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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def from_array(x, frame='unspecified'):
 """ Converts an array of data to an Image based on the values in the array and the data format. """


        if not Image.can_convert(x):
            raise ValueError('Cannot convert array to an Image!')

        dtype = x.dtype
        height = x.shape[0]
        width = x.shape[1]
        channels = 1
        if len(x.shape) == 3:
            channels = x.shape[2]
        if dtype == np.uint8:
            if channels == 1:
                if np.any((x % BINARY_IM_MAX_VAL) > 0):
                    return GrayscaleImage(x, frame)
                return BinaryImage(x, frame)
            elif channels == 3:
                return ColorImage(x, frame)
            else:
                raise ValueError(
                    'No available image conversion for uint8 array with 2 channels')
        elif dtype == np.uint16:
            if channels != 1:
                raise ValueError(
                    'No available image conversion for uint16 array with 2 or 3 channels')
            return GrayscaleImage(x, frame)
        elif dtype == np.float32 or dtype == np.float64:
            if channels == 1:
                return DepthImage(x, frame)
            elif channels == 2:
                return GdImage(x, frame)
            elif channels == 3:
                logging.warning('Converting float array to uint8')
                return ColorImage(x.astype(np.uint8), frame)
            return RgbdImage(x, frame)
        else:
            raise ValueError(
                'Conversion for dtype %s not supported!' %
                (str(dtype)))