YOLOv7

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YOLO v7

The YOLOv7 algorithm is a big advancement in the field of computer vision and machine learning. It is more accurate and faster than any other object detection models or YOLO versions. It is also much cheaper to train on small datasets without any pre-trained weights. Hence, it's expected to become the industry standard for object detection in the near future.

The official paper named “YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors” was released in July 2022 by Chien-Yao Wang, Alexey Bochkovskiy, and Hong-Yuan Mark Liao. The research paper has become immensely popular in a matter of days. The source code was released as open source under the GPL-3.0 license, a free copyleft license. You can find the code in the official YOLOv7 GitHub repository. The repository was awarded over 4.3k stars in the first month after release.

What's new in YOLOv7?

Serveral architectural reforms imporved speed and accuraracy in YOLOv7. Compared to the previously most accurate YOLOv6 model (56.8% AP), the YOLOv7 real-time model achieves a 13.7% higher AP (43.1% AP) on the COCO dataset.

Architectural Reforms
- Model Scaling for Concatenation based Models
- E-ELAN (Extended Efficient Layer Aggregation Network)
Trainable BoF
- Planned re-parameterized convolution
- Coarse for auxiliary and Fine for lead loss

The paper discusses the YOLOv7 architecture in great detail and provides intuition into how the model works.

General
Relese date	July, 2022
Repository	https://github.com/WongKinYiu/yolov7
Type	Real time object detection

Libraries

Discover YOLOv7

Research Paper YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors, official research paper
Hugging Face Spaces Test YOLOv7 in the browser with Hugging Face Spaces
GitHub Repository View the GitHub repository for YOLOv7

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YOLO YOLOv7 AI technology Hackathon projects

Discover innovative solutions crafted with YOLO YOLOv7 AI technology, developed by our community members during our engaging hackathons.

Havelo AI

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RIFFAI

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NetConnect

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MyVision

My Vision is an AI-powered app designed to assist visually impaired individuals by making their surroundings more accessible. With over 285 million people worldwide affected by visual impairment, My Vision offers a simple solution: users take a picture, ask a question, and receive an instant spoken description of their environment. This real-time feedback helps users navigate and interact with the world around them. Beyond supporting the visually impaired, My Vision includes features like Optical Character Recognition (OCR) for real-time translation, making it useful for everyone. What makes My Vision unique is its context-aware results, support for various environments, and Episodic Memory, which remembers repeated objects or settings to enhance user experience and independence.

Diet Vision

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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.