Shooting Target Detection

@albertc1996

Hi, you need a C++ computer vision pipeline that maps B27 scoring rings despite skew, lighting, and bullet-hole noise. I’d build this with OpenCV in C++: paper boundary detection with homography correction, target center estimation using silhouette landmarks, then parametric Lamé/superellipse ring projection instead of fragile Canny/Hough matching. The CLI tool will accept an image path and output a corrected annotated image with X, 10, 9, 8, and 7 rings drawn consistently. I recently built an OpenCV inspection pipeline that improved object boundary detection accuracy by 35% under noisy image conditions. Available to start immediately. Quick questions: do you have sample B27 photos and known target dimensions? Best regards.

@toriquldev123

Hello There! I’m Md Toriqul Islam, and I’m excited to partner with you & I can dive into your project immediately. I’m an experienced C++ Computer Vision engineer specializing in OpenCV, image reconstruction, and robust detection systems. I understand you need a C++ CLI tool that can detect a B27 shooting target from smartphone images, correct perspective distortion, and accurately reconstruct scoring rings (X, 10, 9, 8, 7) even with heavy bullet-hole noise and angled photos. The key challenge is reliable geometry recovery, not basic edge detection. I have rich experience in C++, OpenCV, homography transformation, contour analysis, and robust vision pipelines for noisy real-world images. I am skilled in perspective correction, object center estimation, and superellipse-based shape modeling for accurate ring reconstruction. My approach includes automatic target boundary detection, homography warping, center estimation, and mathematically driven ring overlay to ensure stable results under distortion and occlusion. I’m ready to start immediately and deliver a modular, production-ready C++ solution. Looking forward to hearing from you. Best regards, Md Toriqul Islam

@aidigitalhub

As a researcher and technologist who prides themselves on staying up to date with the constantly evolving technology landscape, I fully understand the importance of choosing the right technology stack to build robust systems. In line with your project requirements, my proficiency in Python ensures that I can effectively deliver a C++ script tailored specifically to your needs. My expertise also extends to computer vision, with a notable focus on image processing, edge detection, and morphology. Your project's most intricate challenges like bullet holes, perspective distortion, and ring shape detection all fall under my core competencies. Throughout my career, I've successfully tackled similar issues using advanced techniques and custom-built algorithms that accounted for nuanced differences. Lastly, I value long-term solutions that can easily be maintained and extended as needed. My experience as a technology strategist allows me to see beyond immediate needs and design comprehensive systems that anticipate future requirements. So, if you're looking for an adaptable professional who combines technical prowess with strategic foresight, then I am excited to take on your shooting target detection project. Together we can build a solution that will accurately map your scoring rings every single time.

@cindyviorinar

Hi there, I understand you're looking for an experienced Computer Vision Engineer to build a robust Python script for detecting and mapping scoring rings on a B27 shooting target captured in various angles and lighting conditions. I'm confident in taking on this challenge, as I have extensive experience in OpenCV and image processing. To address the unique challenges posed by bullet holes, perspective distortion, and the non-standard shapes of the rings, I will implement a comprehensive approach. First, I'll create a CLI tool that takes the image path as input. Then, using advanced techniques, I'll automatically detect the paper boundary and apply perspective correction to flatten the image. Next, I will accurately detect the target's center by locating the human silhouette, which typically remains intact. Finally, I'll project the superelliptical scoring boundaries over the image and output a new image highlighting the rings clearly, despite the noise from bullet holes. I am available for real-time communication based on your time zone and can provide a simple demo or a portion of the project within 12 hours of commencement. Q1: What type of smartphone camera resolution do you expect the photos to be? Q2: Are there specific environmental conditions I should consider during the implementation? Q3: Do you have any preferred libraries or tools aside from OpenCV? Looking forward to your response! Best regards, Cindy Viorina

@RavenDetector

Hello, I have read your target detection scope carefully, and this is a strong fit for a practical computer vision build in c++. You need a pipeline that can find the B27 paper, correct perspective, locate the target center, and draw the scoring rings reliably even when bullet holes break the visible lines. I would build that as a robust OpenCV based c++ script with geometry driven target recovery, not a fragile edge detection demo. The best approach is to combine paper boundary detection, homography correction, and model based ring reconstruction for the B27 layout. I would use contour and line reasoning for the outer target, then estimate the center from the target structure and expected silhouette region, and finally project the X, 10, 9, 8, and 7 rings using the B27 superellipse parameters. This keeps the output stable across angle, lighting, and damaged paper. Technically, I would implement CLI input, image preprocessing, target segmentation, corner and boundary extraction, perspective warp, and ring overlay rendering in c++ with OpenCV. If needed, I can also add a fallback detector for partial occlusion so bullet holes do not disrupt the geometry. The final output would be a cleaned image with the mapped rings drawn in the correct position for later scoring. I can communicate in real time in your time zone and provide a simple demo or part of the project within 12 hours of starting. Q1: Do you have a reference B27 template with exact ring dimensions and center posi

@Zeemeeservices

Hello, With over 9 years of experience as a Senior Full-Stack and DevOps Engineer, I am equipped with the skills to make your Python OpenCV Shooting Target Detection project a complete success. While I notice you mentioned wanting the project in C++, I assure you that my deep familiarity with Python will be tremendous for this task. Here's how my skillset aligns with your envisioned solution. Firstly, my expertise in Frontend Development, Backend Systems, and AI & Machine Learning will be invaluable for addressing the distinct challenges posed by bullet holes, perspective distortion, and ring shapes. Being able to identify the paper boundary, correcting perspective using homography, locating the target center and eventually locating the scoring boundaries - these are all tasks well within my area of expertise. Moreover, I've dealt with similar complex algorithms throughout my career and have successfully delivered high-performance systems that scale under demanding workloads. In this project too, I'll give utmost importance to precision in detecting scoring rings while ignoring any noise from bullet holes. With such deep thoughtfulness about system design and long-term product success, I guarantee not just a functional but a highly efficient solution - one that is production-ready and future-proof. So, let's build your vision, intelligently and robustly - together! Thanks! Chibike

@weetz

Hello, With my extensive background in software engineering, computer vision and automation, I'm confident that I possess the skills necessary to tackle the unique challenges of your project. I have a strong command of Python, which is ideal for this task and will allow me to successfully develop a script that solves each of your identified hurdles, from bullet hole detection to perspective distortion correction. One of my core competencies lies in creating algorithms that are both ingenious and flexible enough to handle real-world scenarios. This has equipped me well to address the issue of skewed or angled images resulting from smartphone photography. My understanding of homography will enable me to accurately identify the paper boundaries and apply perspective correction, ultimately providing you with flat images for analysis. Another distinct advantage I bring is my penchant for thinking beyond conventional solutions. In dealing with the non-uniform shape of B27 rings, I won't simply rely on standard ellipse fitting methods. I'll explore and implement alternative techniques such as Lamé curves (superellipses) that better align with the true shape - ensuring told story accurateósito during realimaçond. Ultimately, what sets me apart is not just my skill set, but rather my drive and passion for transformative software solutionsoured by aninquisitive nature. In partnering with you on this project, I'll be dedicated to surmounting Thanks!

@morganc59

As a seasoned Computer Vision Engineer with deep expertise in OpenCV and python, I am well-suited to script development for this project. Throughout my career, I have crafted and deployed sophisticated solutions for object detection, image classification, OCR, tracking, and video analytics - all of which make shooting target detection a familiar territory for me. Being passionate about real-world AI applications, I find great interest in your project and am committed to bringing my skills and dedication to provide valuable results. Moreover, I understand the peculiar challenges present in this task, namely the presence of bullet holes disrupting traditional edge detection, perspective distortion due to user photography angles, and the complex shape of the rings which cannot be matched using conventional algorithms like cv2.fitEllipse. My extensive experience allows me to tackle these difficulties with deftness and insight, leveraging complementary techniques such as deep learning. The end goal of accurately detecting and mapping scoring rings with no interference from bullet holes or skewed perspectives aligns perfectly with my commitment to precision-driven AI solutions. My vision is to build an algorithm that not only meets but exceeds expectations. To accomplish this, I will dedicate ample time to calibrate my approach based on the incoming dataset nuances unique to your project. Choose me today and let's achieve efficiently what few can do immaculately!

@alanf37

As a determined and detail-oriented Computer Vision specialist, I am confident in my ability to deliver an impeccable Python script that meets and exceeds the needs of your shooting target detection project. My extensive experience has well-prepared me for the unique challenges posed by this task, such as dealing with bullet holes that often obscure traditional detection methods. For instance, I have adeptly approached similar problems in my previous engagements by incorporating advanced edge detection techniques beyond the standard Canny/Hough, allowing for a much higher success rate. Additionally, I have the expertise required to handle not only perspective distortion generated by users taking photos at varying angles but also to accurately detect superellipses — exactly what you need to map the scoring rings on B27 shooting targets. Understanding your business and project requirements is crucial, and it's an area where I excel. I believe that reaching a 100% result doesn't come from just technical skills; it comes from having a comprehensive understanding of the problem at hand and an unwavering commitment to solve it effectively. I guarantee you a great experience on this project – professional approach, open communication throughout the process, and ultimately delivering an exemplary Python script that maps and scores bullet impacts impeccably

@pedrowilberthr2

Hello, I’m Pedro Wilberth, and I’m proposing a robust C++ OpenCV solution for your B27 target project. The CLI tool will take an image path, perform automatic perspective rectification, detect the paper boundary, and flatten the page for consistent analysis. It will then locate the target center reliably (using robust cues beyond damaged edges) and project the scoring boundaries as superellipses (Lamé curves with power n=4) to overlay X, 10, 9, 8, and 7 rings even under bullet holes and variable lighting. The pipeline will use contour-based boundary detection, perspective warp, and parametric fitting with noise rejection to ignore bullet holes while preserving ring geometry. The output will be a new image with the rings highlighted and ready for scoring, with a compact, extendable C++ module and a simple CLI interface for image path input. Best regards,

@mkrimando

Hi, I can build this in C++ using OpenCV, with the logic focused on model-based target detection instead of fragile edge detection. For this B27 target, I’d handle it by first detecting the paper boundary and applying homography correction, then locating the target center from the silhouette/body structure, and finally projecting calibrated superellipse scoring rings for X, 10, 9, 8, and 7. This avoids relying on broken ring edges, so bullet holes won’t confuse the detection. I’ve worked with OpenCV image processing pipelines involving perspective correction, contour analysis, shape fitting, masking/noise rejection, and geometric overlay generation. I can provide a CLI-based C++ tool that takes an image path and outputs the corrected image with the scoring rings drawn. I’d also keep the implementation clean and adjustable, so ring dimensions/thresholds can be tuned for different B27 photo conditions. Available to start and discuss sample images.

@GridsmithLTD

Hello, I've reviewed your project and understand you're looking for a robust C++ computer vision pipeline that can detect and reconstruct B27 target scoring regions from difficult smartphone photos despite bullet hole damage, perspective distortion, and non-standard superellipse geometry. This is far beyond a basic OpenCV contour detection task because the algorithm needs to remain stable under heavy structural noise while fitting Lamé curve style scoring boundaries instead of ordinary ellipses. I can build this in C++ using OpenCV with a staged pipeline covering homography correction, silhouette-based center localization, noise-resistant geometric fitting, and superellipse projection so the final overlay remains accurate even when the printed rings are partially destroyed by impacts. The CLI workflow and annotated output rendering can also be structured cleanly for future scoring expansion. You can review my work here: https://www.freelancer.com/u/GridsmithLTD Do you already have a labeled dataset of target photos across different lighting and angle conditions for validation, or would the algorithm need to generalize from a smaller sample set initially? Regards, Atik

@nutankumarftp

With a specialization in full stack development and extensive experience in Python, I am confident in my ability to tackle your Python OpenCV shooting target detection project. Your unique project needs go far beyond basic OpenCV tutorials, and that's exactly where I thrive. My approach is not only to identify and rectify the challenges but to build ingenious solutions around them. I recognize that detecting scoring rings within a target image that is riddled with bullet holes, often skewed, and containing non-elliptical superellipses, requires a comprehensive plan. From finding the physical paper boundary, applying perspective correction using homography, locating the center of the target using human silhouette detection to eventually detecting or projecting exact scoring boundaries- I'm equipped to handle it all. Moreover, apart from my ample Python skills, I bring along years of problem-solving acumen developed through API integrations, database management & optimization, performance enhancements and security measures. My clients appreciate my swift responsiveness that dramatically reduces the back-and-forths and ensures timely delivery without compromising on quality. So let's nail this project together!

@MDshimulBD

With my extensive experience as a Full-Stack Developer for over a decade, I have not only mastered various programming languages but more importantly, the art of problem-solving. As such, I believe I would be an ideal fit for your Python shooting target detection project. While your project does require skills in C++ and OpenCV, my adeptness in transforming complex tasks into simplified and efficient solutions coupled with my aptitude in computer vision makes me competent in handling such a challenging project. I understand the three key obstacles we face here: bullet hole destruction, perspective distortion, and ring shape complexity. My proficiency will allow me to creatively think beyond the regular 'find edges' approach that fails with destroyed lines and ResponseEntity ServiceUnavailableException:503 even develop an adaptive algorithm that can intelligently counter bullet holes. Desensitizing solid objects like bullet holes while accurately detecting scoring boundaries is one skill I proudly possess.

@rafaels170

Hello, I have experience with C++ and computer vision, having developed image processing algorithms that involve shape recognition and perspective correction for applications like augmented reality and sports analytics. For your project, I can build a script that utilizes advanced contour detection combined with machine learning techniques to accurately identify the scoring rings amid bullet holes. A technical scenario could involve preprocessing the image to enhance ring visibility before applying perspective transformation and contour mapping. Let's discuss!

@sebartian

Hi, I can build a robust C++ (OpenCV-based) solution to detect, correct perspective, and accurately map B27 scoring rings—even with heavy bullet-hole noise. I’ll handle homography, center detection, and custom superellipse fitting for precise ring projection. Clean CLI tool + tested output included. Ready to start.

@sendiw

Saya sendi wahyuzan, dan saya memang pemula di sebuah platform freelance ini, tapi tidak pemula didalam proyek ini Saya tidak mau banyak janji atau sesuatu Yang melebih lebihkan , tapi hasil kerja yang saya pertanggung jawabkan dengan skill saya Saya siap mulai mengerjakan proyek Anda dan menyelesaikannya sesuai keinginan atau jadwal yang ditentukan, Saya menantikan kabar dari Anda. Sendi wahyuzan. 

@donm91

Hello, I understand you need a robust C++ script to detect and map scoring rings on B27 shooting targets from smartphone photos. The challenge arises from bullet holes obscuring edges, perspective distortions, and non-standard superellipse ring shapes, making traditional edge detection insufficient. I have extensive experience in Computer Vision and C++ development, including advanced OpenCV techniques, image processing, homography, and shape analysis. I’ve successfully built systems for object detection and perspective correction under noisy and distorted conditions. My approach: I will implement automated paper boundary detection and perspective correction, locate the target center using resilient visual cues, and accurately project the superellipse scoring rings while ignoring bullet hole noise. The script will take an image path via CLI and output a processed image with highlighted rings. You can expect a precise, reliable, and maintainable solution suitable for real-world images, ensuring minimal errors and robust performance. I look forward to helping you achieve fully automated target mapping.

@saraha083

Hello, I understand you need a C++ script to detect and map scoring rings on B27 shooting targets from smartphone photos. Challenges include bullet holes disrupting edges, perspective distortions from angled photos, and the superellipse shape of the rings that standard ellipse detection cannot handle. I have extensive experience in Computer Vision using C++ and OpenCV, including perspective correction, robust shape detection, and noise-tolerant algorithms. I’ve successfully developed systems for object detection and geometric mapping under noisy and distorted conditions. My approach: The script will take an image path via CLI, detect and correct the target’s perspective, locate the center using resilient cues like shoulders or head, accurately project the superellipse scoring rings while ignoring bullet holes, and output an image with highlighted rings. You can expect a reliable, maintainable solution capable of processing real-world images accurately and efficiently. I look forward to delivering a robust automated target mapping system.