Metadata-Version: 1.1
Name: gesture-classifying-model
Version: 0.1.9
Summary: Classifying model for Sign Language Recognition System
Home-page: https://github.com/kacper1095/gesture_classifying_model
Author: Kacper Kania
Author-email: kacper1095@gmail.com
License: MIT
Description-Content-Type: UNKNOWN
Description: gesture-classifying-model
        ----------------
        
        To use, first create GestureClassifier object::
        
            >>> predictor = GestureClassifier()
        
        This may take a while as model is being downloaded and loaded (approx. 86 MB of weights).
        
        After creation, you can use the predictor, by passing tensor of frames to transform function.
        Numpy array of passed images should have same number of channels, same width and height.
        GestureClassifier receives tensor in following shape (None, 64, 64, 3). By that I mean::
        
            >>> input_tensor.shape
            >>> (any_num, 64, 64, 3),
        
        where 'any_num' is any number of frames passed. Images should be in range of values 0-255.
        
        You can finally predict probabilities of frame of cropped hands (letters are indexed in order shown below)::
        
            >>> predictor.transform(input_tensor_of images)
        
        Letters order::
        
             'abcdefghiklmnopqrstuvwxy' # alphabetical order for indices from 1 to 24 without
Keywords: sign language classification
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
