Comments (3)
Hi, can you provide more information about your data and training?
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Thanks for your reply! I'm also using the SUN-SEG dataset, applying the entropy-based fusion strategy you proposed, using pce loss and mps loss, but since my image prediction result is not two channels, there may be an error in how the fusion result is converted to a pseudo-mask (no argmax operation).
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Hi, for our method, you can view polyp segmentation as 2-class problem (out_channel = 2) and apply softmax to get the probability map from the model raw output, the logits.
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Related Issues (7)
- Regarding the test phase, whether the output is a fused mask or a branch mask? HOT 2
- 数据集 HOT 11
- Hello, may I ask what does the last / \ of this line in the losses.py mean?
- Hello HOT 6
- Hello,in the data preparing file, I find there si a 'csv_root',what data should i put into it? HOT 10
- Perhaps you can provide the full eval-result running on the SUNSEG dataset? They are the results of Smeasure, maxEm, wFmeasure, maxDice, maxIou on four test datasets. HOT 2
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