Corrosion poses a significant threat to infrastructure integrity, necessitating accurate detection and monitoring for preventive maintenance and safety assurance. YOLOv8-based model tailored specifically for precise corrosion segmentation in industrial imagery. an innovative method for video processing by combining YOLOv8, an advanced version of the YOLO object detection model, with the visualization capabilities of the Weights & Biases (W&B) platform. YOLOv8 offers superior real-time object detection performance, thanks to its single-pass detection technique and improved accuracy in localization and classification. Integration with W&B provides interactive dashboards for real-time monitoring of metrics and model behavior, enhancing understanding and optimization. Additionally, the use of cloud-based virtual machines, particularly W&B Cloud, offers a cost-effective deployment and monitoring solution compared to traditional options like Azure. Regardless, This combination is a robust example of a complete resolution for video processing tasks that leverage high-technology primitive techniques to accomplish extra advanced object discovery, one thing, of the actual to apply in not infrequently domain names from surveillance to autonomous cars, and lots extra. Therefore, this methodology towards corrosion identification systems has the potential to increase dependability and efficiency to assist with timely maintenance and longevity of crucial infrastructure assets.