I'm using the Ultralytics YOLOv8 implementation to perform object detection on an image. However, when I try to retrieve the classification probabilities using the probs attribute from the results object, it returns None. Here's my code:
from ultralytics import YOLO
# Load a model
model = YOLO('yolov8n.pt') # pretrained YOLOv8n model
# Run batched inference on a list of images
results = model('00000.png') # return a list of Results objects
# Process results list
for result in results:
boxes = result.boxes # Boxes object for bbox outputs
masks = result.masks # Masks object for segmentation masks outputs
keypoints = result.keypoints # Keypoints object for pose outputs
probs = result.probs # Probs object for classification outputs
print(probs)
When I run the above code, the output for print(probs) is None. The remaining output is
image 1/1 00000.png: 640x640 1 person, 1 zebra, 7.8ms
Speed: 2.6ms preprocess, 7.8ms inference, 1.3ms postprocess per image at shape (1, 3, 640, 640)
Why is the probs attribute returning None, and how can I retrieve the classification probabilities for each detected object? Is there a specific design reason behind this behavior in the Ultralytics YOLOv8 implementation?
I think you should be able to get the confidences with results[0].boxes.conf.
The probs property seems not to be working in Yolov8