Is there anybody who can provide me a road map on how to start the project, from where I can get the data set, and how to convert hand gestures to text? or is there any SDK or API, it will be great if you can provide me git link
Research on hand gesture recognition: Before starting any project, it's important to research the topic you are interested in. Learn about the types of hand gestures commonly used by deaf and dumb people, and the techniques used for hand gesture recognition. You can start with some introductory material on machine learning-based computer vision, image processing, and object recognition, and then dive into more specific literature about hand gesture recognition techniques.
Collect dataset: To train your hand gesture recognition model, you'll need a dataset of labeled images of hands making different gestures. There are a few options for this. You can collect images yourself, but this can be time-consuming and require a lot of effort. Alternatively, you can look for existing datasets, such as the American Sign Language Hand Gesture dataset, which has over 8000 images of hand gestures, or the ChaLearn Gesture Recognition dataset, which has over 20,000 videos of hand gestures.
Preprocess the data: Once you have the dataset, you'll need to preprocess the images to prepare them for training. This can include resizing the images to a uniform size, converting them to grayscale, and normalizing the pixel values.
Train the model: With the preprocessed dataset, you can train a machine learning model to recognize hand gestures. There are several machine learning algorithms that can be used for this, including convolutional neural networks (CNNs) and support vector machines (SVMs).
Convert hand gestures to text: Once the model has been trained, you can use it to recognize hand gestures in real-time and convert them to text. One approach is to use a sign language recognition API, such as Sign Language Interpreter API by Microsoft Azure or Sign Language Detection API by IBM Watson. Alternatively, you can write your own code to convert the output of your model into text using techniques such as sequence labeling.
Build a user interface: Finally, you can build a user interface for your app that captures the hand gestures in real-time using the device's camera and displays the converted text. You can use Flutter's camera plugin to access the device's camera and display the captured video stream in your app.
As for resources and links, here are some to get you started:
American Sign Language Hand Gesture dataset: https://www.kaggle.com/ahmedkhanak1995/asl-gesture-images-dataset
ChaLearn Gesture Recognition dataset: http://chalearnlap.cvc.uab.es/dataset/24/description/
TensorFlow Lite: https://www.tensorflow.org/lite
Sign Language Interpreter API by Microsoft Azure: https://azure.microsoft.com/en-us/services/cognitive-services/sign-language-interpreter/
Sign Language Detection API by IBM Watson: https://www.ibm.com/cloud/watson-studio/autoai/sign-language-detector
Flutter camera plugin: https://pub.dev/packages/camera