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This project utilizes deep learning methodologies to automate the segmentation of a dataset I curated myself, focusing on firearm-specific features within cartridge case images. By employing multi-class semantic segmentation, it aims to enhance firearm identification systems.
Mask R-CNN creates a high-quality segmentation mask in addition to the Faster R-CNN network. In addition to class labels and scores, a segmentation mask is created for the objects detected by this neural network. In this repository, using Anaconda prompt step by step Mask R-CNN setup is shown.
Mask R-CNN creates a high-quality segmentation mask in addition to the Faster R-CNN network. In addition to class labels and scores, a segmentation mask is created for the objects detected by this neural network. In this repository, using Anaconda prompt step by step Mask R-CNN setup is shown.
The project takes an image that contains one hand static gesture and by using Image Processing(Python opencv) and an alogirthm calculates code bit i.e. state of each finger if it is open(1) closed(0) or half open(0.5) and maps it a corresponding word that is defined in a small static dictionary in the program. it uses the text to speech module t…
The project take video that contains one hand moving gesture and by using Image Processing(Python opencv) and an alogirthm calculates code bit i.e. state of each finger if it is open(1) closed(0) or half open(0.5) calculates the direction of movement of the object of interest i.e. hand and maps it a corresponding word that is defined in a small …