czifile.py 文件源码

def data(self, raw=False, bgr2rgb=True, resize=True, order=1):
        """Read image data from file and return as numpy array."""
        self._fh.seek(self.data_offset)
        if raw:
            return self._fh.read(self.data_size)
        elif self.compression and self.compression < RAW_COMPRESSION_VALUE:
            if self.compression not in DECOMPRESS:
                raise ValueError("compression unknown or not supported")
            # TODO: iotest this
            data = self._fh.read(self.data_size)
            data = DECOMPRESS[self.compression](data)
            if self.compression == 2:
                # LZW
                data = numpy.fromstring(data, self.dtype)
        else:
            dtype = numpy.dtype(self.dtype)
            data = self._fh.read_array(dtype, self.data_size // dtype.itemsize)

        data = data.reshape(self.stored_shape)
        if self.stored_shape == self.shape or not resize:
            if bgr2rgb and self.stored_shape[-1] in (3, 4):
                tmp = data[..., 0].copy()
                data[..., 0] = data[..., 2]
                data[..., 2] = tmp
            return data

        # sub / supersampling
        factors = [j / i for i, j in zip(self.stored_shape, self.shape)]
        factors = [(1.0 if abs(1.0-f) < 0.0001 else f) for f in factors]
        shape = list(self.stored_shape)
        # remove leading dimensions with factor 1.0 for speed
        for factor in factors:
            if factor != 1.0:
                break
            shape = shape[1:]
            factors = factors[1:]
        data.shape = shape
        # resize RGB components separately for speed
        if shape[-1] in (3, 4) and factors[-1] == 1.0:
            factors = factors[:-1]
            old = data
            data = numpy.empty(self.shape, self.dtype[-2:])
            for i in range(shape[-1]):
                j = {0: 2, 1: 1, 2: 0, 3: 3}[i] if bgr2rgb else i
                data[..., i] = zoom(old[..., j], zoom=factors, order=order)
        else:
            data = zoom(data, zoom=factors, order=order)

        data.shape = self.shape
        return data