Comments (2)
Yes, Thanks for your quick response!
I saw normal CVDataset processing class, which using 255 as the portrait label.
which label should be used for training?
Regards!
class CVDataset(torch.utils.data.Dataset):
....
def getitem(self, idx):
image_name = self.imList[idx]
label_name = self.labelList[idx]
image = cv2.imread(image_name)
label = cv2.imread(label_name, 0)
label_bool = 255 * ((label > 200).astype(np.uint8))
class ToTensor(object):
...
image_tensor = torch.from_numpy(image).div(255)
label_tensor = torch.LongTensor(np.array(label, dtype=np.int)).div(255) #torch.from_numpy(label)
from ext_portrait_segmentation.
Hello @Minotaur-CN Thanks for your asking
0 is a background 1 is a foreground.
Most of the segmentation dataset denotes 255 for not labeled pixel (It means hard to classify into any class)or ignoring in training.
Therefore, I just follow this custom by my habit.
However, that does not need in here, cuz the dataset is 0 or 255 and 255 convert to 1
from ext_portrait_segmentation.
Related Issues (20)
- the size of input_image HOT 1
- Accuracy issue, implementation difference compared to paper. HOT 4
- visualizing results HOT 4
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from ext_portrait_segmentation.