Computer Vision Application for Warehouse Inventory Classification and Counting
₹12500-37500 INR
Closed
Posted 4 months ago
₹12500-37500 INR
Paid on delivery
Project Overview:
We're seeking an experienced freelancer to develop a computer vision application using Python to classify and count inventory from a warehouse conveyor using a camera. The application will be used to count purchase inventory in retail, distributor, and wholesale warehouses.
Inputs -
Product Images from different angles for training
Image/Video stream from of products from a camera.
Outputs-
Products List from the video/image along with Count
Other informations – Product price, Batch, Expiry (If readable)
Project requirements -
Accuracy: Achieve high accuracy (>95%) in inventory classification and counting.
Efficiency: Optimize the application for real-time processing and efficient use of computational resources.
Scalability: Design the application to handle varying volumes of images and videos.
Technical Requirements:
1. Computer Vision Expertise, Preferrably YOLO: Proven experience in computer vision, image processing, and object detection. YOLO experience or knowledge would be highly advantag. Here is a sample YOLO demo
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2. Python Proficiency: Strong proficiency in Python programming language, including popular libraries such as OpenCV, TensorFlow, and PyTorch.
3. Image/Video Processing: Experience with image and video processing techniques, including object detection, segmentation, and classification.
4. Machine Learning: Familiarity with machine learning concepts and algorithms, including supervised and unsupervised learning.
5. Deep Learning: Experience with deep learning frameworks, such as TensorFlow or PyTorch, and architectures, such as CNNs and RNNs.
Deliverables:
1. Source Code: Well-documented and commented source code for the computer vision application.
2. Documentation: Technical documentation, including architecture, design, and implementation details.
3. Testing: Thorough testing and validation of the application to ensure accuracy and efficiency.
Nice-to-Have Skills:
1. Experience with Warehouse Management Systems: Familiarity with warehouse management systems and inventory management software.
2. Knowledge of Retail, Distributor, or Wholesale Industry: Understanding of the retail, distributor, or wholesale industry and its inventory management challenges.
What We Offer:
1. Competitive Compensation: We offer competitive compensation for the successful completion of the project.
2. Opportunity for Future Collaboration: We're looking for a long-term partner to collaborate on future computer vision projects.
We would seek an initial POC product developed with YOLO which can count a limited set of products.
If you're an experienced computer vision developer with a strong background in Python, machine learning, and deep learning, we'd love to hear from you!
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
Hello
I can help you to develop a Computer Vision product for your warehousing using YOLO and OpenCV(for possible picture preprocessing)
The project is not really hard to do As I have done similar job for postal services. That project was for classifying packages(parcels, letters etc.)
To find a common ground please answer the questions below:
1) What is the camera model? Camera gamut and resolution is really important here.
2)What is the distance from camera to the conveyor?
3) How many products or product categories are we looking?
4) Where should be this model deployed ? is it a server with GPU or some IoT?
I’m happy to discuss the details over chat, and I will respond promptly.
Thanks for your attention
Archil
Hi,
I’m an AI expert with professional experience in computer vision, with a proven track record of working on complex image processing and AI/ML model development. With skill sets:
• Algorithm Development: Strong understanding of computer vision algorithms and techniques, including convolutional neural networks (CNNs), object detection, image segmentation and feature extraction.
• Model Training & fine-tuning: Develop and train machine learning models tailored for image analysis and visual data interpretation. I have worked on some well-known models like YOLO, RCNN, U-Net, Deeplab, ViT etc.
• 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.
• Data Handling: Experience in handling and processing large datasets, including image and video data. Familiarity with data augmentation techniques and synthetic data generation.
• Performance Optimization: Optimize algorithms and models for real-time processing and ensure they can handle large-scale data efficiently.
• Programming Skills: Proficient in programming languages such as Python. Experience with deep learning frameworks like TensorFlow, PyTorch, or Keras.
• Tools & Libraries: Proficiency with OpenCV, scikit-image, and other relevant libraries. Experience with version control systems like Git.
i have 13 years Experience in same required Skills, We already did kind of project many times, We provide support for over 150 technologies worldwide, ensuring comprehensive solutions for our clients. Our global reach allows us to connect with diverse industries and address various technological needs. We pride ourselves on delivering reliable and efficient support services. Our dedicated team is available 24/7 to assist with any technical issues. Partner with us to experience seamless and innovative technology support
Hello,
I am a researcher and trainer in computer vision, machine and deep learning having PhD in Computer Science with 25+ years of experience. I have worked on several research projects in these domains with few research publications as well. I have strong theoretical knowledge with hands-on experience in AI/ML, Computer Vision, python, OpenCV, Tensorflow, MATLAB etc.
I do possess state-of-art knowledge of computer vision topics including image and video processing, image enhancement, image classification, object detection, object recognition, image segmentation, image measurements etc. along with deep learning techniques. I have built customized YOLO models for specific requirements.
Hope to have further discussions in this regard to know more.
Thanks.
As a passionate advocate of AI and a seasoned specialist in the realms of machine learning and Python programming, I am well-equipped to undertake your project for developing a computer vision application for inventory classification and counting. With an impressive track record of crafting advanced, tailor-made artificial intelligence solutions, I've gained extensive expertise in areas crucial to this task - including computer vision with YOLO specifically - tailored towards addressing diverse and complex business challenges.
In past projects, I have successfully deployed robust machine learning algorithms as well as deep learning architectures like CNNs for object detection, all skills that are directly transferable and imperative for this venture. My proficiency along with popular libraries such as OpenCV, TensorFlow, and PyTorch greatly streamlines implementation efforts for accurate and efficient image and video processing.
Moreover, my experience with predictive analytics and demand forecasting also makes me an asset when it comes to scalability. I understand that different volumes of images and videos are a part of your requirement, creating the need for an application that can handle these fluctuations without compromising accuracy or efficiency.
Hi,
I have hands-on experience in developing computer vision applications for real-time object detection and classification, particularly using YOLO and deep learning models. I have successfully implemented inventory tracking and counting solutions in warehouse environments, optimizing for accuracy and efficiency.
For this project, I propose an initial Proof of Concept (POC) using YOLO to classify and count a limited set of products from the conveyor feed. The model can be refined further with additional training data to improve accuracy and scalability.
A few clarifications:
1. Do you have a labeled dataset of product images, or should I handle data collection and annotation?
2. Will the model be deployed on an edge device (e.g., Jetson, Raspberry Pi) or a cloud-based server?
3. Are there specific warehouse management systems (WMS) you’d like the solution to integrate with?
Looking forward to discussing how we can build a robust and scalable system.
Best regards,
Zahid Hassan
I have extensive experience in developing computer vision applications using Python, and I am confident in my ability to deliver a robust solution for real-time inventory classification and counting on warehouse conveyors. With hands-on expertise in object detection frameworks like YOLO (You Only Look Once), along with deep knowledge of OpenCV, TensorFlow, and PyTorch, I can build an accurate and efficient system capable of detecting and counting products with over 95% accuracy. I have previously worked on real-time video processing applications where speed and accuracy were critical, and I understand how to optimize models for performance in resource-constrained environments.
Additionally, I am well-versed in deep learning architectures, machine learning workflows, and integrating OCR techniques to extract supplementary information such as product price, batch, and expiry dates when visible. My approach includes clean, well-documented code, comprehensive testing, and scalable design, ensuring the system can grow with your inventory needs. With a deep understanding of retail and wholesale workflows, I’m prepared to build an effective proof of concept and collaborate with your team on long-term computer vision initiatives that align with your operational goals.
Hi,
I’m an experienced software engineer and AI researcher with 10+ years of development and 5+ years of deep learning experience. I've previously worked on sensor data processing and deep learning-based computer vision systems, including real-time object detection and tracking for UAVs.
I have hands-on experience with YOLO (v4 & v5), TensorFlow, and PyTorch. I can build a POC system to detect and count warehouse inventory with high accuracy rates using product images and video streams. I will focus on modular code, clean architecture, and efficient real-time processing.
I'm offering:
Accurate and fast YOLO-based object detection
Optimized video processing with OpenCV + DL
Documentation and clean Pythonic code
Expandable structure for future product sets
Looking forward to collaborating with you.
With over 8 years of experience in computer vision, I am confident that I am the right fit for your project on developing a computer vision application for inventory classification and counting in warehouses. My proficiency and proven track record in using Python—specifically OpenCV, TensorFlow, and PyTorch—combined with my deep understanding of image and video processing techniques will provide an accurate, efficient, and scalable solution for your needs.
Moreover, I have a strong grasp of machine learning and deep learning algorithms. This includes experience working with YOLO, which will undoubtedly be advantageous for this project. You can count on me to build a well-documented and commented source code, provide technical documentation on the architecture and design details, as well as ensure thorough testing and validation.
Furthermore, I offer not only competitive compensation but also the potential for future collaboration. As you mention
With several years as a full-stack and WordPress developer, I have leveraged my skills in Machine Learning (ML) and Python to provide robust solutions across various domains. Through my work on highly-dynamic and multi-faceted projects, I have developed a deep knowledge of computer vision, object detection, and image processing - all indispensable in maroperating warehouse inventory classification and counting applications like the one you need. In leveraging cutting-edge technologies such as YOLO for efficient inventory management, I am confident that I can exceed your expectations.
Not only do I possess an in-depth understanding of the technical side of this project, but I also bring with me the tenacity and dedication that’s needed to ensure its success. Given my strong proficiency in Python and experience with popular libraries such as OpenCV, TensorFlow, and PyTorch, I can adeptly optimize your application for real-time processing while ensuring it runs efficiently on your computational resources. My expertise in machine learning concepts and algorithms, as well as deep learning frameworks and architectures, are equally essential for meeting your accuracy and performance benchmarks.
In addition to the technical acumen required, my experience working with Warehouse Management Systems is a valuable bonus. This gives me a nuanced understanding of the retail, distributor, and wholesale industry - allowing me
Greetings Client,
I came across your project, and I’m excited about the opportunity to develop a computer vision application for inventory classification and counting. With my expertise in Python, YOLO, and deep learning, I can help you achieve high accuracy (>95%) while ensuring real-time efficiency and scalability.
My Approach:
✔ YOLO-Based Object Detection – Using YOLO for fast and accurate inventory classification and counting.
✔ Image & Video Processing – Leveraging OpenCV, TensorFlow/PyTorch for seamless analysis.
✔ Real-Time Optimization – Efficient processing for handling warehouse conveyor feeds.
✔ Scalability – Designing the application to handle varying product volumes.
Deliverables:
Well-structured Source Code with comments.
Technical Documentation outlining architecture and implementation.
Thorough Testing & Validation to ensure reliability.
Initial POC (Proof of Concept) – A functional demo using YOLO on a limited product set.
Why Choose Me?
✅ Expert in Computer Vision & Machine Learning (YOLO, OpenCV, TensorFlow, PyTorch).
✅ Experience in Warehouse & Inventory Systems – Familiar with industry challenges.
✅ Proven Track Record in delivering AI-driven solutions.
Let’s discuss your requirements further—I’d love to collaborate on this project and explore future opportunities!
Looking forward to your response.
I have extensive experience in computer vision and deep learning, specializing in YOLO-based object detection. I have worked on real-time inventory tracking, image classification, and object counting using Python, OpenCV, TensorFlow, and PyTorch.
For this project, I will:
✅ Train a high-accuracy model (>95%) for product classification & counting.
✅ Optimize it for real-time processing using YOLO.
✅ Ensure scalability for handling various image/video volumes.
Looking forward to discussing further.
I have expertise in YOLO, deep learning, and image/video processing and can develop an efficient computer vision solution for your needs. I can deliver a POC for product counting, well-documented code, and optimized performance. Let’s discuss how I can help!
As a Python practitioner with an undying passion for data, I can tell you that the Warehouse Inventory Classification and Counting project fits perfectly into my expertise. My experience in computer vision, image processing, and object detection (including YOLO), coupled with my knowledge of popular Python libraries like OpenCV, TensorFlow, and PyTorch equip me to handle this challenge with finesse.
I have a solid grounding in machine learning - both supervised and unsupervised learning - which will help me develop a high-precision model to classify and count the varying inventory stock. My hands-on experience within deep learning frameworks such as TensorFlow and PyTorch bolsters my potential to implement state-of-the-art architectures like CNNs and RNNs to extract intricate information from the images or video streams we'll be working with.
Beyond technical prowess, I also offer documentation expertise, for the life-cycled welfare of your project. My approach combines thorough testing with meticulousness in keeping security loopholes at bay - ultimately ensuring your data is safe at all times whilst being readily available as you need it. On top of these proficiencies, I must admit I find great appeal in the long-term aspect of this project - an opportunity to nurture a professional bond and take on more projects of similar nature in future. So why not team up and set new standards in inventory analysis?
I like this project and can finish it with my hands.
I will do it my best, I will put all my effort on it ,
No one can do it better than me,
I have more than 10 years experience on similar projects, trust me ,feel free to contact me at anytime.
Send me with email or WhatsApp.
Thansk
I have excellent experience in computer vision and artificial intelligence using Python, with previous experience in using libraries such as OpenCV and TensorFlow for image analysis and object detection. Although I haven't used YOLO practically before, I am familiar with deep learning concepts and have the ability to quickly learn advanced techniques like YOLO. ??
I am capable of applying techniques such as YOLO to develop an accurate and efficient application for classifying and counting inventory using a camera in warehouse environments. With my experience in machine learning, I will be able to train a model using multiple product data, improve the accuracy of the application, and develop it to work in real-time video environments. ?⚙️
I am committed to delivering high-quality results and am eager to continue learning new techniques and improve the application quickly and efficiently using the appropriate tools. ??
I am excited to submit my proposal for developing a computer vision application for inventory classification and counting using Python. With expertise in computer vision, deep learning, and machine learning, I can deliver a high-accuracy YOLO-based object detection model optimized for real-time processing.
Being a senior AI developer, I bring immense computer vision expertise to tackle the challenges mentioned in your project description. My proficiency with Python and knowledge of YOLO have been applied productively in building robust computer vision systems. The project you listed aligns perfectly with my skills and areas of expertise such as object detection, image classification, key-point detection, action recognition, GUI development and more. I have designed numerous computer vision applications that require high accuracy, real-time processing, and efficient use of computational resources - all traits essential to count and classify inventory in warehouses.
Hiring me assures competitive compensation for meticulous delivery and opens doors for prospective collaborations on future AI projects. Let's explore the POC opportunity together and build a system using YOLO that proves its mettle by counting a limited set of products accurately and swiftly. With me on board for this project, you can rely on the best AI engine prioritizing accuracy and processing speed to optimize your warehouse inventory management while saving costs and enhancing productivity.
