Controlling weeds, precisely. The latest in precision weed control research from the @Sydney_Uni Weeds Research Team in Narrabri and Camden.
Narrabri, New South Wales
Joined July 2018
- Tweets380
- Following256
- Followers1K
- Likes481
Precision Weed Control Lab retweeted
About 50 years ago, the tech behind reflectance-based 'green-on-brown' sprayers was published.
Since then a lot (!) has changed.
We went through ~175 papers from the last 50 years of weed recognition research for this review.
cambridge.org/core/journals/…
Precision Weed Control Lab retweeted
The OpenWeedLocator demo unit will be at the @MsfMallee Future of Weed Detection Expo in Karoonda next week.
A great opportunity to get hands on experience with how image-based weed detection works and DIY units.
@KMatthewson_22 @AgriFuturesAU
Precision Weed Control Lab retweeted
Just finished assembling the compact OWL or OWLet, after some great feedback during the @MingenewExpo.
Fits inside 125 x 75 x 3mm RHS steel for smash protection, same features as the big OWL.
Designs/assembly guide to follow!
Precision Weed Control Lab retweeted
This machine’s algorithm is capable of distinguishing between #BroadleafWeeds, #GrassWeeds, and #ginger with a great level of accuracy and is helping to detect and spray for #weeds in a ginger crop. To read more about this project, visit bit.ly/3o0cmJK
Precision Weed Control Lab retweeted
To pass the 100th commit🥳for the #OpenWeedLocator, we've released an improved image sampling tool. Now you can save whole images, cropped bounding boxes around the detections or cropped squares.
To collect images - just plug in a USB, set it up and go!
github.com/geezacoleman/Open…
Precision Weed Control Lab retweeted
Really enjoyed writing this article for @nozzle_guy and @Spray_Guy!
Check it out if you're interested in the tech behind camera sprayers, where it all started and how an #opensource approach will help it succeed.
@Sydney_Science @SiaSydney @WeedSmartAU
. @Spray_Guy and I are excited to have @GeezaColeman as a guest author on #Sprayers101 with his take on optical spot sprays and the evolution of the technology. A must read if you want to know how #MachineLearning works and fits into ag.
sprayers101.com/computers-an…
Precision Weed Control Lab retweeted
@GeezaColeman & @WeedAI_news are seeking growers to join a beta testing group for feedback user experience.
📷 All you need are the images to upload.
DM @GeezaColeman if you're interested in participating teapawt.net/GeezaColeman/s…
We're looking for growers to join a beta testing group @WeedAI_news, for feedback on the user experience - you'd just need to have images to annotate/upload.
We'll form an ongoing group around opensource weed recognition too.
Let me know if you're interested!
@HenryLydecker
Precision Weed Control Lab retweeted
We're looking for growers to join a beta testing group @WeedAI_news, for feedback on the user experience - you'd just need to have images to annotate/upload.
We'll form an ongoing group around opensource weed recognition too.
Let me know if you're interested!
@HenryLydecker
Precision Weed Control Lab retweeted
Great to see them go out to a good home👍🏼 one rig working and another 3 coming – at Dubbo, New South Wales
Precision Weed Control Lab retweeted
The first dataset with fireweed was just uploaded to @WeedAI_news!
A small dataset of fireweed at both vegetative and flowering growth stages collected with the Sony Alpha A7R IV A, providing 61MP per image.
21/
Dataset name: Brownlow Hill Fireweed
Classes: 1 (Senecio madagascariensis)
Annotation type: bounding box
Image count: 20
weed-ai.sydney.edu.au/datase…
ALT Fireweed plant in green pasture
Precision Weed Control Lab retweeted
🚨🌱New dataset!
This 552 image dataset of wild radish in wheat is the first on @WeedAI_news that makes use of the new weed growth stage/plant part specification.
Plus Weed-AI now has dataset editing & version control functionality too.
@SiaSydney @Sydney_CRF
21/
Dataset name: RadishWheatDataset
Classes 4 (4 growth stages of R. raphanistrum in wheat)
Annotation type: bounding box
Image count: 552 (1012 boxes)
weed-ai.sydney.edu.au/datase…
Precision Weed Control Lab retweeted
Spot the difference:
One collected at 5km/h, the other at 30km/h, dust and all. Both with the #OpenWeedLocator software.
Precision Weed Control Lab retweeted
Had a great time giving this OWL assembly/demo with @williamtsalter & Gus!
Hopefully demonstrated the whole development process: parts to paddock.
Glad nothing too major went awry!
We’re about to start our OpenWeedLocator live assembly and demonstration with @GeezaColeman at the helm 🎥🎙
Precision Weed Control Lab retweeted
We’re about to start our OpenWeedLocator live assembly and demonstration with @GeezaColeman at the helm 🎥🎙 – at New South Wales, Australia
Precision Weed Control Lab retweeted
A university of OWLs, showing the changes in design since way back in 2019 when I first built an enclosure.
If you want to learn how to build an OWL & see a live demo, it's all happening on Wed May 4th, 12 - 1:30pm AEST.
Register here:
eventbrite.com.au/e/openweed…
@williamtsalter
Precision Weed Control Lab retweeted
weed-ai.sydney.edu.au/ is an open data platform that the Sydney Informatics Hub is building to enable R&D into computer vision methods to identify and control weeds. It's great to see new data coming into the system!
Precision Weed Control Lab retweeted
🚨🌱new dataset!
If you're interested in a project for broadleaf weed recognition in your lawn, this might be a good place to start.
567 instances of weeds (rather unbalanced)
78 images
Perfect to get a YOLOv5 model up and running.
20/
Dataset name: Broadleaf Weeds in Common Couch
Classes: 3 (T. officinale, E. bonariensis, S. oleraceus)
Annotation type: bounding box
Image count: 78
weed-ai.sydney.edu.au/datase…
Precision Weed Control Lab retweeted
Images are everything in #deeplearning!
E.g. #ImageNet has >14 M images in 20k classes. Nothing of the same scale exists for weeds (@WeedAI_news is trying!) but there are open datasets.
For weed recognition, here's a 🧵of all weeds datasets I've found.
📸🌱🧵
Precision Weed Control Lab retweeted
Recognising blue lupins in narrow leaf lupins near Geraldton, WA
YOLOv5 L trained on 217 images from @WeedAI_news dataset. Training images are younger/yellower soil, so quite a few false detections here.
weed-ai.sydney.edu.au/datase…
@nick_mckenna1
Precision Weed Control Lab retweeted
Laser weeding ⚡️
@MarkSaundeye and @1800weevil talked about this targeted non-herbicide tool in our webinar on precision weed control.
To find out more about the tech, check out @weedcontrollab / @geezecoleman and watch our webinar in full here ➡️ buff.ly/3pWuhTd