Help protect the Great Barrier Reef with TensorFlow on Kaggle Join Challenge


TensorFlow 1 version View source on GitHub

Loads an image into PIL format.


image = tf.keras.preprocessing.image.load_img(image_path)
input_arr = keras.preprocessing.image.img_to_array(image)
input_arr = np.array([input_arr])  # Convert single image to a batch.
predictions = model.predict(input_arr)

path Path to image file.
grayscale DEPRECATED use color_mode="grayscale".
color_mode One of "grayscale", "rgb", "rgba". Default: "rgb". The desired image format.
target_size Either None (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.

A PIL Image instance.

ImportError if PIL is not available.
ValueError if interpolation method is not supported.