OpenCV Jobs

I want to build a small, self-contained charging station that wakes up only when it “sees” a bottle and a can. The core will be an Arduino (any recent 32-bit board is fine) tied to a solar panel and battery pack. A lightweight AI vision module or camera running something like TensorFlow Lite or OpenCV should continuously—or on a duty-cycled basis—look for bottles. The moment a bottle is detected, the system must move straight into the charging routine without waiting for external confirmation; no alerts, no logging, just automatic activation. What I need from you • Complete Arduino firmware that integrates the vision trigger with the charge-controller logic. • A schematic / wiring diagram showing how the camera, solar panel, charge controller, and any...

I have continuous video footage from live inspection of steel flat bars strips our production line and need a complete deep-learning pipeline that flags surface, structural, and functional defects in real time. The raw videos are already labeled by timestamp; frame-level annotation may still be required for optimal accuracy. Scope • Design and train a deep neural network—CNN, transformer, or hybrid model—that detects all three defect categories directly from video streams. • Implement preprocessing (frame extraction, augmentation, ROI isolation) and post-processing (tracking, alert generation) in Python using libraries such as PyTorch/TensorFlow and OpenCV. • Optimise for inference on an on-premise GPU; latency under 200 ms per frame is the target. &bull...

I’m building a ROS 2 pipeline that must reliably spot nuts and bolts in a live camera feed and publish their positions to the rest of my stack in real time. Your job is to create the complete vision-detection module—from model training or fine-tuning through to a clean ROS 2 node that subscribes to an image topic and spits out the detected objects with bounding boxes (or masks) and a confidence score. OpenCV, TensorFlow/PyTorch and any of the common ROS 2 image-transport plugins are all fine as long as the final node runs on Humble and stays GPU-agnostic (CUDA acceleration is a bonus, not a requirement). I already have a test rig with a standard USB camera; if you need specific calibration images I can capture them for you. Please deliver: • Source code for the detection...

I need a small software tool that runs on an NVIDIA Jetson Orin Nano to capture, organize, and export a labeled image/video dataset for training YOLO object detection models. The camera is an 640×512 sensor connected via MIPI CSI-2 (4 lanes) using a 22-pin ribbon cable to the Jetson Orin Nano CSI connector. The tool should support live preview, capture, dataset management, and YOLO-format export. Build an application that: - Interfaces with the camera on Jetson Orin Nano - Acquire frames from the MIPI CSI-2 camera reliably (GStreamer / V4L2 / libargus or best approach for this sensor). - Provide live preview (grayscale or false color optional). - Display FPS + resolution. Dataset capture: - Capture single frames and/or short clips (optional). - Save images in a consist...

Title: AI-Powered Document Intelligence Demo – 7-Day Delivery Budget: ₹10k Timeline: 10 Days Location: Remote ⸻ Project Overview We are building a proof-of-concept Doc Intelligence demo for medical perfusion sheets. The goal is to extract structured vitals from uploaded images/PDFs and display them in a simple real-time dashboard with alerts. This is a demo only, not a full MVP — the focus is on speed, accuracy, and visual clarity. ⸻ Key Deliverables 1. OCR / Text Extraction. • Input: scanned perfusion sheet (PNG/JPG) or PDF. Have handwritten • Output: structured JSON (BP, ACT, Flow, Temp, Time). • Include basic validation (range checks, missing values). 2. Backend API • Python + FastAPI (or equivalent). • Receives uploaded file → r...

We are building an AI-powered technical interview and remote assessment platform designed to automate and enhance hiring processes for global companies. The system will integrate real-time video communication, screen sharing, browser-based coding assessment, and AI-driven interview intelligence including automated question generation, live evaluation, and structured answer suggestions. We are seeking a highly experienced Full Stack Engineer to lead architecture and development of this scalable SaaS product. Russian Developer should be high priority for skilled people. Don't apply Indian people don't waste your time

I’m putting together a straightforward online page where visitors can upload a photo and immediately receive automated face-based feedback powered by AI image recognition. The core requirement is reliable detection of faces in any uploaded image; once a face is located, I’d like the response to display bounding boxes or similar visual confirmation so users clearly see what the model found. Beyond that essential functionality, I’m open to expanding into deeper facial insights—age, emotion, gender, or related analytics—if you have an off-the-shelf model or a custom pipeline that can slot in cleanly. My priority, however, is to ship a polished, latency-friendly MVP that runs either server-side (Python + OpenCV, TensorFlow, or similar) or directly in the browse...

I need a deep-learning solution that watches a driver’s face through a standard camera feed, tracks eye-closure patterns and yawning frequency, then translates those cues into a clear fatigue score that updates continuously. Over a journey the model should also plot a time-based curve so I can see how alertness rises or falls. Please build and train the full pipeline in Python, preferably with PyTorch or TensorFlow paired with OpenCV for video handling. The system must be completely vision-based; no wearables or contact sensors. I will supply sample clips for initial testing, but the code should accept any 30 fps video stream so I can later attach it to an in-car webcam. The final hand-off should include: • Inference script that ingests a live or recorded feed, detects eyes ...

We need an Android developer to add iPhone-style panorama to the Open Camera app (open source: ). Goal: Implement panorama in Open Camera so it works like iPhone: guided on-screen motion, smooth horizontal panning, and one stitched panorama image. • Works seamlessly on both the front and back cameras. • Guides the user with the same arrow-line UI Apple uses, keeping motion smooth and level. • Captures a continuous series of frames, stitches them on-device, and outputs one high-quality image without pushing memory limits. You’ll work only against the official Open Camera codebase (or a clean fork you create). I’ll take your branch and merge it into our own app later.