Visually impaired individuals face numerous challenges in their daily lives, including the ability to identify and navigate through their surroundings independently. Object detection techniques based on computer vision have shown results in helping the visually impaired by detecting and classifying objects in real-time. In this paper, we used a realtime object detection and audio feedback system that provides audio feedback to the visually impaired for identifying and navigating in their surroundings. The proposed system uses the YOLO_v3 algorithm with the MS COCO dataset to detect and classify objects in real-time and provide corresponding audio feedback. We used gTTS (Google Text to Speech) API for generating the audio feedback. The audio feedback is generated using an audio processing techniques and deep learning algorithms. We evaluated on a dataset, and achieved an average detection accuracy of 90%. The proposed system provides a practical and effective solution for enhancing accessibility and independence for visually impaired individuals, and demonstrates the potential of using advanced deep learning algorithms and datasets for real-time object detection and audio feedback systems.