AI Parking Lot Vehicle Counter

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@quan9824

## EXPERT ##(Real-time Object Detection Tracking and Counting) DEAR CLIENT, I’ve completed the exact same projects before successfully. I can upload my previous works. Before, using python and YOLOv8, I completed @@Car Detection Tracking and Bidirectional Counting@@ project. Awarding me will be the fastest way to complete your task with the best rates possible. THANK YOU.

@devanshkhandekar

GOOD - I am a seasoned Applied ML Engineer(6+ yoe) and I've extensive experince with ANPR, vehicle classification,counting and deployment on edge devices -I can build a real-time vehicle counting system using YOLOv8,OpenCV,ByteTrack,& line/zone-crossing logic -The pipeline will classify cars,motorcycles,& trucks,prevent duplicate counts,& handle occlusion,glare,rain,& low-light footage -I previously developed real-time detection/tracking systems involving lane-based object counting,ROI crossing,stable track IDs,confidence filtering,& event logging -Deliverables include Dockerised code,Jetson-compatible optimisation,REST/WebSocket counts,daily CSV reports,weights,README,& demo video -I will validate counting precision on your footage & tune camera-specific thresholds

@manoval09

Dear Client, Thank you for posting this project. I have extensive experience in AI. I'm confident I can deliver high-quality results: - Technical expertise: Proven track record with similar automation projects - Timeline: Efficient delivery with minimal delays - Support: Full testing and debugging included I'm ready to start immediately and am flexible with communication. I would appreciate the opportunity to discuss your specific requirements in detail. Best regards, Petrovich

@iterativeTech

As a seasoned AI/ML engineer with over 5 years of experience, I fully understand and am adept at fulfilling your unique project requirements. My proficiency in technologies like TensorFlow, OpenCV, and Docker, matched with my extensive knowledge and hands-on experience in real-time video analytics, make me an ideal candidate for your AI Parking Lot Vehicle Counter. Drawing from my work across multiple industries such as finance, healthcare, insurance etc., I bring to the table a deep understanding of how to convert raw data into valuable insights. This specifically applies to your project as it necessitates interpreting live feeds from fixed cameras under various conditions. My expertise in building scalable ETL/ELT pipelines for data lakes and data warehouses will ensure reliability even under challenging circumstances. Additionally, my comprehensive skills in cloud automation and data engineering are essential in providing you with a deployable solution. By leveraging AI-driven automation, which I have successfully implemented using Azure Logic Apps and AWS Lambda among others, I can hand-off an efficient system that is easy to setup, run smoothly on your preferred devices and reliably produces REST or WebSocket outputs. Combining this with my passion for delivering business value through driving ROI with intelligent systems makes me the well-rounded choice for your project. Let's exceed your accuracy goal together! Thanks Prem golani

@HASEEB1803

Hi! I am a software and ML developer specializing in computer vision pipelines. I will build a Dockerized, real-time vehicle counting system using YOLOv8 (optimized via TensorRT for Jetson Xavier/GPU) paired with the ByteTrack algorithm to handle occlusions and glare. My approach: Pipeline: OpenCV + YOLOv8 + ByteTrack + Custom Virtual Counting Lines. Accuracy: Exceeds 90% via specialized confidence thresholds for night/rain. Output: FastAPI WebSocket for live tracking + automated daily CSV reporting. I have extensive experience deploying optimized edge-AI systems and robust multi-agent evaluation frameworks. Ready to deliver clean code, Dockerfiles, and weights. Let's connect!

@retinderdeepsing

I am a Deep Learning and Computer Vision researcher/developer with hands-on experience in building AI-based solutions for image classification, object detection, image segmentation, medical image analysis, and real-time computer vision applications with more than 40 publications. I specialize in developing models using Python, TensorFlow, Keras, PyTorch, OpenCV, and transfer learning architectures such as ResNet, EfficientNet, VGG, Inception, U-Net, YOLO, and Vision Transformers. i can help you create camera-based system that reliably counts every vehicle entering or leaving a parking lot. And if you need i can come to site and install it myself, if the site is in india (extra charges for that)

@ssquare489

With over five years of experience in developing smart applications integrated with AI, I am the perfect match for your AI Parking Lot Vehicle Counter project. My previous work at tech giants like Google and Apple has sharpened my skills in data analysis, model deployment, and creating REST APIs—key components of this project. I have successfully built similar customized solutions in past, which is evident from my extensive portfolio (screenshot attached) that reflects my abilities to your count requirements. For your project, I will utilize my expertise in OpenCV and deep-learning detectors (I recommend leveraging YOLOv8 or TensorFlow) to maximize accuracy while ensuring real-time processing on mid-range GPUs. I understand the nuances of handling occlusions, night lighting, rain, and glare that parking lot cameras usually deal with—a powerful addition to bolstering the system’s robustness. As a developer, transparency is paramount to me—I ensure clients are well-informed about every step of development. Delivering clean, well-commented source code, pre-trained weights, setup guides (README), and even a short demo video align with my desire to ensure complete satisfaction.

@sailokhande29

I have 5+ years of experience in Computer Vision, Deep Learning, and AI-based automation projects. I have developed similar real-time vehicle detection and counting systems using YOLOv8, OpenCV, tracking algorithms, REST APIs, and Docker deployment. I can build a lightweight parking analytics system supporting cars, motorcycles, and trucks with live counting, CSV reports, and edge deployment on Jetson/Xavier-class devices. I will provide clean source code, trained weights, setup documentation, and demo video. I have attached screenshots of my previous AI vision projects for reference. I can start immediately and deliver a tested solution.

@MoviesLiker

Hey i can build this. Last year i build a face recognition to attendence marking tool using opencv. Last week nvidia realated locatAnythink 3b vission model. A lightweight model can run in 4gb ram. It was best fit for you. It's accurate rate was 90%

@jabulanix

We've just completed a similar project, helping someone achieve their goal successfully. Our professional and reliable solution can assist you in reaching your objective seamlessly. I have a vast experience in completing projects outside Freelancer.com and am currently offering discounted rates to establish my reputation here. Payment is only required if the final work meets the agreed scope and requirements. I'd love to chat about your project! The worst that can happen is you walk away with a free consultation. Regards, Jabu.

@usamaKhan577

Hi, I hope you are doing great. I have hands-on experience building computer vision solutions using YOLO, OpenCV, TensorFlow, and NVIDIA Jetson platforms. Recently, I worked on vehicle and object detection systems optimized for real-time inference and edge deployment. For your parking lot project, I can develop a Dockerized solution that accurately count cars, motorcycles, and trucks, supports live RTSP/video feeds, handles challenging conditions (night, glare, rain, occlusions), and provides REST/WebSocket APIs with CSV reporting. The system will be optimized for Jetson Xavier and mid-range GPUs, with clean code, documentation, trained weights, and a demo video. Looking forward to discussing your test footage and requirements.

@simonj29

Hello, I can build your AI-powered vehicle counting system for parking-lot entrance/exit monitoring. I have experience with OpenCV-based video pipelines, YOLO object detection, tracking logic, camera stream handling, Docker deployment, and real-time dashboard/API outputs. The system will detect and separately count cars, motorcycles, and trucks from live or recorded video. I will implement configurable camera URLs, FPS control, counting zones, REST/WebSocket live count output, and automatic daily CSV reports. For robustness, I will tune the pipeline for occlusion, night lighting, rain, glare, and camera-angle issues using your test footage. Final delivery will include source code, weights, Docker setup, README, validation results, and a demo video.