Change the number of channels and preprocess the image.

[SnifferCaptain]

Search before asking

• [X] I have searched the Ultralytics YOLO issues and discussions and found no similar questions.

Question

Thanks for your fantastic model before I begin. I want to change the channels from 3 to 4 to meet my personal requirements, but here are the challenge: The image I read is originally three channels (BGR), but I want to randomly select a label based on the situation and convert it into a mask for the fourth channel of this image. such code may look like: ////// alpha_channel = np.zeros(img.shape[:2], dtype=np.uint8)#3channels cv2.rectangle(alpha_channel, p1, p2, 255, -1) img_rgba = np.dstack((img, alpha_channel))#4channels ////// but I don't know where should I put this transform. Help me plz...

yolov8-det while training.

Additional

No response

[glenn-jocher]

@SnifferCaptain thank you for your question and for using our model! To add a fourth channel to your images during training, you can modify the dataset loading function to include your transformation. This can be done in the load_image function within the dataset class. If you need further assistance, please refer to the Ultralytics documentation.