Closed polinamalova0 closed 4 months ago
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Hello! π It's great to see your enthusiasm for working with YOLOv5. The error you're encountering often points to an issue with the input dimensions or type at some point before it's passed into the model. Your preprocessing steps seem correct, converting the grayscale image to RGB and adjusting its shape to match the expected input format of (n, 3, w, h).
Given the error trace, it appears the issue might not be with your code directly but rather an unexpected interaction with OpenCV or the way the processed image array is being interpreted just before resizing operations in letterbox
.
One potential troubleshooting step is to ensure all images passed into the model are indeed of non-zero size after any preprocessing. It can sometimes help to explicitly check or print the shape of images at various points to confirm they're not being inadvertently altered to a zero-dimension array, which seems to be what OpenCV is complaining about (!dsize.empty()
).
Considering the error happens during a cv2.resize
call inside the letterbox
function and your transformed array shape and dtype look correct, you might also want to inspect if there's an edge case where the preprocessing results in dimensions that OpenCV cannot handle (though this seems less likely given the shape you've provided).
Without altering much of your existing workflow and adding an explicit check, your code already appears well-structured for the task. So, I recommend inserting trouble-shooting print statements or debugging steps around the preprocessing steps, especially right before the model invocation, to ensure everything is as expected.
Let's keep debugging collaborative and insightful! If the issue persists or you find more specific patterns leading to the error, feel free to share more details. The YOLO community and the Ultralytics team are here to help. π
π Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.
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Thanks YOLO team for making such a great tool! I have question regarding the prediction of the already trained model. what do I have as an input: an np.array with the shape (428, 428). each value of the array varies from 1.3 to 1.4 I have faced the problem that when I am trying to predict, the model says that there must be specific data format given in the form of (n, 3, w, h). Therefore, I transposed the array and provided it in the correct form to the model.
however, in the end i get this error, and i have no clue how to proceed, since all the dimentions are correct and when i print out cvImage_array i do get the values in the end.
I would be very grateful for the help. Thank you in advance!
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