/MNSIT-HandWritting-Recognition-CNN-Pytorch

MNSIT handwritten digit recognition using CNN in pytorch

Primary LanguageJupyter Notebook

MNSIT HANDWRITTEN DIGIT RECOGNETION USING CNN IN PYTORCH

a simple convolutional neural network in PyTorch and train it to recognize handwritten digits using the MNIST dataset. Training a classifier on the MNIST dataset can be regarded as the hello world of image recognition.

Sample Data

Sample data

Network used

class Net(nn.Module): """ConvNet -> Max_Pool -> RELU -> ConvNet -> Max_Pool -> RELU -> FC -> RELU -> FC -> SOFTMAX""" def init(self): super(Net, self).init() self.conv1 = nn.Conv2d(1, 20, 5, 1) self.conv2 = nn.Conv2d(20, 50, 5, 1) self.fc1 = nn.Linear(4450, 500) self.fc2 = nn.Linear(500, 10)

def forward(self, x):
    x = F.relu(self.conv1(x))
    x = F.max_pool2d(x, 2, 2)
    x = F.relu(self.conv2(x))
    x = F.max_pool2d(x, 2, 2)
    x = x.view(-1, 4*4*50)
    x = F.relu(self.fc1(x))
    x = self.fc2(x)
    return F.log_softmax(x, dim=1)

Plot Of Training Loss

Loss

Sample Predition

SAMPLE Prediction