OpenCV Jobs

I want a fully-automated goalie controller for NHL 26 that can keep the crease locked down every game. The end goal is simple: once the tool is running, the goalie should track the puck, slide into perfect position, make every plausible save, and clear rebounds or handle the puck with the poise of a pro—no manual input required from me during play. Here’s what matters most to me: • A consistent, “unbeatable” performance that reacts in real time to on-ice situations. • Clean integration with NHL 26 so I can fire up a match and let the bot take over instantly. • Compatibility with all common setups; if you need separate builds for PC and console, outline the differences early. • Straightforward installation plus a short read-me or video walk...

We are looking for a contractor with strong experience in computer vision, signal processing, multimedia systems, and Python-based research prototyping. The work involves designing and evaluating algorithms for video analysis, content protection, robustness testing, and experimental research. Ideal candidates should have experience with: Python OpenCV FFmpeg NumPy / SciPy Computer Vision Signal Processing Image / Video Processing Experimental Evaluation Technical Report Writing Selected candidates will be asked to complete a paid technical assessment involving the design and evaluation of a video-processing algorithm.

I am putting together an instructional animation and need a five-person AI task-force to power the technical side of the production. The core roles are Machine Learning Experts, Data Scientists, and Computer Vision Specialists—ideally people who feel at home moving between Python notebooks, TensorFlow / PyTorch stacks, and OpenCV pipelines. Your main focus will be data analysis and algorithm development. Concretely, I’ll count on you to: • Analyse raw video and motion-capture data so we can pinpoint the most engaging sequences to animate. • Develop custom algorithms that automate character rigging, lip-sync, and scene transitions, feeding those outputs directly into our animation software (Blender and After Effects). • Optimise and document the entire workf...

I want shoppers on the Laxmi Opticians site to slip on any frame from our catalogue without leaving the page. The idea is a lightweight, 2-D computer-vision overlay that precisely positions sunglasses and prescription glasses on a customer’s face, working fluidly on both desktop and mobile browsers. No full 3-D modelling, no manual prompt engineering—just an instant preview that feels as natural as looking in a mirror. The experience must offer two entry points: • Real-time overlay through the user’s webcam or phone camera. • Photo upload for those who prefer to try glasses on a still image. Accuracy is critical: pupils should align, temple angles should respect head pose, and scaling must stay consistent as users lean closer or farther from the camera. I&...

I need a complete system that can turn data written in the ancient Brahmi and Sharda scripts into a scannable, QR-style matrix and then read it back reliably. The work splits into two tightly linked parts: 1) Pattern engine Build an algorithm that takes Brahmi or Sharda text (Unicode strings supplied by me) and outputs a square, high-contrast image resembling a QR code. Include error-correction logic so the pattern survives moderate camera tilt, blur, and 20 % visual noise. A lightweight CLI or library in Python, Java, or C++ is fine as long as I can call it from other projects later. 2) Dual-platform scanner Create an app for both iOS and Android whose main task is to scan and decode these patterns. After scanning, the screen should show an informative read-out: the detected script,...

I want to build a simple yet reliable mobile application that lets my field-workers mark their attendance the moment they snap a photo. The app must run smoothly on both Android and iOS and use face-recognition to validate each selfie automatically. As soon as the match is confirmed, the system should time-stamp the record and tag the exact GPS coordinates so I can verify where the employee was standing when the photo was taken. Core flow 1. Worker opens the app, the camera launches instantly. 2. They take a photo; the face-recognition engine checks it against a stored profile. 3. If the face matches, attendance is logged right away together with latitude, longitude and time. 4. All data syncs to a secure back-end; if the phone is offline it queues the record and uploads once a ...

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The goal is to deliver a stand-alone Python desktop application that records classroom or workplace attendance through real-time face recognition. The stack is fixed: Python 3, OpenCV, and the standard Tkinter GUI toolkit. Core flow 1. A compact Tkinter window opens with clearly labelled buttons. The interface must, at a minimum, let a supervisor register new users. 2. During registration the system captures multiple webcam frames per person, automatically saving at least 20 crisp face crops for stronger training data. 3. An LBPH model is trained on those images and stored locally; subsequent launches should reload the latest model without retraining. 4. When recognition mode is active the app checks each detected face against the model and writes a time-stamped entry to a CSV fil...