def get_bounding_box(camera_dict):
import numpy as np
# Initialize min and max values
min_point = np.array([float('inf')] * 3)
max_point = np.array([-float('inf')] * 3)
for camera_id, transform in camera_dict.items():
# Extract translation from the transformation matrix
translation = transform[:3, 3]
# Update min and max
min_point = np.minimum(min_point, translation)
max_point = np.maximum(max_point, translation)
return tuple(min_point), tuple(max_point)
Schlüsselwörter
- Python
- Generieren
- Funktion
- Maschinen Lernen
- Umrandungsrahmen
- Transformationsmatrix
- Datenwissenschaft
- Numpy
- Bildverarbeitung
- Computer Vision
Quelle
