About ROC curve in segmentation model

Solution for About ROC curve in segmentation model
is Given Below:

I know how to draw ROC curves about classification model for a one class. And I know how to plot ROC curves about classification model for many classes. But is there a way to plot ROC curves for a segmentation model? If so, tell me how

When computing a ROC curve for classification, you treat each image (and its prediction) as a single “data point”.
In image segmentation, you need to treat each pixel as a data point.

for example:

from sklearn import metrics

y_true = []
y_pred = []
for img, true_seg in test_set:
  pred = model(img)  # get prediction for each pixel in the image
  y_true.append(true_seg.to_numpy().flatten())  # flatten all targets
  y_pred.append(pred.to_numpy().flatten())  # flatten all predictions

# concatenate all predictions and targets:
y_true = np.concatenate(y_true, axis=0)
y_pred = np.concatenate(y_pred, axis=0)
# copte the ROC curve
fpr, tpr, thresholds = metrics.roc_curve(y_true, y_pred)