utils.py

# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
#
# 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
#
#     http://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.

# CREDIT
# Copied from https://github.com/tensorflow/examples/blob/master/lite/examples/object_detection/raspberry_pi/utils.py

"""Utility functions to display the pose detection results."""

import cv2
import numpy as np
from tflite_support.task import processor

_MARGIN = 10  # pixels
_ROW_SIZE = 10  # pixels
_FONT_SIZE = 1
_FONT_THICKNESS = 1
_TEXT_COLOR = (0, 0, 255)  # red


def visualize(
    image: np.ndarray,
    detection_result: processor.DetectionResult,
) -> np.ndarray:
  """Draws bounding boxes on the input image and return it.

  Args:
    image: The input RGB image.
    detection_result: The list of all "Detection" entities to be visualize.

  Returns:
    Image with bounding boxes.
  """
  for detection in detection_result.detections:
    # Draw bounding_box
    bbox = detection.bounding_box
    start_point = bbox.origin_x, bbox.origin_y
    end_point = bbox.origin_x + bbox.width, bbox.origin_y + bbox.height
    cv2.rectangle(image, start_point, end_point, _TEXT_COLOR, 3)

    # Draw label and score
    category = detection.classes[0]
    class_name = category.class_name
    probability = round(category.score, 2)
    result_text = class_name + ' (' + str(probability) + ')'
    text_location = (_MARGIN + bbox.origin_x,
                     _MARGIN + _ROW_SIZE + bbox.origin_y)
    cv2.putText(image, result_text, text_location, cv2.FONT_HERSHEY_PLAIN,
                _FONT_SIZE, _TEXT_COLOR, _FONT_THICKNESS)

  return image