YOLO YOLOv5 AI technology Top Builders

Explore the top contributors showcasing the highest number of YOLO YOLOv5 AI technology app submissions within our community.

YOLO v5

YOLOv5 is a family of object detection architectures and models pretrained on the COCO dataset and created By Ultralytics Team in 2020. This architecture uses single Neural Network to process entire image. It divides image into regions and predicts bounding boxes and probabilities for each region. These bounding boxes are weighted by the predicted probabilities. YOLOv5 is available in the Hub as a PyTorch module. You can use it directly in your code or in the Hub.

General
Relese date	June 25, 2020
Author	YOLO
Repository	https://github.com/ultralytics/yolov5
Type	Real time object detection

Libraries

Discover YOLOv5

YOLOv5 Repository Object detection architectures and models pretrained on the COCO data set
YOLOv5 Documentation GPT-4 Product description page
PyTorch Hub

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YOLO YOLOv5 AI technology Hackathon projects

Discover innovative solutions crafted with YOLO YOLOv5 AI technology, developed by our community members during our engaging hackathons.

Pyropulse

Pyroplus presents a comprehensive solution to address the urgent challenges of wildfire management. Integrating IoT technology, AI algorithms, drones, and eco-friendly chemical materials, our system detects wildfires early using air quality sensors, analyzes data in real-time to guide response efforts, and employs drones for aerial surveillance and strategic firefighting. Our innovative chemical material, composed of cellulose, colloidal silica, sodium nitrite, and ammonium chloride, swiftly extinguishes fires while minimizing environmental impact. By combining cutting-edge technology with sustainable practices, Pyroplus aims to revolutionize wildfire management, protect ecosystems, and safeguard communities from the devastating effects of wildfires. Our LLM agent plays a pivotal role in enhancing public awareness and offering crucial instructions for fire protection. With a focus on preventing human-caused fires, which account for a staggering 95% of incidents, our agent acts as a proactive guide. Through informative content and clear directives, it empowers individuals with the knowledge needed to prevent wildfires, fostering a community-driven approach to fire safety.

Netra - AI Enabled Imaging device for MSMEs

How Netra Works Installation: Netra seamlessly integrates into your existing infrastructure. Data Collection: Netra gathers data over time, learning and adapting to your environment. Netra Edge Analytics (Cloud Platform): Our cloud platform processes the collected data, providing actionable insights. Proof of Concept (POC): We develop a POC to showcase the potential of Netra in your specific use case. Deployment & Testing: Once approved, Netra is deployed with rigorous testing to ensure reliability and accuracy. Continuous Improvement: We continuously refine and enhance Netra's capabilities based on feedback and real-world usage. Netra Edge Analytics Netra Edge Analytics Services Data Collection: Gather data from Netra devices securely and efficiently. Data Pre-processing: Clean, preprocess, and transform raw data for analysis. Data Annotation: Annotate data to train machine learning models effectively. Model Deployment: Deploy trained models onto Netra devices seamlessly. Supported Tasks Netra Functions Where? Manufacturing 🏭 Product Counting: Track inventory levels with precision. 🔍 Defect Detection: Identify flaws in products accurately. 📋 SOP Compliance: Ensure adherence to industry standards seamlessly. Logistics/Transportation 🚚 Worker Safety Monitoring: Ensure the safety of your workforce in real-time. 🛒 Vehicle Stability: Optimize loading operations and prevent accidents. Petrochemicals ⚠️ Accident Prevention: Mitigate risks associated with hazardous chemical handling. Security 🔒 Real-time Alerts: Stay ahead of potential threats with proactive notifications. Retail 🛍️ Customer Behavior Analysis: Gain insights into consumer behavior for informed decision-making. Custom Use Cases 🔧 Tailored Solutions: Adapt to your unique business needs with custom implementations.

Visionary Plates

Visionary Plates: Advancing License Plate Detection Models is a project driven by the ambition to revolutionize license plate recognition using cutting-edge object detection techniques. Our objective is to significantly enhance the accuracy and robustness of license plate detection systems, making them proficient in various real-world scenarios. By meticulously curating and labeling a diverse dataset, encompassing different lighting conditions, vehicle orientations, and environmental backgrounds, we have laid a strong foundation. Leveraging this dataset, we fine-tune the YOLOv8 model, an architecture renowned for its efficiency and accuracy. The model is trained on a carefully chosen set of parameters, optimizing it for a single class—license plates. Through iterative experimentation and meticulous fine-tuning, we address critical challenges encountered during this process. Our journey involves overcoming obstacles related to night vision scenarios and initial model performance, with innovative solutions like Sharpening and Gamma Control methods. We compare and analyze the performance of different models, including YOLOv5 and traditional computer vision methods, ultimately identifying YOLOv8 as the most effective choice for our specific use case. The entire training process, from dataset curation to model fine-tuning, is efficiently facilitated through the use of Lambda Cloud's powerful infrastructure, optimizing resources and time. The project's outcome, a well-trained model, is encapsulated for easy access and distribution in the 'run.zip' file. Visionary Plates strives to provide a reliable and accurate license plate detection system, with the potential to significantly impact areas such as traffic monitoring, parking management, and law enforcement. The project signifies our commitment to innovation, pushing the boundaries of object detection technology to create practical solutions that make a difference in the real world.

DishForge

DishForge is an innovative AI-powered application revolutionizing cooking experiences by seamlessly merging AI capabilities with culinary artistry. It harnesses Llama 2's natural language processing and Clarifai's computer vision, resulting in an unparalleled recipe generation experience. Users interact with DishForge through a user-friendly interface, inputting the desired type of meal or beverage, their preferences, dietary restrictions, available ingredients, and cooking appliances. Llama 2 processes these inputs to create coherent and personalized recipes. Simultaneously, Stable Diffusion presents the ingredients visually, ensuring a comprehensive understanding of the recipe components and the dish visuals. DishForge addresses practical challenges in meal planning by going beyond being just a recipe generator. It caters to users seeking kitchen convenience by considering preferences, available ingredients, and time constraints. The app's ability to generate recipes tailored to dietary needs, ingredient availability, and cooking resources enhances its value proposition, making it perfect for various culinary skill levels. What sets DishForge apart is its holistic approach to recipe generation. By combining Llama 2's language understanding and generative and recognition image models, it provides a comprehensive culinary solution. The app's ability to generate recipes in diverse formats, visualize ingredients, and accommodate specific preferences positions it as an innovative tool that promotes creativity and experimentation in the kitchen. In summary, DishForge represents the cutting-edge fusion of AI and culinary expertise. It showcases a deep understanding of Llama 2 and Clarifai's capabilities, resulting in a solution that transforms recipe generation, meal planning, and culinary exploration. With its user-friendly interface and personalized recipes, DishForge sets a new standard for AI-driven kitchen innovation.

CookPal

Welcome to CookPal, the food identification software created with cutting-edge technology like Vertex AI and object detection. CookPal is a cutting-edge food management program created to decrease food waste and improve user convenience. Those uncertain times when you're examining the leftover food in your fridge are over, so say goodbye to them. CookPal saves the day! You can use the phone's camera or manual text entry to identify your food products with CookPal. CookPal's cutting-edge object identification technology will do its magic as soon as you take a picture or enter the ingredients you have on hand. CookPal, however, doesn't end there. It involves more than just recognizing your ingredients. It elevates your culinary experience by giving you access to a huge library of mouthwatering recipes that are specially adapted to use the products you have on hand. There is no need to waste time browsing innumerable recipe websites or cookbooks. CookPal's recipe recommendations are only a few clicks away, saving you time and energy. CookPal invites you to try out new flavors, play around with flavor pairings, and maximize the ingredients in your pantry. It is simple to navigate and locate the ideal recipe for your culinary trip thanks to its user-friendly layout and intuitive design. So whether you're an experienced cook or a kitchen newbie, CookPal is your go-to partner for excellent meals made with products you already own. Join us in our effort to reduce food waste and create a more sustainable future with CookPal. Try CookPal today and begin on a voyage of culinary inventiveness. Your kitchen's best buddy is CookPal.

AI Home Design

AI Home Design is an interior design assistant powered by Stable Diffusion and YOLO to solve pain points felt by homeowners. It differs from other AI interior design apps out there because 1) it addresses pain points in homeowners' entire user journey, 2) functions as a social sharing platform, and 3) is an aide to augment, not replace home decor professionals and designers. FIRSTLY, the flagship "Create With AI" feature guides the user in prompt engineering to convert their design hunches from text to actual image, helping them overcome creative blockages. This also improves communication with interior designers, since words can be subjective, but images are direct. SECONDLY, homeowners may want to reimagine a space even after initial fittings like paneling and paint jobs are already done. They cannot tear down these fittings in real life, but they can use Stable Diffusion's image-to-image functionality to reimagine the space. THIRD, AI Home Design also functions as a social sharing platform where users can draw inspiration and start conversations with one another. FINALLY, homeowners still need to furnish and populate their spaces even after they have decided on their designs. This is where YOLO comes in, helping the user to recognise objects, and creating outbound e-commerce links for them to buy items. AI is thus used here to smoothen homeowner-professional interactions and engender connections. Even after the hackathon, I am continually improving the app by creating new features (see slide deck!), such as tools to facilitate discussions, recommenders, or improved object detection. On the technical front, I aim to infuse more powerful models like CLIP, Segment Anything or YOLOv8. On the business front, I am building in-app services to serve new target groups like real estate agents and elder-friendly/disability-friendly retrofitting specialists. Join me on this journey to make interior design more seamless for users, and to use AI in a coherent, impactful way.