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Hello dear author, I was reading through the volume of your article and noticed that you are cropping the image to 512*512 size, and in conjunction with your dataset, I noticed that the targets in your dataset are smaller, so it may be less likely that the foreground will be truncated, whereas my foreground is larger and therefore truncated (e.g., the head of a camel is in 1.jpg, and it's body is in 2.jpg. But 1.jpg and 2.jpg belong to the same original image), how to deal with this situation? (My native language is not English, and I have great respect for you, if you feel any offense and confusion, it's my translation software's problem, haha),I have a second question for you if it's convenient for you, if the size of the target in the image that I want to count is slightly larger than the size of the target in the image in your dataset, does this method still work?
The text was updated successfully, but these errors were encountered:
Hello dear author, I was reading through the volume of your article and noticed that you are cropping the image to 512*512 size, and in conjunction with your dataset, I noticed that the targets in your dataset are smaller, so it may be less likely that the foreground will be truncated, whereas my foreground is larger and therefore truncated (e.g., the head of a camel is in 1.jpg, and it's body is in 2.jpg. But 1.jpg and 2.jpg belong to the same original image), how to deal with this situation? (My native language is not English, and I have great respect for you, if you feel any offense and confusion, it's my translation software's problem, haha),I have a second question for you if it's convenient for you, if the size of the target in the image that I want to count is slightly larger than the size of the target in the image in your dataset, does this method still work?
The text was updated successfully, but these errors were encountered: