tf.io.decode_image
Function for decode_bmp, decode_gif, decode_jpeg, and decode_png.
tf.io.decode_image(
contents, channels=None, dtype=tf.dtypes.uint8, name=None,
expand_animations=True
)
Detects whether an image is a BMP, GIF, JPEG, or PNG, and performs the appropriate operation to convert the input bytes string into a Tensor of type dtype.
Note: decode_gif returns a 4-D array [num_frames, height, width, 3], as opposed to decode_bmp, decode_jpeg and decode_png, which return 3-D arrays [height, width, num_channels]. Make sure to take this into account when constructing your graph if you are intermixing GIF files with BMP, JPEG, and/or PNG files. Alternately, set the expand_animations argument of this function to False, in which case the op will return 3-dimensional tensors and will truncate animated GIF files to the first frame.
Note: If the first frame of an animated GIF does not occupy the entire canvas (maximum frame width x maximum frame height), then it fills the unoccupied areas (in the first frame) with zeros (black). For frames after the first frame that does not occupy the entire canvas, it uses the previous frame to fill the unoccupied areas.
| Args |
|---|
contents | 0-D string. The encoded image bytes. |
channels | An optional int. Defaults to 0. Number of color channels for the decoded image. |
dtype | The desired DType of the returned Tensor. |
name | A name for the operation (optional) |
expand_animations | Controls the shape of the returned op's output. If True, the returned op will produce a 3-D tensor for PNG, JPEG, and BMP files; and a 4-D tensor for all GIFs, whether animated or not. If, False, the returned op will produce a 3-D tensor for all file types and will truncate animated GIFs to the first frame. |
| Returns |
|---|
Tensor with type dtype and a 3- or 4-dimensional shape, depending on the file type and the value of the expand_animations parameter. |
| Raises |
|---|
ValueError | On incorrect number of channels. |