从Yolo v2切换到Yolo v3时OpenCV报Unknown layer type: shortcut错误求助

Hey there, that Unknown layer type: shortcut error is super common when moving from YOLOv2 to YOLOv3 with OpenCV's DNN module—let's break down the fixes step by step:

1. Check Your OpenCV Version #

YOLOv3 introduced the shortcut layer (used for residual connections), and OpenCV only added support for this layer in version 3.4.2 and above. Older versions simply don't recognize it.

• To check your version in Python:

  import cv2
  print(cv2.__version__)
  

• In a terminal (for system-wide OpenCV):

  pkg-config --modversion opencv4  # or opencv if using older naming
  

If you're on an older version, upgrade to the latest stable release. For Python, use:

pip install --upgrade opencv-python opencv-contrib-python

2. Verify Your YOLOv3 Config File #

Double-check that your YOLOv3 .cfg file is correctly formatted. A valid shortcut layer should look like this:

[shortcut]
from=-1
activation=linear

Make sure there are no typos (like misspelling "shortcut" as "shortcutt" or missing parameters). Compare your file against the official YOLOv3 cfg to rule out formatting errors.

3. Ensure OpenCV Has Darknet/YOLO Support #

If you compiled OpenCV from source, you might have missed enabling the necessary flags. When compiling, make sure to set:

• OPENCV_ENABLE_NONFREE=ON
• OPENCV_DNN_ENABLE_TORCH_IMPORTS=ON (or relevant flags for Darknet support)
  If you're using pre-built packages, the latest opencv-python/opencv-contrib-python from PyPI should already include this support.

4. Alternative: Use Darknet Natively #

If upgrading OpenCV isn't feasible right now, you can run YOLOv3 directly using the official Darknet code instead of OpenCV's DNN module. This avoids any layer compatibility issues—just use the Darknet command line tools or the provided Python bindings.

内容的提问来源于stack exchange，提问作者Austin