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Upload model.onnx
Verified signatureConverted to onnx using following code: import torch import torch.nn as nn import torch.nn.functional as F from PIL import Image import torchvision.transforms as transforms # Define the model architecture (based on the code you provided) class WatermarkRemover(nn.Module): def __init__(self): super(WatermarkRemover, self).__init__() self.enc1 = self.conv_block(3, 64) self.enc2 = self.conv_block(64, 128) self.enc3 = self.conv_block(128, 256) self.enc4 = self.conv_block(256, 512) self.bottleneck = self.conv_block(512, 1024) self.dec4 = self.conv_block(1024 + 512, 512) self.dec3 = self.conv_block(512 + 256, 256) # Corrected input channels based on error message self.dec2 = self.conv_block(384, 128) # Corrected input channels based on error message self.dec1 = self.conv_block(192, 64) self.final_layer = nn.Conv2d(64, 3, kernel_size=1) def conv_block(self, in_channels, out_c…34f616c
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