Opencv jobs

...accuracy is sufficient for now; we can iterate later. Both real-time and batch inference modes should be supported. Phase 3 – Wrap the model in a lightweight web interface where a user can upload media and immediately see the percentage split. The interface also needs: • File upload history • Downloadable analysis reports • Basic user authentication Preferred stack & tools Python, OpenCV, YOLOv5/YOLOv8 (or similar), Flask/FastAPI for the back end, plus any front-end framework you deem lean and quick to deploy. To help me shortlist quickly, please send: • Links or screenshots of past AI/computer-vision projects (especially anything involving material classification or industrial inspection) • A brief outline of your proposed a...

...• AI models for advanced tasks such as background removal, image upscaling, and photo enhancement • Traditional image processing libraries for simpler tasks such as compression, resizing, cropping, and format conversion Recommended models/libraries include: • U²-Net / MODNet for background removal • Real-ESRGAN for image upscaling • GFPGAN for face restoration • ImageMagick / Sharp / OpenCV for standard image processing Key Features Required: • Image upload and processing pipeline • Before/after comparison slider for processed images • Instant preview before download • Image download system with watermark option for free users • User account system with usage limits • Free and premium subscr...

...program should show the recent results visually as icons (like a timeline of previous rounds). Example: 8. Continuous Operation The tool must run continuously and monitor the game automatically. It should: - detect each new round - log results in real time - update statistics No user interaction should be required. 9. Technology Suggestions The developer may use technologies such as: Python OpenCV Image Recognition / Template Matching Screen Capture 10. Deliverables At the end of the project I expect: • a fully working desktop application • Windows executable file (.exe) • simple instructions on how to run the tool The program should work with both LDPlayer and BlueStacks emulators. Important Notes: This project does NOT require game source code or integr...

...Image) - Recent results panel showing last rounds with icons - Round counter and session tracking - Frequency table with percentages for each icon - Hot item detection with visual indicators - Multiple statistical views 3. Data Export - Auto-save to Excel (.xlsx) format - CSV export option - Timestamped results with round numbers 4. Technical Implementation - Python with OpenCV for image recognition - GUI built with tkinter matching your interface design - Automated screen capture from emulator - 95%+ detection accuracy 5. Installation Package - Executable file (no Python installation needed) - Setup guide - Icon template configuration Timeline: 8 days (March 10-18, 2026) Includes testing and any adjustments needed for your specifi...

I need a custom-built AI that can take my raw short clips and automatically turn them into polished, “ready-to-share” videos. The tool must recognise good in- and out-points, apply smooth transitions or hard ...Drop-in usage: I point the tool at a folder of clips, pick a destination folder, press “Go”, and receive an edited file. • Cuts feel natural; no jarring jump-cuts unless the algorithm intentionally applies a jump effect. • Average loudness around –14 LUFS with minimal background hiss. • Colour consistency between consecutive shots within ±3 ΔE. You’re free to choose the stack—Python with OpenCV, FFmpeg, or a lightweight TensorFlow/PyTorch model, for instance—as long as setup is simple and per...

...output frame rate and any other relevant image settings—must be editable from a clean, graphical interface that carries my company logo. No multilingual support is required, so the UI can stay in English. To speed things up I can supply an existing Lua script that demonstrates the core image calculations; feel free to translate or rewrite it in the language you are most comfortable with (Python + OpenCV, C#/.NET, C++ with Qt, etc.) as long as the final build runs natively on Windows and delivers smooth GUI performance. Deliverables • Windows executable with installer (or portable folder) • Source code with clear build instructions • Brief user guide showing how to load a batch, adjust settings, run the process, and export the video The project will...

OpenCV Hill Climb Project – Description Project Title: Autonomous Hill Climbing Robot using OpenCV Project Description: Developed an AI-based computer vision system using OpenCV and Python that enables a robot/vehicle to automatically detect and climb slopes or hills. The system processes real-time camera input to analyze terrain conditions such as slope direction, obstacles, and surface edges. Implemented image processing techniques like edge detection, contour detection, and gradient analysis to determine the steepest safe path for climbing. Applied the Hill Climbing optimization algorithm to continuously choose the best next movement direction based on terrain analysis. Integrated real-time decision making so the robot adjusts movement dynamically while...

...uploads image Image is validated (type and size) Image is sent to processing engine Processing engine generates result Preview is displayed to user User downloads processed image Preferred implementation: Self-hosted image processing using open-source models or libraries. Avoid third-party paid APIs that charge per image unless absolutely necessary. Possible technologies: Python OpenCV Pillow rembg or similar background removal library --- USER SYSTEM The platform should support two types of users: Free Users No login required. Users can upload images and download processed results with watermark. Premium Users Users must create an account and log in. Premium users can download processed images without watermark. A user dashboard should display: Su...

**Project Title:** Source Detection using Human Behaviour Dynamics using Machine Learning /...novelty is must **Scope of Work:** * Dataset preprocessing and exploration * Model development using ML/DL techniques * Training and testing the models * Performance evaluation (Accuracy, Precision, Recall, Confusion Matrix) * Comparison of different models * Clear documentation of the workflow **Preferred Tech Stack:** * Python * Machine Learning / Deep Learning models * TensorFlow / PyTorch / OpenCV * Data visualization libraries **Deliverables:** * Complete source code * Trained model * Results and performance comparison * Brief documentation of the methodology **Additional Notes:** If you have suggestions for improving the model or methodology, feel free to include them in your...

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, ...

...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. • Provide clear metrics: precision, recall, F1, and confusion matrices on a held-out validation set. • Package the final solution with a lightweight REST or gRPC endpoint so the in-house engineering team can call it from our SCADA system. Del...

...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...

...instructions for installing dependencies and running on Jetson Orin Nano. Source code in a Git repo + a short README. Provide a short demo video or screen recording of the workflow. Technical Requirements - Target platform: NVIDIA Jetson Orin Nano (JetPack Linux) - work remotely through ssh - Camera: 640×512, MIPI CSI-2 4 lanes, 22-pin ribbon Preferred languages: Python (PyQt / Tkinter / OpenCV). Must run offline (no cloud requirement). What I Will Provide: - Jetson Orin Nano hardware access (remote via ssh). - Camera details / driver info if needed (device node, gstreamer pipeline, etc.). - List of target object classes....

...charts of vitals. • Alert panel for out-of-range values. • Patient info card: Name, ID, Date. 4. Upload Interface • Web upload form (drag & drop or file select). • Trigger OCR → dashboard update. 5. Demo-Ready Hosting • Hosted on AWS EC2/S3 (or equivalent). • Fully clickable end-to-end flow: upload → extract → dashboard → alerts. ⸻ Tech Stack (Suggested) • OCR: AWS Textract / Tesseract / OpenCV • Backend: Python + FastAPI • Database: Postgres or SQLite • Frontend: React.js + / Recharts • Hosting: AWS ⸻ Requirements • Proven experience with OCR / Document AI projects. • Experience in Python backend + React frontend. • Must deliver a fully working demo in 7 days. &bul...

...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 browser via or MediaPipe. I’m comfortable hosting on typical cloud stacks, so just note any special environment requirements. Deliverables: • A responsive web page (HTML/CSS/JS or framework of your choice) with an intuitive image-upload interface. • Integrated face-detection model returning on-sc...

...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 browser via or MediaPipe. I’m comfortable hosting on typical cloud stacks, so just note any special environment requirements. Deliverables: • A responsive web page (HTML/CSS/JS or framework of your choice) with an intuitive image-upload interface. • Integrated face-detection model returning on-sc...

...Technical Requirements Core: Expert-level Node.js (TypeScript) or Python. Automation: Mastery of Playwright or Puppeteer. System Resilience: Deep understanding of request orchestration, session persistence, and residential proxy management to ensure high uptime against enterprise-grade site architectures. Cloud: AWS (Fargate, Lambda, S3). Vision: Familiarity with image processing/fingerprinting (OpenCV/pHash) is a significant advantage. 4. The Challenge: National Scale You will be building a system designed to support a $10MM+ ARR run-rate within 12 months. This requires a "Zero-Error" approach to data integrity, specifically ensuring that material quantities and freight weights remain accurate across 40,000+ US zip codes. 5. Why Join Us? Lead the technical bui...

...revenue report • Staff performance report • Customer visit history • Suspicious activity report • Export to PDF and Excel ⸻ 7. Hardware Integration System must support integration with CCTV cameras such as: • Hikvision • Dahua Technology • TP-Link • CP Plus Or recommend compatible AI camera hardware. ⸻ Preferred Technology Stack • Backend: Python or Node.js • AI and Computer Vision: OpenCV, Face Recognition, TensorFlow • Database: Firebase or PostgreSQL • Frontend: React or Angular • Cloud: Google Cloud Platform or Amazon Web Services ⸻ Deliverables • Fully working AI system (production-ready) • Web dashboard (admin panel) • Camera integration setup • Installation guide ...

...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 and mouth, classifies ...

...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 and mouth, classifies ...

...photographs that need an automated touch-up pipeline. The goal is a single, well-documented Python script (or small module) that: • reads one image or an entire folder of JPEGs, • boosts brightness and contrast in a controllable way, • performs effective noise reduction without blurring fine detail, and • applies colour correction so skin tones and skies look natural. I usually work with OpenCV and Pillow, so feel free to lean on those or another mainstream library (scikit-image, wand, etc.). Command-line arguments for input path, output path, and optional strength parameters will make the tool easy for me to integrate into an existing workflow. Deliverables 1. The Python script with clear docstrings and inline comments. 2. A short README explaini...

... and performance targets. Once we lock the scope, I’ll provide sample images plus any domain knowledge you need. You’ll handle the end-to-end pipeline: dataset preparation, model architecture selection (CNN, transformer, or whatever you judge best), training/tuning, and deployment in a lightweight API or on-device model. I’m comfortable with common stacks like Python, TensorFlow, PyTorch, and OpenCV, so feel free to propose the combination that will deliver both speed and accuracy. Deliverables • A working, tested model meeting agreed accuracy/F1 benchmarks • Inference script or REST/GraphQL API for easy integration • Brief setup guide and commented code I’m ready to move quickly and can review prototypes as soon as you have them. L...

... and performance targets. Once we lock the scope, I’ll provide sample images plus any domain knowledge you need. You’ll handle the end-to-end pipeline: dataset preparation, model architecture selection (CNN, transformer, or whatever you judge best), training/tuning, and deployment in a lightweight API or on-device model. I’m comfortable with common stacks like Python, TensorFlow, PyTorch, and OpenCV, so feel free to propose the combination that will deliver both speed and accuracy. Deliverables • A working, tested model meeting agreed accuracy/F1 benchmarks • Inference script or REST/GraphQL API for easy integration • Brief setup guide and commented code I’m ready to move quickly and can review prototypes as soon as you have them. L...

... and performance targets. Once we lock the scope, I’ll provide sample images plus any domain knowledge you need. You’ll handle the end-to-end pipeline: dataset preparation, model architecture selection (CNN, transformer, or whatever you judge best), training/tuning, and deployment in a lightweight API or on-device model. I’m comfortable with common stacks like Python, TensorFlow, PyTorch, and OpenCV, so feel free to propose the combination that will deliver both speed and accuracy. Deliverables • A working, tested model meeting agreed accuracy/F1 benchmarks • Inference script or REST/GraphQL API for easy integration • Brief setup guide and commented code I’m ready to move quickly and can review prototypes as soon as you have them. L...

... and performance targets. Once we lock the scope, I’ll provide sample images plus any domain knowledge you need. You’ll handle the end-to-end pipeline: dataset preparation, model architecture selection (CNN, transformer, or whatever you judge best), training/tuning, and deployment in a lightweight API or on-device model. I’m comfortable with common stacks like Python, TensorFlow, PyTorch, and OpenCV, so feel free to propose the combination that will deliver both speed and accuracy. Deliverables • A working, tested model meeting agreed accuracy/F1 benchmarks • Inference script or REST/GraphQL API for easy integration • Brief setup guide and commented code I’m ready to move quickly and can review prototypes as soon as you have them. L...

I have a working ASP.NET (VB.NET) + SQL face-recognition attendance portal th...timing, not just audio similarity. • Hook directly into my existing VB.NET codebase and SQL user tables with minimal architectural change. • Return a clear pass/fail flag so the current attendance logic remains untouched. Acceptance criteria 1. Demonstrable defeat of static images and replayed videos during testing. 2. Source code and comments in VB.NET, plus any helper libraries (e.g., OpenCV, MediaPipe, Azure Cognitive Services) properly referenced. 3. Simple setup guide so I can build, deploy, and tweak the phrase list myself. If you have ideas for extra safeguards—like random head-movements or an optional MFA step—I’m open to discussing them once the core r...

...expectations and delivery teams • Manage scope discussions, solution changes, and technical clarifications with clients • Ensure project timelines, quality, and deliverables are met • Maintain strong client relationships and ensure satisfaction throughout the development lifecycle Technical Expertise Required • Strong background in Computer Vision & Image Processing • Hands-on experience with: • OpenCV • Facial recognition systems • Video detection and analysis • Image classification and object tracking • Python-based AI/ML workflows • Understanding of model deployment and production pipelines • Ability to review code, guide architectural decisions, and unblock teams Leadership & Communication Skills • P...

... and any visual aids required for smooth, engaging live delivery. • At least two industry-specific application projects per course—think finance anomaly detection for LSTMs, medical-image segmentation, or manufacturing quality-control models—complete with datasets, step-by-step guidance, and evaluation metrics. • Clear instructions on the environment and tools you use (PyTorch, TensorFlow, OpenCV, Jupyter, or similar) so participants can replicate results during the sessions. By the end of our collaboration I should have three ready-to-run, instructor-led courses that advanced learners can dive into immediately, each capped with practical projects they can showcase at work. If you’ve taught or built curricula at this level and can commit to inte...

...three off-the-shelf webcams. As soon as a dart sticks, the system must pinpoint its exact segment, translate that into the correct score, and push a real-time event—ideally over a WebSocket—so any client can update the match instantly. Core expectations • Camera input: three synchronized 1080p webcams positioned around the board. • Tech stack: feel free to reach for either Python/OpenCV or C++/OpenCV; whichever lets you reach millisecond-level detection with reliable accuracy. • Calibration: a quick routine that someone in a pub can run in a couple of minutes—no chessboard targets or lab lighting required. • Output: headless service only; no on-screen UI. Emit JSON events such as `{ "x":…, "y":...

...expectations and delivery teams • Manage scope discussions, solution changes, and technical clarifications with clients • Ensure project timelines, quality, and deliverables are met • Maintain strong client relationships and ensure satisfaction throughout the development lifecycle Technical Expertise Required • Strong background in Computer Vision & Image Processing • Hands-on experience with: • OpenCV • Facial recognition systems • Video detection and analysis • Image classification and object tracking • Python-based AI/ML workflows • Understanding of model deployment and production pipelines • Ability to review code, guide architectural decisions, and unblock teams Leadership & Communication Skills • P...

...should open the standard share sheet so I can send the chosen files through any installed channel (Messages, WhatsApp, AirDrop, e-mail, etc.). Accuracy is key: false positives in face grouping must be minimal, and whenever the algorithm is unsure, it should simply place the photo in an “Unsorted” bucket so I can manually move it. I’m happy for you to use Apple’s Vision/Core ML, Google ML Kit, OpenCV or another proven face-clustering library—whatever offers reliable on-device processing and keeps users’ photos private. Deliverables 1. A fully functional mobile app (native or cross-platform) that runs on at least one major platform. 2. Automatic face clustering with an easy way to correct mistakes. 3. Filters that let me select photos ind...

...core of the job is therefore twofold: • build a reliable face-detection pipeline specialised for personal-album style images (no security-camera angles, mostly smartphone shots in varied lighting), and • structure the results so I can analyse them later inside Python or export them to CSV for further data analysis. Please use a mainstream deep-learning framework you are comfortable with—OpenCV, TensorFlow, PyTorch, or a comparable library is fine—as long as the final code runs on Windows and can be triggered from a simple command line. The model can be pre-trained (e.g., a RetinaFace or MTCNN backbone) provided you fine-tune or post-process it so false positives stay minimal. Acceptance criteria 1. A script or notebook that takes an input folder ...

...should open the standard share sheet so I can send the chosen files through any installed channel (Messages, WhatsApp, AirDrop, e-mail, etc.). Accuracy is key: false positives in face grouping must be minimal, and whenever the algorithm is unsure, it should simply place the photo in an “Unsorted” bucket so I can manually move it. I’m happy for you to use Apple’s Vision/Core ML, Google ML Kit, OpenCV or another proven face-clustering library—whatever offers reliable on-device processing and keeps users’ photos private. Deliverables 1. A fully functional mobile app (native or cross-platform) that runs on at least one major platform. 2. Automatic face clustering with an easy way to correct mistakes. 3. Filters that let me select photos ind...

Project Description We are looking for an experienced Computer Vision engineer to develop a high-performance real-time object tracking system running on Linux. The system will allow a user to select a target within a live video stream and maintain robust tracking under dynamic conditions. This is not a basic OpenCV demo project. We require a stable, production-oriented architecture with strong tracking persistence under motion, scale variation, partial occlusion, and illumination changes. Core Functional Requirements • Linux-based implementation (Ubuntu preferred) • Real-time video stream processing (USB / CSI / RTSP compatible) • User-initiated ROI selection (click-to-track) • Persistent target tracking at minimum 30 FPS (hardware dependent) • Co...

...developer to enhance and fix several parts of the project. Scope of Work: CAPTCHA Integration (No Third-Party Services) I need to add a CAPTCHA system into my application. It must NOT use any third-party CAPTCHA solving services or paid APIs (no 2Captcha, AntiCaptcha, etc.). The solution should work locally. Preferred approach: machine learning-based CAPTCHA recognition (for example using OpenCV or another suitable C++-compatible method). It must be optimized for speed and low delay. Clean and maintainable implementation is required. Modify / Improve Existing Scripts Update and adjust some existing logic inside the C++ application. Improve performance and stability if possible. Ensure the code remains organized and readable. Fix Visual Studio Errors Currently, there ...

I’m working with a very short hit-and-run clip—under one minute, shot on a phone—where the vehicle’s license plate is visible for only about three seconds but is heavily blurred. I need those few frames professionally stabilised, deblurred, and enhanced so the characters on the plate are as legible as current tools will allow. You’re free to use any workflow that suits you best—OpenCV, Topaz Video AI, DaVinci Resolve, Adobe After Effects, proprietary neural nets—whatever gets the cleanest result without introducing artifacts that could cast doubt on authenticity. I’m realistic: if the plate can’t be read with certainty, I still need the best possible clarity and a brief explanation of why further improvement isn’t feasible...

I need an experienced computer-vision developer to build a photo-based image classification pipeline using OpenCV. The system will ingest still photographs taken at live events and automatically tag each shot into predefined categories (for instance crowd, stage, speaker, logo, VIP, etc.). The core requirement is accurate, fast classification of photos only; we are not dealing with video or live camera feeds right now, though I may extend in that direction later. You are free to choose the underlying framework—TensorFlow, PyTorch, scikit-learn—so long as OpenCV is used for image handling and preprocessing. Here is what I expect: • A well-documented training script that reads my labeled dataset, performs augmentation where helpful, and outputs a reprod...

...should open the standard share sheet so I can send the chosen files through any installed channel (Messages, WhatsApp, AirDrop, e-mail, etc.). Accuracy is key: false positives in face grouping must be minimal, and whenever the algorithm is unsure, it should simply place the photo in an “Unsorted” bucket so I can manually move it. I’m happy for you to use Apple’s Vision/Core ML, Google ML Kit, OpenCV or another proven face-clustering library—whatever offers reliable on-device processing and keeps users’ photos private. Deliverables 1. A fully functional mobile app (native or cross-platform) that runs on at least one major platform. 2. Automatic face clustering with an easy way to correct mistakes. 3. Filters that let me select photos ind...

...Python code implementing the full video analysis pipeline • Clear separation between face identification, exercise classification, and rep counting logic • Sample outputs on provided video files • Short README explaining how to run the pipeline and describing the architecture Required experience: • Strong Python skills • Computer vision fundamentals • Experience with video processing and OpenCV • Experience with pose estimation • Experience with deep learning frameworks such as PyTorch or TensorFlow • Ability to design clean, modular systems Nice to have: • Facial recognition or embedding-based identity systems • Human activity or action recognition experience • Prior work in fitness, sports, or biomechanic...

...Handle multi-page statements, varying templates, and common artefacts such as skew, shading, or mixed languages. • Expose the extraction workflow to my app through a simple Node.js function or REST endpoint that I can call with a file path and receive JSON. • Store results to MySQL once the JSON passes validation. Technology expectations I have no fixed preference on libraries: Tesseract, OpenCV, PDFPlumber, pdfminer-six, or a custom C++ wrapper are all acceptable as long as the final stack remains 100 % on-prem. Optimising accuracy with pre-processing (deskew, denoise) and template detection is critical, and I’m open to using GPU acceleration if it simplifies heavy workloads. What I’d like from you Send a concise, detailed project proposal that ou...

I need a Raspberry Pi programmed so it can take a live video feed from an attached camera, run image-recognition on each frame to spot custom objects or patterns that I will later define, and then publish the resulting data over Modbus TCP. Here is the flow I am after: 1. Camera streams video into the Pi. 2. Your code performs real-time detection of the specified custom objects/patterns (OpenCV, TensorFlow Lite, or another light framework is fine as long as it runs smoothly on the Pi). 3. For every detection event—or on a set interval if no object is found—you convert the recognition result into register values and expose them through a Modbus TCP server running on the same Pi. Deliverables • Fully commented source code (Python preferred) • A br...

...multiple video files • Automatic video merging • Frame-difference / motion-based analysis • Automatic removal of low-motion segments • Export condensed MP4 video • Simple timeline interface for manual trimming • Basic text/overlay insertion No cloud required initially — local processing is preferred. ⸻ Preferred Tech Stack (Open to Suggestions) Backend / Video Processing: • Python • OpenCV • FFmpeg Frontend: • Electron / Tauri • React or similar Must support: • Windows and Mac • Efficient handling of large files (up to 5GB) ⸻ Project Type MVP development with potential long-term expansion into: • Advanced AI • SaaS platform • International commercialization I am looking...

...a neatly laid-out A4 PDF must be produced automatically. One wagon per page, with a frame grab of the video, the captured fields already filled, and space left for handwritten or typed comments. The PDF has to save locally and be shareable through the Android share sheet, ready to print without scaling issues. I am happy for you to rely on Android Studio, Kotlin or Java, CameraX, ML Kit OCR or OpenCV—whatever delivers reliable scanning and a clean, responsive UI. Accuracy and speed come before flashy graphics. Deliverables • Release-ready APK • Complete Android Studio source project • A4 PDF template and code that fills it dynamically • Brief setup/user guide Acceptance criteria • At least 90 % successful extraction of all three data grou...

...camera (USB or built-in), and immediately see bounding boxes with class names and confidence scores updating on-screen at 30 fps or better. Key details • Model: start with an existing YOLO checkpoint (v5, v7, v8 or YOLO-NAS—whatever you feel offers the best speed / accuracy trade-off). Feel free to fine-tune if that improves precision, but the core must stay YOLO. • Language & libs: Python 3.x, OpenCV for video capture/rendering, torch or ultralytics for inference. • Platform: Windows 10/11 desktop, runnable from a single installer or clean virtual environment; no cloud dependencies. • Output: highlighted video stream plus a lightweight UI panel that shows FPS, tool class counts and a “save frame” button for manual snapshot expor...

AI Image Generation Automation MVP ## 1. Project Goal Build a scalable AI image generation progran using AdsPower, Playwright, and Supab...and indices. 2. **Worker Implementation:** Build the script to read 400 prompts from the DB and save indexed images to local/cloud storage. 3. **Failure Handling:** Implement the logic to re-run only the specific indices that failed. 4. **Minimal UI:** Create a simple dashboard to upload prompts (CSV/Excel) and view the status of each index. ## 5. Strictly Prohibited - **No Image Recognition (OpenCV):** Use only DOM Selectors for reliability. - **No Manual Captcha Solving:** Use persistent manual sessions or 3rd party solvers if absolutely necessary. - **No Synchronous Processing:** All tasks must be processed via an asynchronous Worker-Queue ...

...video generation logic—transitions, basic trimming, and soundtrack alignment—so the user can go from assets to finished output with minimal clicks. • Include real-time or near-real-time preview plus the option for manual tweaks (simple timeline edits, text overlays, color adjustments). • Deliver clean, well-commented code—Python preferred—with clear instructions for installing dependencies (OpenCV, PyTorch/TensorFlow, FFmpeg, or any libraries you choose). • Provide a short demo video and sample input–output files showing the system working end-to-end. Acceptance criteria 1. Feed the system a folder of mixed MP4 clips and JPG/PNG images; receive a coherent, 1080p final video without crashes. 2. Key events (e.g., faces speakin...

My MP4 clip is under one minute long, shot on a poor-quality security camera, and shows just one car. I must know its licence plate with absolute certainty for an insurance claim, so anything less than 100 % accuracy is of no value to me. I am looking for someone who routinely works with forensic video tools such as Amped FIVE, VideoCleaner, OpenCV pipelines, Topaz Video AI or comparable software to extract a crystal-clear, fully readable still. De-blurring, super-resolution, frame stacking—whatever it takes—is expected, provided the end result is court-defensible. Deliverables • A high-resolution still image of the plate (PNG or TIFF) • The enhanced video segment in a lossless format • A brief technical report (PDF) describing the methods and settin...

...context, and presents step-by-step on-screen cues and explanations. • A simple dashboard where I can script or edit each tutorial flow without touching code. • Solid architecture documentation so the solution can later expand into additional features such as multilingual support or automated editing. I’m open to whichever stack you recommend, though I anticipate computer-vision tools (e.g., OpenCV), an LLM integration (OpenAI, Anthropic, etc.), and a lightweight web interface (React, Vue, or similar). Please explain how you plan to: 1. Detect relevant moments in the video. 2. Trigger conversational tips or guided overlays. 3. Keep latency low so guidance feels instantaneous. Along with your approach, include timelines, any required APIs or licenses...

...should open the standard share sheet so I can send the chosen files through any installed channel (Messages, WhatsApp, AirDrop, e-mail, etc.). Accuracy is key: false positives in face grouping must be minimal, and whenever the algorithm is unsure, it should simply place the photo in an “Unsorted” bucket so I can manually move it. I’m happy for you to use Apple’s Vision/Core ML, Google ML Kit, OpenCV or another proven face-clustering library—whatever offers reliable on-device processing and keeps users’ photos private. Deliverables 1. A fully functional mobile app (native or cross-platform) that runs on at least one major platform. 2. Automatic face clustering with an easy way to correct mistakes. 3. Filters that let me select photos ind...

...architecture so multiple spas can use their own branding. • HIPAA-friendly storage practice for images and reports (no protected health info beyond the photo). • Admin capability to tweak the recommendation rules without redeploying code. • Clean, mobile-first UI; React or Vue on the front end is fine, but I’m open to other modern stacks. • Back-end could be Python (FastAPI, TensorFlow, OpenCV) or another language you prefer as long as the model can run securely on my server or via a trusted API. Deliverables • A fully deployed MVP on my cloud account (AWS or GCP). • Source code in a private repo with build instructions. • Trained/finetuned model or documented API connection. • Brief user guide and 30-minute hand-off ...