testing on high-resolution image about automatic-identification-and-counting-of-blood-cells HOT 5 CLOSED

@GloriaZLQ
Hi. Model is used on the high-resolution image in Prediction_on_HRI.py and partially visible cells at the edge are ignored by the model as in the training set edge cells are not annotated as ground truth cells.

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The Images\ folder was missing high-resolution images previously. I have added them to the folder.

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I watched your result in README "Combined Output",found that one rbc cell was counted twice and some rbc cells were ignored at the edge of the 3x3 grid. I think this problem affects the counting accuracy and do you have any solution?

from automatic-identification-and-counting-of-blood-cells.

That RBC cell is divided by grid line and two predictions are coming from two grid cells. Double counting can be prevented using proposed KNN and IOU based verification which is implemented only for platelets only. Those high-resolution images (HRI) are used only to verify the generalization of the learning and not used any similar image during training and HRI dataset only contains images, not any annotations. So, if you want to show any counting performance in those images, you have to manually annotate the cells first.
Edge cells are ignored because in the training dataset edge cells are not considered as full cell and not annotated as ground truth cell.

from automatic-identification-and-counting-of-blood-cells.

ok,thank you

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