vis-example.py

# Copyright 2022 The KerasCV Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
resizing_demo.py shows how to use the resizing preprocessing layer for
object detection.
"""
import demo_utils

from keras_cv import layers

from luketils import visualization



class_ids = [
    "Aeroplane",
    "Bicycle",
    "Bird",
    "Boat",
    "Bottle",
    "Bus",
    "Car",
    "Cat",
    "Chair",
    "Cow",
    "Dining Table",
    "Dog",
    "Horse",
    "Motorbike",
    "Person",
    "Potted Plant",
    "Sheep",
    "Sofa",
    "Train",
    "Tvmonitor",
    "Total",
]
class_mapping = dict(zip(range(len(class_ids)), class_ids))


def visualize_dataset(dataset, bounding_box_format):
    example = next(iter(dataset))
    images, boxes = example["images"], example["bounding_boxes"]
    visualization.plot_bounding_box_gallery(
        images,
        value_range=(0, 255),
        bounding_box_format=bounding_box_format,
        y_true=boxes,
        scale=4,
        rows=3,
        cols=3,
        show=True,
        thickness=4,
        font_scale=1,
        class_mapping=class_mapping,
    )


def main():
    dataset = demo_utils.load_voc_dataset(bounding_box_format="xywh")
    visualize_dataset(dataset, bounding_box_format="xywh")
    resizing = layers.Resizing(
        height=300, width=400, pad_to_aspect_ratio=True, bounding_box_format="xywh"
    )
    dataset = dataset.map(resizing).map(layers.Resizing(bounding_box_format="xywh"))
    visualize_dataset(dataset, bounding_box_format="xywh")


if __name__ == "__main__":
    main()