚚</br>
8 -> 'Gastank'--> cylindrical tanks such as butane tanks and gas expansion tanks, or grain silos... pretty much anything that looks cylindrical for storing liquids 🫙</br>
10 -> 'Digger' --> all kinds of construction vehicles, including tractors and construction gear 🚜</br>
11 -> 'Solarpanels' --> solar panels ▪️🌞▪️</br>
12 -> 'Bus' --> a bus 🚌</br>
--> In general the lower the class number the better-trained you can expect it to be.
For users of previous versions of WALDO: note that I removed the military class and smoke detection. This is meant to be a FOSS tool for civilian use and I don't want to pursue making it work for military applications.
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WHERE IS WALDO?
Right here on Gumroad!
There is a smaller set of models on Huggingface, but this set is the complete release and includes P2 variants which perform quite a lot better especially for smaller model sizes and especially on smaller objects.
They have a few more parameters but IMO especially for this use case of overhead detection these models are well worth the trade-off!
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WHAT IS IT GOOD FOR?
People are currently using versions of WALDO for:
1. disaster recovery
2. monitoring wildlife sanctuaries (intruder detection)
3. occupancy calculation (parking lots etc..)
4. monitoring infrastructure
5. construction site monitoring
6. traffic flow management
7. crowd counting
8. some fun AI art applications!
9. drone safety (avoiding people / cars on the ground)
10. lots of other fun stuff...
The main reason for me to make WALDO free has in fact been discovering all these cool applications. Let me know what you build!
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FOR AI NERDS !
It's a set of YOLOv8 model, trained on my own datasets of synthetic and "augmented" / semi-synthetic data.
I'm not going to release the dataset for the time being.
The weights are completely open, allowing you to deploy in any number of ways this time!
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HOW CAN I START WITH WALDO?
Check out the boilerplate code in the repo to run the models and output pretty detections using the wonderful Supervision annotation library from Roboflow :)
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GOING DEEPER
Of course if you know your way around deploying AI models there is a lot more you do
with this release, inclusing:
1. fine-tuning the models on your own data (if you know what you are doing, this is probably your starting point)
2. building a nicely optimized sliding-window inference setup that works nicely on your edge hardware
3. quantizing the models for super-duper edge performance on cheap devices
4. using the models to annotate your own data and train something of your own!
Enjoy!
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PREVIOUS VERSIONS
I am retiring the old versions, this is the only one that will stay online.
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CAN YOU HELP ME WITH X?
Sure, email me at stephan.sturges@gmail.com
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DETECTION OF X ISN'T WORKING AS EXPECTED:
I'd love to see example images, videos, sample data, etc at:
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SUPPORT WALDO!
Visit --gumroad-- to support the project!
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LICENSE
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Unless otherwise specified all code in this release is published with the
licence conditions below.
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MIT License
Copyright (c) 2024 Stephan Sturges / Aircortex.com
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
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The above copyright notice and this permission notice shall be included in all
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
the complete set of AI models