TUI-NICR / ESANet

ESANet: Efficient RGB-D Semantic Segmentation for Indoor Scene Analysis

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How to Dataset Inference in cityscapes‘ image

feng899 opened this issue · comments

I runed a command:python inference_samples.py --dataset cityscapes --ckpt_path ./trained_models/cityscapes/r34_NBt1D_half.pth --depth_scale 1 --raw_depth
then changed sample_rgb.png and sample_rgb.png in the test in ./samples but this segmentation is terrible. I do not know why,how can I slove this question .
thanks.Look forward to your reply!

It depends on the images you use. The more different your images are from the dataset the model was trained on, the worse the segmentation will be.