Object detection with IP camera on Raspberry Pi

XMOUSEX Thank you for your posting! Just I have read your job posting, and I’m very interested in your project. I am a computer vision expert with full experience using machine learning such as tensorflow, caffe, darknet, keras, pytorch and so on. I have developed lots of object detection/recognition/tracking/counting projects such as symbol and logo detection, ball tracking, people and vehicle counting, image segmentation, player speed detection and so on. Also, I am very famillar with Rasberry Pi, Python and OpenCV. If you response my bid , I will send you my image processing Demos and I can finish your task and deliver you perfectly, Also, you can know my ability enough. I sincerely hope this project would be first step in long term relationship with you. Please give me your detail. Looking forward to hear from you soon. Best Regard!

XMOUSEX Hi there, I have experiences in object detection and recognition on Raspberry Pi and Jetson Nano. I now have Raspberry Pi zero W, 3B+, 4B and EzyViz IP camera, so I can start work right now. Bests, Sai.

XMOUSEX Hello, I have done Object detection worh Raspberry Pi several times. Most of the people think it can be done using YOLO but that is incorrect as YOLO takes so much processing power of Raspberry Pi and or will stuck. I have done it differently with less proceeding required. Contact me so that I can show you the images of my project and we can start. Thank you

XMOUSEX hi dear, I just read out your description and i am interested in your project. i am expert in object detection, and also done with it. if you need quality work than feel free to contact me. Thanks.

Familiar with OpenCV and Computing Vision application with Raspberry Pi. This project work proposes a camera-based to detect product packaging from hand-held objects in their daily lives. The project work is framed into three stages. First, Image capturing – Using a mini camera , the user need to read get captured as an image and have to send to the image processing Platform. Secondly, Text recognition – Using text recognition algorithm, the text will get filtered from the image. Finally, all text output - A filtered text will be passed into this system to get an audio output. The entire application is based on Raspberry Pi.