too many values to unpack (expected 5)

[0xD4rky]

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• [X] I have searched the Supervision issues and found no similar bug report.

Bug

I was using Supervision for an inference of yolov8 model on a sample video data. When I am trying to run the program using the code below, its showing me this error:

for _, _, confidence, class_id, _
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: too many values to unpack (expected 5)

I have went through the updated code in the Detections/core.py but haven't found out exactly why this error is coming up.

I have also referred to downgrading the supervision version to 0.3.0 but that has created more clashes as python versions and pytorch versions also clash.

Environment

• supervision==0.23.0
• opencv-python==4.10.0.84
• ultralytics==8.3.1
• python==3.12.0

Minimal Reproducible Example

import numpy as np
from ultralytics import YOLO

video_path = r'det/data/football.mp4'

model = YOLO("yolov8s.pt")
video_info = sv.VideoInfo.from_video_path(video_path)

def process_frame(frame: np.ndarray,_) -> np.ndarray:

    results = model(frame,imgsz = 1280)[0]
    detections = sv.Detections.from_ultralytics(results)
    box_annotator = sv.BoundingBoxAnnotator()

    labels = [
    f"{model.names[class_id]} {confidence:0.2f}"
    for _, _, confidence, class_id, _
    in detections
    ]
    frame = box_annotator.annotate(scene=frame, detections=detections, labels=labels)

    return frame

sv.process_video(source_path=video_path, target_path=f"result.mp4", callback=process_frame)

Additional

No response

Are you willing to submit a PR?

• [X] Yes I'd like to help by submitting a PR!

[LinasKo]

Hi @0xD4rky 👋

This happens because the detections __iter__ iterators used to produce less values in the past. In recent supervision versions you will have 6 values:

labels = [
    f"{model.names[class_id]} {confidence:0.2f}"
    for xyxy, mask, confidence, class_id, tracker_id, data_slice
    in detections
    ]

[LinasKo]

Closing as I'm certain it's the solution 😉

[0xD4rky]

Thanks a lot @LinasKo for clearing out, was stuck in this problem for some time!

[LinasKo]

Glad to help!