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zhangbaijin / MemoryNet

Code for paper: Memory Augment is All Your Need for image restoration(cloud,rain,shadow removal, low-light image enhancement, image deblur)即插即用提点的记忆模块
MIT License
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In MemoryNet.py, MemoryNet() forward(). How to get the x2 and x3, thif function input is x3_img #7

Closed huangwenwenlili closed 9 months ago

huangwenwenlili commented 11 months ago

def forward(self, x3_img):

    # Original-resolution Image for Stage 3
    H = x3_img.size(2)
    W = x3_img.size(3)

    # Multi-Patch Hierarchy: Split Image into four non-overlapping patches
    # Two Patches for Stage 2
    x2top_img  = x2[:,:,0:int(H/2),:]
    x2bot_img  = x2[:,:,int(H/2):H,:]

    x3top_img  = x3[:,:,0:int(H/2),:]
    x3bot_img  = x3[:,:,int(H/2):H,:]
zhangbaijin commented 11 months ago

baseline是CVPR2021的MPRNet