Opencv Projects

opportunityurgent

Urgent Development Support Needed for High-Quality App Launch

We are The SoCiety, entering a critical migration phase for our innovative app, transitioning from React Native (ejected Expo) to a robust and dynamic technology stack built on Flutter, Firebase Authentication, Node.js/Express.js, and MongoDB. The platform utilizes WebRTC integration with Unity, alongside RunPod and AWS for backend operations. Quality is non-negotiable. If you're unable to guarantee exceptional results should not apply. Comprehensive Project Scope: Platform Migration: Complete the seamless migration from React Native (ejected Expo) to Flutter, ensuring full feature parity, performance optimization, and enhanced user experience. Backend Hardening: Enhance backend infrastructure with rigorous security protocols, scalability solutions, and reliability measures. Robust QR Scanner: Develop and integrate a powerful and accurate QR scanning solution utilizing OpenCV, optimized for diverse operational scenarios. MVP Completion: Finalize all essential MVP features, ensuring readiness for comprehensive user and market testing. OpenCV Engineering: Expert-level OpenCV integration to guarantee rapid, precise, and reliable scanning functionality. Admin Panel (Organizer and Venue): Design and build a comprehensive administrative interface for organizers and venue operators, including intuitive UI, secure authentication, robust user management, and operational oversight. Superadmin Panel (Internal Operations): Implement an extensive management console for internal administrative and operational management, featuring detailed analytics, user and content moderation capabilities, and critical system control. WebRTC Integration: Optimize WebRTC implementation, ensuring seamless Unity interactions, real-time communications, and superior streaming quality. Cloud and Infrastructure Management: Efficient utilization and optimization of AWS and RunPod resources for high availability, scalability, and performance. Timeline: The entire platform must be fully ready for rigorous testing by next Friday, aligning with critical internal milestones. Collaboration Approach: Active integration with our existing internal development team, functioning as a cohesive extension for accelerated delivery. Real-time collaboration and issue resolution through Discord. All UI/UX designs are fully completed and accessible via Figma. Comprehensive technical documentation outlining current progress, detailed architecture, and data flows is readily available. Additional Requirements: Mandatory signing of an NDA before gaining access to complete project documentation and details. We require Digital Operatives who embody precision, adaptability, proactive problem-solving, foresight, and a relentless pursuit of quality. Please urgently respond with your availability, relevant expertise, and a clear plan detailing how your team can efficiently support our ambitious goals and timeline. We eagerly await your prompt reply and look forward to a productive partnership!

Python OpenCV for Road Panorama Creation

I'm looking for a Python expert with OpenCV skills to stitch road images together into panoramas. Key Requirements: - Image stitching experience using OpenCV with Python - Familiarity with handling and processing road photos - Capable of stitching more than 6 images together into a seamless panorama The primary purpose of this project is to create expansive, detailed panoramas from a series of road images. The ideal candidate will have strong technical skills in Python and OpenCV, with a portfolio demonstrating previous work with image stitching. Experience with road photos will be a significant advantage. The project typically involves stitching together more than 6 images, so an ability to handle large datasets efficiently is crucial.

opportunity

Window Dimensions API OpenCV Python

An API is to be provided that receives an image file of a window section taken for a construction project. The image comes from the camera of a mobile device (smartphone/tablet) and meets the following requirements: The window is photographed straight from the front. The window is rectangular or square. The image is well-lit. A reference object (e.g., a green cube) with known dimensions can be placed in the image. The API detects the object (window or window hole) and generates the outer dimensions. The tolerance should be as low as possible (max 1.0 - 1.5 cm). The API returns a JSON with the following properties: width: Width of the window hole height: Height of the window hole imagepath: Image path to the picture with the frame and dimensions, so that it can be checked if the section was captured correctly Only the API needs to be programmed. The image illustrates Step 2 and Step 3. Ideally, the project will be implemented in Python.

opportunity

Python and Machine Learning - AI-powered floor replacement tool

(UK AND EUROPE BASED ONLY) ** Others will be reported. We’re looking for a Python and Machine Learning expert to build the core visualization engine for an AI-powered floor replacement tool—think along the lines of HomeDesigns.ai Floor Editor or Winstars.ai Flooring Designer. This gig is all about the backend visualization: take an uploaded room image, detect the floor, and swap it with a custom texture, keeping it lean and cost-effective on a server. No fancy frontend—just a simple Python UI for testing. **Here’s what we need: Core Task: Use Python and OpenCV to detect floors and replace them with a custom tiled image we provide. AI Models: Leverage or fine-tune lightweight ML models (e.g., segmentation) for accurate floor detection—good enough to keep things clean and precise. TensorFlow or PyTorch are our go-tos. Server Efficiency: Deploy it on a low-cost server (like a small AWS/GCP instance). We want a solid balance of speed and accuracy without racking up big server bills—efficiency is the name of the game. Simple UI: Build a basic Python UI (e.g., Tkinter or a script) so we can upload an image, select a texture, and tweak it—specifically, resize and rotate the tile/texture to fit the room. Nothing flashy, just functional. Success Looks Like: The final image has no (or barely any) artifacting—clean edges, no weird glitches. The texture’s perspective matches the room realistically, like it belongs there. Plus, we can adjust the tile/texture size and rotation for a perfect fit. **What We’re Looking For: Strong Python and OpenCV skills—floor detection and texture replacement should be second nature to you. Experience with lightweight ML models (e.g., U-Net, MobileNet) that deliver accuracy without eating resources. Know-how to deploy on a server and keep costs low—think CPU-friendly or minimal GPU, maybe some model optimization tricks like quantization. Ability to whip up a simple Python GUI that lets us resize and rotate textures on the fly. A practical approach to hit our success criteria—clean output, realistic perspective, and flexible textures—without overcomplicating things. **Project Scope & Budget: Fixed-price job, aiming for a working prototype in 4 weeks. This is just the visualization engine—no frontend needed. **How to Apply: Examples of Python/OpenCV or ML projects you’ve done (code, demos, or write-ups are awesome). A quick rundown of how you’d tackle this—model ideas, optimization approach, etc. Your availability and rate.

opportunity

Window Dimensions API OpenCV Python

An API is to be provided that receives an image file of a window section taken for a construction project. The image comes from the camera of a mobile device (smartphone/tablet) and meets the following requirements: The window or the window hole (building/construction) is photographed straight from the front. The window is rectangular or square. The image is well-lit. A reference object (e.g., a green cube) with known dimensions can be placed in the image. The API detects the object (window or window hole) and generates the outer dimensions. The tolerance should be as low as possible (max 1.0 cm). The API returns a JSON with the following properties: width: Width of the window hole height: Height of the window hole imagepath: Image path to the picture with the frame and dimensions, so that it can be checked if the section was captured correctly Only the API needs to be programmed. The image illustrates Step 2 and Step 3. - I need the hardware/hosting requirements for the project to run this on the customers environment. - It is possible that a different reference object is used for the project (e.g. square magnetic board or standee). The project should be completed by mid-January 2025.

opportunity

AI Script to Improve Interaction with Security Tests

I need an experienced developer with expertise in Tampermonkey and JavaScript to create a script that enhances interaction with digital security tests (such as user verification tests). The script should leverage AI technologies like image recognition and data analysis to work efficiently and accurately. Required Skills: Proficient in Tampermonkey for creating robust and efficient scripts. Strong experience with JavaScript for scripting and execution. Familiarity with AI libraries like OpenCV, TensorFlow, or PyTorch. Ability to process and analyze images and data. Knowledge of machine learning techniques to improve the script's ability to interact with distorted or altered images/texts. The script should be able to handle tests requiring interaction with distorted or obfuscated images or texts, aiming to improve the effectiveness and speed of the interaction

Fixing Python AI code bugs

I need an AI developer with python programming knowledge to fix my code. I am working on computer vision project and open-cv is not working correctly due to timeout error I am facing each time. Is there someone with good experience in openCV ?

opportunity

Window Dimensions API OpenCV Python

An API is to be provided that receives an image file of a window section taken for a construction project. The image comes from the camera of a mobile device (smartphone/tablet) and meets the following requirements: The window is photographed straight from the front. The window is rectangular or square. The image is well-lit. A reference object (e.g., a green cube) with known dimensions can be placed in the image. The API detects the object (window or window hole) and generates the outer dimensions. The tolerance should be as low as possible (max 1.0 - 1.5 cm). The API returns a JSON with the following properties: width: Width of the window hole height: Height of the window hole imagepath: Image path to the picture with the frame and dimensions, so that it can be checked if the section was captured correctly Only the API needs to be programmed. The image illustrates Step 2 and Step 3. Ideally, the project will be implemented in Python.

Computer Vision / Artificial Intelligence / Machine Learning

We are looking for Senior Computer Vision Engineers for Contractual/Freelancing Roles. The job description and requirements are as following: Key Responsibilities: Algorithm Development: Design, develop, and optimize computer vision algorithms for image processing, object detection, recognition, and segmentation. Model Training: Develop and train machine learning models tailored for image analysis and visual data interpretation. AI Integration: Implement and integrate AI models into existing software and hardware systems, ensuring high performance and scalability. Data Analysis: Analyze and process large datasets of images and video feeds to identify patterns, trends, and insights. Performance Optimization: Optimize algorithms and models for real-time processing and ensure they can handle large-scale data efficiently. Required Technical Qualifications: Experience: Minimum of 2 years of professional experience in computer vision, with a proven track record of working on complex image processing and ML projects. Programming Skills: Proficient in programming languages such as Python, C++, and MATLAB. Experience with deep learning frameworks like TensorFlow, PyTorch, or Keras. Algorithm Expertise: Strong understanding of computer vision algorithms and techniques, including but not limited to convolutional neural networks (CNNs), object detection (e.g., YOLO, Faster R-CNN), image segmentation (e.g., U-Net), and feature extraction. AI/ML Knowledge: In-depth knowledge of machine learning principles and experience with supervised, unsupervised, and reinforcement learning. Data Handling: Experience in handling and processing large datasets, including image and video data. Familiarity with data augmentation techniques and synthetic data generation. Performance Tuning: Expertise in optimizing models for deployment in real-time systems and experience with GPU acceleration (e.g., CUDA, TensorRT). Tools & Libraries: Proficiency with OpenCV, scikit-image, and other relevant libraries. Experience with version control systems like Git. Analytical Skills: Strong analytical and problem-solving skills with the ability to think creatively and develop innovative solutions. Communication: Excellent written and verbal communication skills, with the ability to present complex technical information to non-technical stakeholders.

(URGENT) I need expert OpenCV developer

It is simple project. I'm looking for a skilled developer to create a simple image stereo matching program in C++. The primary objective is to support 3D reconstruction from stereo image pairs. Your main tasks will include: - Implementing stereo matching algorithms in C++ with a focus on 3D reconstruction - Ensuring the program is efficient and robust for real-time image processing - Delivering a user-friendly interface for ease of use Ideal candidates should have: - Proficiency in C++ programming, with a strong focus on image processing - A solid understanding of stereo matching concepts and 3D reconstruction - Experience in developing software for image processing applications, particularly in stereo matching Please bid if you're confident in your ability to deliver high-quality, efficient code for this project.

opportunity

Flutter Developer for Image-Based Distance Measurement ( SOS)

Hello everyone, We're on the lookout for an experienced Android/Flutter developer for a groundbreaking project base. We are working on an Android application that utilizes image recognition technology for accurate distance measurement within live camera. Project Overview: Objective: Develop a cross-platform Flutter app capable of measuring distances through mobile camera using advanced image recognition techniques. Key Requirements: Proficient in Flutter app development, experience with integrating image processing libraries (like OpenCV, TensorFlow Lite, etc.), and a solid understanding of image recognition and AI algorithms. What We're Looking For: Proven experience in Android/Flutter app development, particularly in integrating AI and image processing functionalities. Ability to implement efficient and accurate distance measuring algorithms using image recognition. Familiarity with machine learning libraries (such as TensorFlow Lite) is highly desirable. Strong problem-solving skills and the ability to work independently

Computer Vision Project (OpenCV)

We are seeking a skilled freelancer to implement a code in opencv to detect and count the vehicles in a video according to specific requirements and algorithms. The project involves analyzing the video footage and using opencv algorithms to identify and track vehicles. The freelancer should have a strong understanding of computer vision and image processing techniques and be able to work with opencv libraries. The deliverables include a fully functional code that can detect and count vehicles in the video and a report detailing the implementation process and results.

A web App to identify what the user did in a video

I need your help to create a project related with video detention using technologies and libraries like a Video-LLaMa, OpenCV and others, the project is in an definition step. If you are interested in the project and you feel comfortable doing this kind of projects I would be happy to tell you more about this.

Fix my PC-based live image processor (Python/OpenCV)

My Windows PC - based live image processor application runs fine but is unfinished. It needs tweaks as follows: SEE ATTACHED CURRENT APP SCREENSHOT: As a summary: This is a Windows app. It is a live image processor. It takes input from: 1. A local webcam (internal) 2. A USB webcam 3. A URL IP cam (remote streaming) 4. A Video input. Various processing steps can be created, tested then saved as a preset for re-use later. SImilar to the Mirrror platform Methods (presets). Key features are as follows: 1. The app captures a frame of the stream, makes a copy, processes the original versus the copy then generates a result image. 2. It will repeat this for as long as the Loop value is not reached. 3. In the next loop round, the result frame becomes the Original. Then repeats 1. There are several processes between Original Versus Copy. These are called Operators. 1. Addition - Copy added to Original, Subtraction - Copy subtracted from Original, Difference - Difference between RGB values of Original and Copy (+ and - signs ignored), Multiply - Original is multiplied by Copy (values higher than 256 are truncated to 256) 2. FILTERS There are several filters: 1. Gaussian, Median, Average, High Pass, Low Pass, Band Pass and Notch - Original, Copy and Result images must be able to have their own values 3. COLOUR CONTROL There are several colour controls and each of Original, Copy and Result must be able to have their own value 1. Brightness, Contrast, HSL, Intensity, Levels 4. LOOP The processes are looped for as long as the loop value has not been reached. Current loop max value is 20 times. 5. DIGITAL ZOOM The Result Image must be able to be zoomed up too 5,000 times. 6. Each new settings must be saved as a new present - so that each time the preset is selected, the app repeats exactly all the processing steps recorded in that preset. 7. When the Zoom button on a window is pressed, a live screen pops out which can be made full-screen or less. Currently, it just shows a frame. The Zoom value needs to be up to X 5,000. The Levels is not working properly, needs to be fixed to be smooth. The Operators (Subtraction and Difference) need to be fixed/added. The Presets are not saving all values that needs to be fixed. To speed the process up, only the Result window can show live streaming, the original and copy windows can just show the last frame. Also, when a video source is selected, the app runs until the end of the video, then stops. It should continue until the source is changed or the app is closed. I need to be able to save the Result video. (ut works now but the frames take time to to save and is complicated to do. The final thing that was not done is to create a EXE file or a file that can be sent to someone and the click it and the app is installed. So. Practically all is there but needs tweaking as described.

opportunity

Design and implement a drowning person detection rescue system

I want to Design and implement a drowning person detection and rescue system using pattern recognition in swimming pools Simulation Based using ROS, Steps to complete the project: 1. Develop an algorithm using OpenCV to detect a drowning person in the swimming pool. 2. Design a robot using ROS-Gazebo to rescue the drowning person, incorporating prismatic joints and a control algorithm for the bucket. 3. Create a ROS-Gazebo simulation of an arena with specified dimensions and the necessary actuators for the rescue robot. 4. Develop a distance calculation algorithm to determine the distance between the origin and the detected drowning person in the pool. 5. Implement the rescue algorithm, including the derivation of the bucket to the destination. 6. Implement the algorithm that control the position and velocity of the actuator with mathematics. 7. Provide the camera calibration algorithm mathematics and results. 8. Develop the control mathematics for the actuators in sliding forms. 9. Deliver a write-up of the abstract, methodology with results explanation, complete mathematical modeling (Kinematics, inverse kinematics, Odometer), flowsheet diagrams, and algorithms for each step involved in the project. Remember that the complete documentation of the project is very important, with each clear steps, 10. All the project should run on my laptop

opportunity

Mobile / Flutter Developer for Image-Based Distance Measurement

Hello everyone, Exciting news! We're on the lookout for an experienced Android/Flutter developer for a ground-breaking project project base. We are working on an Android application that utilizes image recognition technology for accurate distance measurement within images. Project Overview: Objective: Develop a cross-platform Flutter app capable of measuring distances through mobile camera using advanced image recognition techniques. Key Requirements: Proficient in Flutter app development, experience with integrating image processing libraries (like OpenCV, TensorFlow Lite, etc.), and a solid understanding of image recognition and AI algorithms. What We're Looking For: Proven experience in Android/Flutter app development, particularly in integrating AI and image processing functionalities. Ability to implement efficient and accurate distance measuring algorithms using image recognition. Familiarity with machine learning libraries (such as TensorFlow Lite) is highly desirable. Strong problem-solving skills and the ability to work independently.

2D Avatar Clothing Change Application

I am looking for a skilled developer to create a 2D avatar clothing change application. The goal of the project is to allow users to change the clothing of their avatar in images. The application will overlay different clothing items onto existing avatar images. Key Features: Avatar Dataset: Gather a diverse dataset of avatar images covering various poses, lighting conditions, and backgrounds. Clothing Images: Collect images of clothing items with a transparent background for seamless overlay onto avatars. Image Preprocessing: Resize avatar and clothing images to a consistent size. Optional: Background removal for clothing images. Segmentation Model (Optional): Train or use a segmentation model to identify the region of interest on avatars corresponding to the clothing area. Image Warping: Implement or use image warping techniques to overlay clothing images onto avatars based on segmentation or desired regions. Alpha Blending: Apply alpha blending to seamlessly integrate clothing onto avatars. Adjust transparency based on segmentation masks or specific criteria. User Interface (Optional): Design a user interface for a user-friendly experience, allowing users to upload avatars, clothing, and make selections. Testing and Validation: Ensure the system is robust by testing it with a set of images under various scenarios and lighting conditions. Documentation: Document the code, providing clear instructions on usage, dependencies, and examples for future reference. Optimization (Optional): Optimize the code for performance, considering parallelization or hardware acceleration if needed. Deployment (Optional): If applicable, deploy the project as a service or application. Consider the deployment environment and any additional requirements. Requirements: Proficiency in Python and relevant libraries (e.g., OpenCV, TensorFlow). Experience with image processing, segmentation, and blending techniques. Ability to create a user interface for a seamless user experience (if applicable). Strong documentation skills for future reference and collaboration. Optional: Experience with optimization techniques for performance improvement. Deliverables: Fully functional 2D avatar clothing change application. Source code with clear documentation. Test results demonstrating the robustness of the system. Budget: Please provide a realistic estimate of the budget and timeframe for completing the project. Additional Notes: Feel free to include any additional information or specific requirements you may have for the project.

Android app, OpenCV, Tesseract to scan inventory

Good day sir, I was needing a Android app built that can utilize OpenCV and Google's Tesseract to scan inventory items that come in for our small laboratory. I would like it to be able to identify individual items. Then be able to input how much of said item we received and if the item has a label be able to read the expiration date from said label. Lastly, I would like it to be able to take all this information (description of the item, amount inputted and expiration date) and upload it to a Google sheet.

urgent

Recording soccer game

Objective / Goal We will use a mini computer like the Orange PI 5B (similar to the Raspberry PI) to be able to film the entire soccer field, reaching an angle equal to or greater than 180 degrees. We will join the 3 cameras using Python or any command line or script that the operating system can offer. It will generate 2 final videos: 1-) With the 3 cameras, a video that shows the whole field. 2-) With OpenCV you can track the ball on the field, if you don't detect the ball, keep the current position or try to follow the largest group of people on the field. W x H smaller than video 1 (HD). The final videos will be uploaded to an online server (when you have internet, Wi-Fi connected to the internet). A simple webserver that shows the date and time the video was generated and we can open video 1 or video 2. I already have some commands ready to start the project and the boards for testing, I will be able to carry out the tests. I can send 1 Orange Pi 5b + 3 cameras if needed.