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Mehmet Batuhan Duman
commited on
Commit
•
67b8498
1
Parent(s):
ea1daab
Changed scan func
Browse files- .idea/workspace.xml +1 -1
- app.py +13 -17
.idea/workspace.xml
CHANGED
@@ -65,7 +65,7 @@
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<workItem from="1683665300392" duration="7649000" />
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<workItem from="1683708398011" duration="1235000" />
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<workItem from="1684437905081" duration="110000" />
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-
<workItem from="1686602174110" duration="
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</task>
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<servers />
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</component>
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<workItem from="1683665300392" duration="7649000" />
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<workItem from="1683708398011" duration="1235000" />
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<workItem from="1684437905081" duration="110000" />
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+
<workItem from="1686602174110" duration="7930000" />
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</task>
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<servers />
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</component>
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app.py
CHANGED
@@ -70,57 +70,53 @@ class Net2(nn.Module):
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class Net(nn.Module):
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def __init__(self):
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super(Net, self).__init__()
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-
self.conv1 = nn.Conv2d(3,
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-
self.bn1 = nn.BatchNorm2d(512)
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self.pool1 = nn.MaxPool2d(2, 2)
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self.dropout1 = nn.Dropout(0.25)
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self.conv2 = nn.Conv2d(
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-
self.bn2 = nn.BatchNorm2d(256)
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self.pool2 = nn.MaxPool2d(2, 2)
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self.dropout2 = nn.Dropout(0.25)
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-
self.conv3 = nn.Conv2d(
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-
self.bn3 = nn.BatchNorm2d(128)
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self.pool3 = nn.MaxPool2d(2, 2)
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self.dropout3 = nn.Dropout(0.25)
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self.conv4 = nn.Conv2d(
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self.bn4 = nn.BatchNorm2d(64)
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self.pool4 = nn.MaxPool2d(2, 2)
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-
self.dropout4 = nn.Dropout(0.
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self.flatten = nn.Flatten()
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self.fc1 = nn.Linear(
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self.fc2 = nn.Linear(
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self.fc3 = nn.Linear(150, 2)
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def forward(self, x):
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x = F.relu(self.
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x = self.pool1(x)
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x = self.dropout1(x)
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x = F.relu(self.
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x = self.pool2(x)
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x = self.dropout2(x)
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x = F.relu(self.
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x = self.pool3(x)
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x = self.dropout3(x)
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x = F.relu(self.
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x = self.pool4(x)
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x = self.dropout4(x)
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x = self.flatten(x)
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x = F.relu(self.fc1(x))
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x = F.relu(self.fc2(x))
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x =
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return x
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model = None
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model_path = "
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model2 = None
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model2_path = "model4.pth"
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class Net(nn.Module):
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def __init__(self):
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super(Net, self).__init__()
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+
self.conv1 = nn.Conv2d(3, 32, 3, padding=1)
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self.pool1 = nn.MaxPool2d(2, 2)
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self.dropout1 = nn.Dropout(0.25)
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+
self.conv2 = nn.Conv2d(32, 32, 3, padding=1)
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self.pool2 = nn.MaxPool2d(2, 2)
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self.dropout2 = nn.Dropout(0.25)
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+
self.conv3 = nn.Conv2d(32, 32, 3, padding=1)
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self.pool3 = nn.MaxPool2d(2, 2)
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self.dropout3 = nn.Dropout(0.25)
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+
self.conv4 = nn.Conv2d(32, 32, 3, padding=1)
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self.pool4 = nn.MaxPool2d(2, 2)
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self.dropout4 = nn.Dropout(0.25)
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self.flatten = nn.Flatten()
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self.fc1 = nn.Linear(32 * 5 * 5, 200)
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self.fc2 = nn.Linear(200, 150)
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self.fc3 = nn.Linear(150, 2)
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def forward(self, x):
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x = F.relu(self.conv1(x))
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x = self.pool1(x)
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x = self.dropout1(x)
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x = F.relu(self.conv2(x))
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x = self.pool2(x)
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x = self.dropout2(x)
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x = F.relu(self.conv3(x))
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x = self.pool3(x)
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x = self.dropout3(x)
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x = F.relu(self.conv4(x))
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x = self.pool4(x)
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x = self.dropout4(x)
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x = self.flatten(x)
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x = F.relu(self.fc1(x))
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x = F.relu(self.fc2(x))
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x = torch.sigmoid(self.fc3(x))
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return x
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model = None
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model_path = "model3.pth"
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model2 = None
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model2_path = "model4.pth"
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