util.py 文件源码

def read_img(in_filename, grayscale=False, extra_info={}):
    """Returns the image saved at in_filename as a numpy array.

    If grayscale is True, converts from 3D RGB image to 2D grayscale image.
    """
    if is_pypy:
        ans = Image.open(in_filename)
        height = ans.height
        width = ans.width
        channels = len(ans.getbands())
        if ans.mode == 'I':
            numpy_mode = 'uint32'
            maxval = 65535.0
        elif ans.mode in ['L', 'RGB', 'RGBA']:
            numpy_mode = 'uint8'
            maxval = 255.0
        else:
            raise ValueError('unknown mode')
        ans = numpy.fromstring(ans.tobytes(), numpy_mode).reshape((height, width, channels))
        ans = ans/maxval
        if grayscale and (len(ans.shape) == 3 and ans.shape[2] == 3):
            ans = ans[:,:,0]*0.2125 + ans[:,:,1]*0.7154 + ans[:,:,2]*0.0721
        if len(ans.shape) == 3 and ans.shape[2] == 1:
            ans = ans[:,:,0]
        return ans
    else:
        ans = skimage.io.imread(in_filename)
        if ans.dtype == numpy.int32:    # Work around scikit-image bug #1680
            ans = numpy.asarray(ans, numpy.uint16)
        ans = skimage.img_as_float(ans)
        if grayscale:
            ans = skimage.color.rgb2gray(ans)
#        print('here', use_4channel, len(ans.shape) == 3, ans.shape[2] == 3)
        if use_4channel and len(ans.shape) == 3 and ans.shape[2] == 3:
            ans = numpy.dstack((ans,) + (numpy.ones((ans.shape[0], ans.shape[1], 1)),))
            extra_info['originally_3channel'] = True
    return ans