| import cv2
|
| from PIL import Image
|
| import numpy as np
|
|
|
|
|
| def add_bounding_boxes(img, pred_cls, boxes, pred_score=None, thresh=0.35, rect_th=2, text_size=0.5, text_th=1,
|
| color_box=(1, 1, 1), return_pil=True):
|
| """
|
| Returns the image with boxes and labels as PIL
|
| :param thresh:
|
| :param img: The image
|
| :param pred_cls: Array of classes (as numbers)
|
| :param pred_score: array of probabilities
|
| :param boxes: Array of boxes
|
| :param rect_th: thickness of the rectangle
|
| :param text_size: Text size
|
| :param text_th: thickness of the text
|
| :param color_box: Box and text color
|
| :param return_pil: Boolean indicate whether to return a pil
|
| :return: Returns the image with boxes and labels as PIL
|
| """
|
|
|
| pred_cls = pred_cls.numpy()
|
|
|
| if pred_score is not None:
|
| pred_score = pred_score.numpy()
|
|
|
| for i in range(len(boxes)):
|
| if pred_score is not None and pred_score[i] < thresh:
|
| continue
|
| cv2.rectangle(img, (int(boxes[i][0]), int(boxes[i][1])),
|
| (int(boxes[i][2]),
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| int(boxes[i][3])),
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| color=color_box, thickness=rect_th)
|
| print_text = f"fish{pred_cls[i]}"
|
| print_text = print_text if pred_score is None else print_text + ":{}".format(str(round(pred_score[i],3)))
|
| cv2.putText(img, print_text, (int(boxes[i][0] + rect_th), int(boxes[i][1])+20),
|
| cv2.FONT_HERSHEY_SIMPLEX, text_size, color_box, thickness=text_th)
|
|
|
|
|
| if return_pil:
|
| return Image.fromarray((img * 255).astype(np.uint8))
|
|
|
| return img
|
|
|
|
|
