Object detection
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The document discusses object detection in images, highlighting its significance in computer vision and image processing. It details the tools used, including OpenCV, DNN, and SSD frameworks, and describes a project that detects multiple objects within images using these technologies. Applications of the project include face detection, people counting, vehicle detection, and security enhancements.
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Object detection
- 1. OBJECT DETECTION IN IMAGE Presented By: ROUSHAN KUMAR SARWAJEET BHARTI
- 2. CONTENTS INTORDUCTION TOOLS USED DESCRIPTION OF PROJECT EXPERIMENTAL RESULTS APPLICATION
- 3. INTRODUCTION OBJECT DETECTION IS COMPUTER TECHNOLOGY REALATED TO COMPUTER VISION AND IMAGE PROCESSING IT IS USED IN OBJECT DETECTION IN IMAGE OBJECT DETECTION IS DIFFERENT FROM OBJECT RECOGNITION OBJECTION DETECTION NOT ONLY RECOGNIZES OBJECT AND ALSO TELL US THE POSITION WHERE OBJECTS ARE PRESENT IN THE IMAGE. IT USES DNN MODULE AND CAFFE FRAME WORK FOR TRANING IMAGE
- 4. TOOLS USED OPENCV 3.3.0 DNN(DEEP NEURAL NETWORK) MOBILENET ARCHITECTURE SSD(SINGLE SHOT DETECTOR) FRAMEWORK CAFFE (DEEP LEARNING FRAMEWORK) COCO PYHTON LANGUAGE
- 5. DESCRIPTION OF PROJECT UPLOAD REQUIRED IMAGE UPLOAD DNN MODULE AND CAFFE FRAMEWORK USE THE BONDING BOXEX AROUND THE DETECTED OBJECT TAG AND ACCURACY PERCTANGE DISPLAYED ON TOP LEFT IT CAN DETECT SEVERAL OBJECT WHICH IS TRAINED UNDER DNN MODULE SEGMENTATION AND DOWNSAMPLING TECHNIQUES USED IN DNN
- 11. APPLICATION FACE DETECTION PEOPLE COUNTING VEHICLE DETECION ONLINE IMAGES DETECTION SECURITY