👁️ Computer Vision, Image Processing, OpenCV & Deep Learning in Python!
Professional computer vision solutions with OpenCV and deep learning — accurate image processing built for real-world applications.
go.fiverr.com/visit/?bta=2...
#ComputerVision #OpenCV #DeepLearning #ImageProcessing #Python
Professional computer vision solutions with OpenCV and deep learning — accurate image processing built for real-world applications.
go.fiverr.com/visit/?bta=2...
#ComputerVision #OpenCV #DeepLearning #ImageProcessing #Python
September 28, 2026 at 7:51 PM
👁️ Computer Vision, Image Processing, OpenCV & Deep Learning in Python!
Professional computer vision solutions with OpenCV and deep learning — accurate image processing built for real-world applications.
go.fiverr.com/visit/?bta=2...
#ComputerVision #OpenCV #DeepLearning #ImageProcessing #Python
Professional computer vision solutions with OpenCV and deep learning — accurate image processing built for real-world applications.
go.fiverr.com/visit/?bta=2...
#ComputerVision #OpenCV #DeepLearning #ImageProcessing #Python
OpenCV smeared the plate when I tried to pull the warrior out. Had to image-edit a clean background so he could get knocked back on his own.
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Subscribe for the full breakdown: beginnersinai.com/subscribe
Follow @BeginnersinAI for the next one.
September 28, 2026 at 5:14 PM
OpenCV smeared the plate when I tried to pull the warrior out. Had to image-edit a clean background so he could get knocked back on his own.
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Follow @BeginnersinAI for the next one.
Subscribe for the full breakdown: beginnersinai.com/subscribe
Follow @BeginnersinAI for the next one.
Classifier latency (local dataset)
* P01: 37ms
* P50: 59ms
* P99: 71ms
> Pure math over extra LLM passes
#python #opencv #vlm #localfirst #systems
* P01: 37ms
* P50: 59ms
* P99: 71ms
> Pure math over extra LLM passes
#python #opencv #vlm #localfirst #systems
September 28, 2026 at 11:43 AM
Classifier latency (local dataset)
* P01: 37ms
* P50: 59ms
* P99: 71ms
> Pure math over extra LLM passes
#python #opencv #vlm #localfirst #systems
* P01: 37ms
* P50: 59ms
* P99: 71ms
> Pure math over extra LLM passes
#python #opencv #vlm #localfirst #systems
Cut token consumption by 88% with deterministic image routing (P50: 59ms)
Attaching raw images to VLM context wastes VRAM and tokens when an image is mostly text.
In my VEX runtime, a 58 LOC OpenCV pre-pass inspects images beforehand and routes text to OCR instead of raw pixels.
Attaching raw images to VLM context wastes VRAM and tokens when an image is mostly text.
In my VEX runtime, a 58 LOC OpenCV pre-pass inspects images beforehand and routes text to OCR instead of raw pixels.
September 28, 2026 at 11:43 AM
Cut token consumption by 88% with deterministic image routing (P50: 59ms)
Attaching raw images to VLM context wastes VRAM and tokens when an image is mostly text.
In my VEX runtime, a 58 LOC OpenCV pre-pass inspects images beforehand and routes text to OCR instead of raw pixels.
Attaching raw images to VLM context wastes VRAM and tokens when an image is mostly text.
In my VEX runtime, a 58 LOC OpenCV pre-pass inspects images beforehand and routes text to OCR instead of raw pixels.
Apparently it’s computer vision week over here. 😅
Currently collaborating on another CV project while also working on my own.
Somehow I keep ending up surrounded by cameras, tracking, and questionable amounts of OpenCV.
Currently collaborating on another CV project while also working on my own.
Somehow I keep ending up surrounded by cameras, tracking, and questionable amounts of OpenCV.
September 28, 2026 at 4:25 AM
Apparently it’s computer vision week over here. 😅
Currently collaborating on another CV project while also working on my own.
Somehow I keep ending up surrounded by cameras, tracking, and questionable amounts of OpenCV.
Currently collaborating on another CV project while also working on my own.
Somehow I keep ending up surrounded by cameras, tracking, and questionable amounts of OpenCV.
Reminds me a lot of OpenCV. I used it many years ago for a face detection prototype. I bet it has significantly improved since then.
OpenCV DNN Module: Deep Learning Inference in OpenCV 5
Run YOLO26 object detection and RF-DETR segmentation with OpenCV 5 DNN. Includes tested Python and C++ code, ONNX export steps, and CPU benchmarks.
opencv.org
September 27, 2026 at 8:21 PM
Reminds me a lot of OpenCV. I used it many years ago for a face detection prototype. I bet it has significantly improved since then.
Learn AI-Powered Image Analysis at your own pace!
#ComputationalBiology #DataAnalytics #DataScience #MachineLearning #BiomedicalEngineering #Bioinformatics #ComputerScience #Engineering #Statistics #ChatGPT #Jupyter #Linux #Python #R #Research #ResearchTraining #Instats
#ComputationalBiology #DataAnalytics #DataScience #MachineLearning #BiomedicalEngineering #Bioinformatics #ComputerScience #Engineering #Statistics #ChatGPT #Jupyter #Linux #Python #R #Research #ResearchTraining #Instats
AI-Powered Image Analysis - On-Demand
Join our one-day online workshop, AI-Powered Image Analysis, designed for PhD students, professors, and professional researchers working with biological, microscopy, high-throughput, or clinical imaging data. Led by Nikolay Oskolkov, Group Leader/PI at LIOS, this intensive hands-on seminar bridges deep learning theory and practical implementation, covering CNNs, transfer learning, UNet, Mask R-CNN, object detection, Bayesian uncertainty, GRAD-CAM interpretability, OpenCV, OTSU thresholding, and reproducible Python workflows in Jupyter on Linux. Participants will learn how to build publication-ready image analysis pipelines for classification, segmentation, detection, cell counting, morphometrics, and biologically meaningful model interpretation, while also using ChatGPT-assisted coding to accelerate prototyping, debugging, and documentation. The seminar includes live Zoom instruction, practical coding examples, access to recordings and materials for 30 days, a monitored Q&A forum, and an official Instats certificate of completion. Whether you are developing methods for a thesis, paper, grant, or research project, this workshop will help you turn complex image datasets into rigorous, reproducible, and publishable results.
#ComputationalBiology #DataAnalytics #DataScience #MachineLearning #BiomedicalEngineering #Bioinformatics #ComputerScience #Engineering #Statistics #ChatGPT #Jupyter #Linux #Python #R #Research #ResearchTraining #Instats
instats.org
September 27, 2026 at 1:27 AM
Learn AI-Powered Image Analysis at your own pace!
#ComputationalBiology #DataAnalytics #DataScience #MachineLearning #BiomedicalEngineering #Bioinformatics #ComputerScience #Engineering #Statistics #ChatGPT #Jupyter #Linux #Python #R #Research #ResearchTraining #Instats
#ComputationalBiology #DataAnalytics #DataScience #MachineLearning #BiomedicalEngineering #Bioinformatics #ComputerScience #Engineering #Statistics #ChatGPT #Jupyter #Linux #Python #R #Research #ResearchTraining #Instats
Now a lot of cleaning up to do to make that upstream-able.
Claude needed a moderate amount of guidance, at first it picked OpenCV T-API since move OpenCV CPU to OpenCV GPU only seems logical.
However one it found the 5X improvement, it kept getting stuck failing at improving the OpenCL usage.
Claude needed a moderate amount of guidance, at first it picked OpenCV T-API since move OpenCV CPU to OpenCV GPU only seems logical.
However one it found the 5X improvement, it kept getting stuck failing at improving the OpenCL usage.
September 26, 2026 at 2:10 PM
Now a lot of cleaning up to do to make that upstream-able.
Claude needed a moderate amount of guidance, at first it picked OpenCV T-API since move OpenCV CPU to OpenCV GPU only seems logical.
However one it found the 5X improvement, it kept getting stuck failing at improving the OpenCL usage.
Claude needed a moderate amount of guidance, at first it picked OpenCV T-API since move OpenCV CPU to OpenCV GPU only seems logical.
However one it found the 5X improvement, it kept getting stuck failing at improving the OpenCL usage.
OpenPnP GPU processing results:
- baseline, upstream's code, opencv on CPU + some java image kernels 100% CPU usage (1 core)
- OpenCV T-API (OpenCL) 20% CPU usage with lots of GPU driver CPU overhead
- Vulkan with command queue caching 5% CPU usage
20X performance improvement all done by claude.
- baseline, upstream's code, opencv on CPU + some java image kernels 100% CPU usage (1 core)
- OpenCV T-API (OpenCL) 20% CPU usage with lots of GPU driver CPU overhead
- Vulkan with command queue caching 5% CPU usage
20X performance improvement all done by claude.
September 26, 2026 at 2:10 PM
OpenPnP GPU processing results:
- baseline, upstream's code, opencv on CPU + some java image kernels 100% CPU usage (1 core)
- OpenCV T-API (OpenCL) 20% CPU usage with lots of GPU driver CPU overhead
- Vulkan with command queue caching 5% CPU usage
20X performance improvement all done by claude.
- baseline, upstream's code, opencv on CPU + some java image kernels 100% CPU usage (1 core)
- OpenCV T-API (OpenCL) 20% CPU usage with lots of GPU driver CPU overhead
- Vulkan with command queue caching 5% CPU usage
20X performance improvement all done by claude.
We just locked in our Fantasy Grounds (.mod) export pipeline! 🐉 The Masterwork Engine just parsed Mörk Borg tactical maps at exactly 50px with perfect wall vectors using OpenCV.
September 26, 2026 at 1:51 AM
We just locked in our Fantasy Grounds (.mod) export pipeline! 🐉 The Masterwork Engine just parsed Mörk Borg tactical maps at exactly 50px with perfect wall vectors using OpenCV.
At GM-Copilot Studios, we enforce rigid mathematical gates and strict schema validation using Lean 4, Pydantic, and OpenCV. The machine validates the machine, and the human only steps in when a structural invariant actually fails.
cmccombs01.github.io/GM-Copilot-Studios.github.io
cmccombs01.github.io/GM-Copilot-Studios.github.io
GM-Copilot Studios | TTRPG PDF to Foundry VTT & Roll20 Conversion
Turn your TTRPG rulebooks and adventure PDFs into ready-to-play Foundry VTT and Roll20 modules with zero manual data entry and zero AI hallucinations.
cmccombs01.github.io
September 25, 2026 at 7:38 PM
At GM-Copilot Studios, we enforce rigid mathematical gates and strict schema validation using Lean 4, Pydantic, and OpenCV. The machine validates the machine, and the human only steps in when a structural invariant actually fails.
cmccombs01.github.io/GM-Copilot-Studios.github.io
cmccombs01.github.io/GM-Copilot-Studios.github.io
Wrote a Linux driver for Shenzhen Betterlife (Blestech) BL8514A & BL8515 fingerprint sensors (USB ID 347d:0304 / 347d:0302).
Link: https://codeberg.org/Hebisenshi/betterlife-fingerprint/
Link: https://codeberg.org/Hebisenshi/betterlife-fingerprint/
betterlife-fingerprint
Blestech BL8514A/BL8515 fingerprint sensors (USB 347d:0304) using OpenCV SIFT+RANSAC, with native PAM and fprintd D-Bus bridge.
codeberg.org
September 25, 2026 at 6:47 PM
Wrote a Linux driver for Shenzhen Betterlife (Blestech) BL8514A & BL8515 fingerprint sensors (USB ID 347d:0304 / 347d:0302).
Link: https://codeberg.org/Hebisenshi/betterlife-fingerprint/
Link: https://codeberg.org/Hebisenshi/betterlife-fingerprint/
We route PDFs through Lean 4 math gates to perfectly map Bestiary XML nodes, then use OpenCV spatial mapping to inject .uvtt grid topologies directly into the image layers.
Zero hallucinations. Zero manual data entry.
Zero hallucinations. Zero manual data entry.
September 25, 2026 at 5:00 AM
We route PDFs through Lean 4 math gates to perfectly map Bestiary XML nodes, then use OpenCV spatial mapping to inject .uvtt grid topologies directly into the image layers.
Zero hallucinations. Zero manual data entry.
Zero hallucinations. Zero manual data entry.
We route your human-written PDFs through Lean 4 math gates to perfectly map Bestiary and Equipment XML nodes. Then, we use OpenCV spatial mapping to inject tactical grid topologies directly into the VTT image layers.
September 25, 2026 at 12:12 AM
We route your human-written PDFs through Lean 4 math gates to perfectly map Bestiary and Equipment XML nodes. Then, we use OpenCV spatial mapping to inject tactical grid topologies directly into the VTT image layers.
Manual data entry is the biggest bottleneck in tabletop publishing. Banning deterministic tools like OpenCV layout mapping doesn't protect art—it just burns out the artist.
Stop enforcing a manual labor tax on the creators you claim to protect.
Stop enforcing a manual labor tax on the creators you claim to protect.
September 24, 2026 at 11:01 PM
Manual data entry is the biggest bottleneck in tabletop publishing. Banning deterministic tools like OpenCV layout mapping doesn't protect art—it just burns out the artist.
Stop enforcing a manual labor tax on the creators you claim to protect.
Stop enforcing a manual labor tax on the creators you claim to protect.
Generative AI hallucinates text/art and steals creative jobs. Deterministic AI (like our pipeline) uses OpenCV to read layouts & Lean 4 math to verify rules. It just does the grueling VTT data-entry so indie publishers don't burn out.
September 24, 2026 at 10:56 PM
Generative AI hallucinates text/art and steals creative jobs. Deterministic AI (like our pipeline) uses OpenCV to read layouts & Lean 4 math to verify rules. It just does the grueling VTT data-entry so indie publishers don't burn out.
Spot on. That's exactly why we don't read left-to-right. OpenCV maps the page into a coordinate grid first. Sidebars get their own [x1, y1, x2, y2] bounding boxes and are extracted as separate JSON objects. The main text flow routes right past it. Zero ordering collisions.
September 24, 2026 at 10:55 PM
Spot on. That's exactly why we don't read left-to-right. OpenCV maps the page into a coordinate grid first. Sidebars get their own [x1, y1, x2, y2] bounding boxes and are extracted as separate JSON objects. The main text flow routes right past it. Zero ordering collisions.
Chi utilizza KDE Plasma può ora aggiungere lo sblocco facciale al proprio desktop Linux. Plasma Face Unlock sfrutta la webcam e OpenCV per riconoscere l’utente e gestire l’autenticazione. #KDE #KDEPlasma #Linux #Wayland #OpenSource #FaceUnlock www.linuxeasy.org/plasma-face-...
Plasma Face Unlock porta il riconoscimento facciale su KDE Plasma 6
Plasma Face Unlock porta il riconoscimento facciale su KDE Plasma 6 e Wayland per sbloccare lo schermo e autorizzare sudo.
www.linuxeasy.org
September 24, 2026 at 7:41 PM
Chi utilizza KDE Plasma può ora aggiungere lo sblocco facciale al proprio desktop Linux. Plasma Face Unlock sfrutta la webcam e OpenCV per riconoscere l’utente e gestire l’autenticazione. #KDE #KDEPlasma #Linux #Wayland #OpenSource #FaceUnlock www.linuxeasy.org/plasma-face-...
UK Games Expo just banned generative AI. Good.
This is why GM-Copilot Studios refuses LLMs for VTTs. We use OpenCV to read layouts & Lean 4 to verify math.
AI shouldn't generate your game; it should just do your data entry so you can hit conventions without burning out.
This is why GM-Copilot Studios refuses LLMs for VTTs. We use OpenCV to read layouts & Lean 4 to verify math.
AI shouldn't generate your game; it should just do your data entry so you can hit conventions without burning out.
UK Games Expo has banned generative AI art, text, and merchandise across all NEC exhibition halls, bringing the convention in line with broader British tabletop standards. Standholders face removal or bans if their products aren't made by humans. #UKGE
UK Games Expo bans generative AI art and text across all trade halls
UK Games Expo has introduced a mandatory policy prohibiting generative AI art and text across all NEC trade halls, requiring exhibitors to sell only human-made games.
www.geeknative.com
September 24, 2026 at 7:16 PM
UK Games Expo just banned generative AI. Good.
This is why GM-Copilot Studios refuses LLMs for VTTs. We use OpenCV to read layouts & Lean 4 to verify math.
AI shouldn't generate your game; it should just do your data entry so you can hit conventions without burning out.
This is why GM-Copilot Studios refuses LLMs for VTTs. We use OpenCV to read layouts & Lean 4 to verify math.
AI shouldn't generate your game; it should just do your data entry so you can hit conventions without burning out.
Training vehicle damage models without real photos. Dmitry Geyzersky (Click-Ins) on deploying synthetic data for production inspections. Join us live at 9am Pacific youtube.com/live/QpowZtY...
Deploying Synthetic Data for Real-World Inspections - OpenCV Live! 226
YouTube video by OpenCV
youtube.com
September 24, 2026 at 3:39 PM
Training vehicle damage models without real photos. Dmitry Geyzersky (Click-Ins) on deploying synthetic data for production inspections. Join us live at 9am Pacific youtube.com/live/QpowZtY...
It's been ages since I did any Flutter development... always wanted to try out OpenCV for something fun, so I cobbled together a CyberpunkTCG card scanner for personal use, inspired by my favourite Magic card collecting app @manabox.app
September 24, 2026 at 12:08 PM
It's been ages since I did any Flutter development... always wanted to try out OpenCV for something fun, so I cobbled together a CyberpunkTCG card scanner for personal use, inspired by my favourite Magic card collecting app @manabox.app
New Instats livestreaming seminar: AI-Powered Image Analysis for Scientific Research
#ComputationalBiology #DataAnalytics #DataScience #MachineLearning #BiomedicalEngineering #Bioinformatics #ComputerScience #ArtificialIntelligence #Statistics #SoftwareEngineering #Biology #ChatGPT #Jupyter #
#ComputationalBiology #DataAnalytics #DataScience #MachineLearning #BiomedicalEngineering #Bioinformatics #ComputerScience #ArtificialIntelligence #Statistics #SoftwareEngineering #Biology #ChatGPT #Jupyter #
AI-Powered Image Analysis for Scientific Research - Livestream starting Nov 30, 2026 (UTC)
Turn image data into publication-ready insights with our one-day online workshop on AI-powered image analysis for PhD students, professors, and professional researchers, led by Nikolay Oskolkov, Group Leader/PI at LIOS. This intensive, hands-on seminar bridges rigorous theory and real-world implementation, covering CNNs, transfer learning, UNet, Mask R-CNN, object detection, Bayesian uncertainty quantification, GRAD-CAM interpretability, OpenCV, OTSU thresholding, reproducible Jupyter workflows on Linux, and effective ChatGPT-assisted coding in Python. Participants will learn how to build, train, evaluate, and interpret image classification, segmentation, and detection pipelines for biological, microscopy, high-throughput, and clinical imaging data, with a strong focus on reproducibility, statistical reporting, experiment design, and publication-quality outputs. All livestream seminars are delivered via Zoom, with recordings, materials, and a monitored Q&A forum available for 30 days after the seminar, plus an official Instats certificate of completion.
#ComputationalBiology #DataAnalytics #DataScience #MachineLearning #BiomedicalEngineering #Bioinformatics #ComputerScience #ArtificialIntelligence #Statistics #SoftwareEngineering #Biology #ChatGPT #Jupyter #Linux #Python #R #Research #ResearchTraining #Instats
instats.org
September 24, 2026 at 9:06 AM
New Instats livestreaming seminar: AI-Powered Image Analysis for Scientific Research
#ComputationalBiology #DataAnalytics #DataScience #MachineLearning #BiomedicalEngineering #Bioinformatics #ComputerScience #ArtificialIntelligence #Statistics #SoftwareEngineering #Biology #ChatGPT #Jupyter #
#ComputationalBiology #DataAnalytics #DataScience #MachineLearning #BiomedicalEngineering #Bioinformatics #ComputerScience #ArtificialIntelligence #Statistics #SoftwareEngineering #Biology #ChatGPT #Jupyter #
At GM-Copilot Studios, we don't guess.
Our Masterwork Engine uses OpenCV to physically map the page and routes the data through strict Pydantic math gates. If the output doesn't match the exact 3-stat Pip economy, the pipeline rejects it. Zero hallucinations.
Our Masterwork Engine uses OpenCV to physically map the page and routes the data through strict Pydantic math gates. If the output doesn't match the exact 3-stat Pip economy, the pipeline rejects it. Zero hallucinations.
September 24, 2026 at 8:32 AM
At GM-Copilot Studios, we don't guess.
Our Masterwork Engine uses OpenCV to physically map the page and routes the data through strict Pydantic math gates. If the output doesn't match the exact 3-stat Pip economy, the pipeline rejects it. Zero hallucinations.
Our Masterwork Engine uses OpenCV to physically map the page and routes the data through strict Pydantic math gates. If the output doesn't match the exact 3-stat Pip economy, the pipeline rejects it. Zero hallucinations.