Loads an image into PIL format.
Usage
image_load(
path,
color_mode = "rgb",
target_size = NULL,
interpolation = "nearest",
keep_aspect_ratio = FALSE
)Arguments
- path
Path to image file.
- color_mode
One of
"grayscale","rgb","rgba". Default:"rgb". The desired image format.- target_size
Either
NULL(default to original size) or tuple of ints(img_height, img_width).- interpolation
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.- keep_aspect_ratio
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.
Example
image_path <- get_file(origin = "https://www.r-project.org/logo/Rlogo.png")
(image <- image_load(image_path))input_arr <- image_to_array(image)
str(input_arr)input_arr %<>% array_reshape(dim = c(1, dim(input_arr))) # Convert single image to a batch.model |> predict(input_arr)See also
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_gaussian_blur() op_image_hsv_to_rgb() op_image_map_coordinates() op_image_pad() op_image_perspective_transform() 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()