Hi I am training the following model to count cell in microscopy images. I am keen to hear suggestions from people on how to improve the model. Many Thanks in advance.
import torch.nn as nn
class Convnet(nn.Module):
"""
A custom convnet for convolving 1080x1080 fluorescence micrograph images.
"""
def __init__(self):
super(Convnet,self).__init__()
self.main = nn.Sequential(
nn.Conv2d(4,16,10,stride=2,padding=0),
nn.LeakyReLU(0.2,inplace=False),
nn.Conv2d(16,32,7,stride=2,padding=0),
nn.LeakyReLU(0.2,inplace=False),
nn.Conv2d(32,64,3,stride=3,padding=0),
nn.LeakyReLU(0.2,inplace=False),
nn.Conv2d(64,96,3,stride=2,padding=0),
nn.LeakyReLU(0.2,inplace=False),
nn.Conv2d(96,128,3,stride=2,padding=0),
nn.LeakyReLU(0.2,inplace=False),
nn.Conv2d(128,192,3,stride=2,padding=0),
nn.LeakyReLU(0.2,inplace=False),
nn.Conv2d(192,256,3,stride=2,padding=0),
nn.LeakyReLU(0.2,inplace=False),
nn.Conv2d(256,256,3,stride=2,padding=0),
nn.LeakyReLU(0.2,inplace=False),
nn.Conv2d(256,1,1,stride=1,padding=0)
)
def forward(self, x):
# x: B x 2 x 1024 x 1024
return self.main(x) # B x 1 x 9 x 9