Loads an image into PIL format.
image_load(
path,
color_mode = "rgb",
target_size = NULL,
interpolation = "nearest",
keep_aspect_ratio = FALSE
)A PIL Image instance.
Path to image file.
One of "grayscale", "rgb", "rgba". Default: "rgb".
The desired image format.
Either NULL (default to original size) or tuple of ints
(img_height, img_width).
Interpolation method used to resample the image if the
target size is different from that of the loaded image. Supported
methods are "nearest", "bilinear", and "bicubic".
If PIL version 1.1.3 or newer is installed, "lanczos"
is also supported. If PIL version 3.4.0 or newer is installed,
"box" and "hamming" are also
supported. By default, "nearest" is used.
Boolean, whether to resize images to a target size without aspect ratio distortion. The image is cropped in the center with target aspect ratio before resizing.
image_path <- get_file(origin = "https://www.r-project.org/logo/Rlogo.png")
(image <- image_load(image_path))
## <PIL.Image.Image image mode=RGB size=724x561 at 0x0>input_arr <- image_to_array(image)
str(input_arr)
## num [1:561, 1:724, 1:3] 0 0 0 0 0 0 0 0 0 0 ...input_arr %<>% array_reshape(dim = c(1, dim(input_arr))) # Convert single image to a batch.
model |> predict(input_arr)
Other image utils:
image_array_save()
image_from_array()
image_smart_resize()
image_to_array()
op_image_affine_transform()
op_image_crop()
op_image_extract_patches()
op_image_hsv_to_rgb()
op_image_map_coordinates()
op_image_pad()
op_image_resize()
op_image_rgb_to_grayscale()
op_image_rgb_to_hsv()
Other utils:
audio_dataset_from_directory()
clear_session()
config_disable_interactive_logging()
config_disable_traceback_filtering()
config_enable_interactive_logging()
config_enable_traceback_filtering()
config_is_interactive_logging_enabled()
config_is_traceback_filtering_enabled()
get_file()
get_source_inputs()
image_array_save()
image_dataset_from_directory()
image_from_array()
image_smart_resize()
image_to_array()
layer_feature_space()
normalize()
pad_sequences()
set_random_seed()
split_dataset()
text_dataset_from_directory()
timeseries_dataset_from_array()
to_categorical()
zip_lists()