Changed scan func

.idea/workspace.xml

@@ -65,7 +65,7 @@
       <workItem from="1683665300392" duration="7649000" />
       <workItem from="1683708398011" duration="1235000" />
       <workItem from="1684437905081" duration="110000" />
-      <workItem from="1686602174110" duration="7569000" />
+      <workItem from="1686602174110" duration="7930000" />
     </task>
     <servers />
   </component>

app.py

@@ -70,57 +70,53 @@ class Net2(nn.Module):
 class Net(nn.Module):
     def __init__(self):
         super(Net, self).__init__()
-        self.conv1 = nn.Conv2d(3, 512, 3, padding=1)
-        self.bn1 = nn.BatchNorm2d(512)
+        self.conv1 = nn.Conv2d(3, 32, 3, padding=1)
         self.pool1 = nn.MaxPool2d(2, 2)
         self.dropout1 = nn.Dropout(0.25)
 
-        self.conv2 = nn.Conv2d(512, 256, 3, padding=1)
-        self.bn2 = nn.BatchNorm2d(256)
+        self.conv2 = nn.Conv2d(32, 32, 3, padding=1)
         self.pool2 = nn.MaxPool2d(2, 2)
         self.dropout2 = nn.Dropout(0.25)
 
-        self.conv3 = nn.Conv2d(256, 128, 3, padding=1)
-        self.bn3 = nn.BatchNorm2d(128)
+        self.conv3 = nn.Conv2d(32, 32, 3, padding=1)
         self.pool3 = nn.MaxPool2d(2, 2)
         self.dropout3 = nn.Dropout(0.25)
 
-        self.conv4 = nn.Conv2d(128, 64, 3, padding=1)
-        self.bn4 = nn.BatchNorm2d(64)
+        self.conv4 = nn.Conv2d(32, 32, 3, padding=1)
         self.pool4 = nn.MaxPool2d(2, 2)
-        self.dropout4 = nn.Dropout(0.20)
+        self.dropout4 = nn.Dropout(0.25)
 
         self.flatten = nn.Flatten()
 
-        self.fc1 = nn.Linear(1600, 300)
-        self.fc2 = nn.Linear(300, 150)
+        self.fc1 = nn.Linear(32 * 5 * 5, 200)
+        self.fc2 = nn.Linear(200, 150)
         self.fc3 = nn.Linear(150, 2)
 
     def forward(self, x):
-        x = F.relu(self.bn1(self.conv1(x)))
+        x = F.relu(self.conv1(x))
         x = self.pool1(x)
         x = self.dropout1(x)
 
-        x = F.relu(self.bn2(self.conv2(x)))
+        x = F.relu(self.conv2(x))
         x = self.pool2(x)
         x = self.dropout2(x)
 
-        x = F.relu(self.bn3(self.conv3(x)))
+        x = F.relu(self.conv3(x))
         x = self.pool3(x)
         x = self.dropout3(x)
 
-        x = F.relu(self.bn4(self.conv4(x)))
+        x = F.relu(self.conv4(x))
         x = self.pool4(x)
         x = self.dropout4(x)
 
         x = self.flatten(x)
         x = F.relu(self.fc1(x))
         x = F.relu(self.fc2(x))
-        x = F.softmax(self.fc3(x), dim=1)
+        x = torch.sigmoid(self.fc3(x))
         return x
 
 model = None
-model_path = "models1.pth"
+model_path = "model3.pth"
 
 model2 = None
 model2_path = "model4.pth"