SSD is a popular algorithm in object detection. It’s generally faster than Faster RCNN. In this project we have train SSD model on custom dataset , by doing this model is able to classify various type of 'Alphabets'. This way an effective Sign language Translator can be made . This type of project is not only bound to SSD-mobilenet , various Object detection algorithm can be used.
I have created a custom flag called INFO that can be added to any detect.py or detect_video.py commands in order to print detailed information about each detection made by the object detector. To print the detailed information to your command prompt just add the flag --info to any of your commands. The information on each detection includes the class, confidence in the detection and the bounding box coordinates of the detection in xmin, ymin, xmax, ymax format.
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