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Is your feature request related to a problem? Please describe.
Communication Barrier: One of the primary challenges faced by the Deaf community is the communication barrier, especially when interacting with hearing individuals or accessing content that relies heavily on audio. A web application tailored to the Deaf community can provide alternative communication methods, such as sign language interpretation, text-based chat, or visual representations of information, enabling more effective communication.
Describe the solution you'd like
Many existing web applications are not fully accessible to Deaf individuals. By creating a web application designed with features that cater to their needs, such as providing sign language interpretation, closed captioning, or visual representations of audio content, I will make digital content more accessible to Deaf users.
Describe alternatives you've considered
🔴 Approach: Finding the movements of hands through pre-trained models like media pipe and VITpose then taking the model with the most precise output and then assigning keywords to every movement of actions.
Custom Dataset: I will use my own specific application, I will collect my own dataset by recording hand gestures using a webcam as I have a specific set of gestures relevant to my use case.
Algorithmic steps involved in developing the model through hand gesture recognition:
Data Collection: I will Gather a dataset of hand gesture images or videos along with their corresponding labels.
Data Preprocessing: I will Preprocess the dataset to ensure uniformity and compatibility, including tasks like resizing images, normalization, and augmentation to increase dataset variability.
Feature Extraction: Extract relevant features from the preprocessed images or videos. This may involve Convolutional Neural Networks (CNNs) technique for automatic feature learning.
Model Selection: This part will be handled by Conventional Neural Networks (CNN).
Model Training: Training the selected model using the Custom dataset.
Model Evaluation: Evaluate the trained model's performance on a separate validation or test dataset to assess its accuracy and precision.
Deployment: Integrating the model into the website, or embedded system for real-time recognition.
Is your feature request related to a problem? Please describe.
Communication Barrier: One of the primary challenges faced by the Deaf community is the communication barrier, especially when interacting with hearing individuals or accessing content that relies heavily on audio. A web application tailored to the Deaf community can provide alternative communication methods, such as sign language interpretation, text-based chat, or visual representations of information, enabling more effective communication.
Describe the solution you'd like
Many existing web applications are not fully accessible to Deaf individuals. By creating a web application designed with features that cater to their needs, such as providing sign language interpretation, closed captioning, or visual representations of audio content, I will make digital content more accessible to Deaf users.
Describe alternatives you've considered
🔴 Approach: Finding the movements of hands through pre-trained models like media pipe and VITpose then taking the model with the most precise output and then assigning keywords to every movement of actions.
Custom Dataset: I will use my own specific application, I will collect my own dataset by recording hand gestures using a webcam as I have a specific set of gestures relevant to my use case.
Algorithmic steps involved in developing the model through hand gesture recognition:
Additional context
Tech use: Python, Tensorflow, Keras, OpenCV