Create app.py

app.py

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+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+import torchvision.transforms as transforms
+from PIL import Image
+import gradio as gr
+
+# ------------------- Model Definition -------------------
+class SimpleCNN(nn.Module):
+    def __init__(self, num_classes=1):
+        super(SimpleCNN, self).__init__()
+        self.conv1 = nn.Conv2d(3, 32, kernel_size=3, padding=1)
+        self.conv2 = nn.Conv2d(32, 64, kernel_size=3, padding=1)
+        self.conv3 = nn.Conv2d(64, 128, kernel_size=3, padding=1)
+        self.pool = nn.MaxPool2d(2, 2)
+        self.fc1 = nn.Linear(128 * 28 * 28, 512)
+        self.fc2 = nn.Linear(512, num_classes)
+
+    def forward(self, x):
+        x = self.pool(F.relu(self.conv1(x)))
+        x = self.pool(F.relu(self.conv2(x)))
+        x = self.pool(F.relu(self.conv3(x)))
+        x = x.view(-1, 128 * 28 * 28)
+        x = F.relu(self.fc1(x))
+        x = self.fc2(x)
+        return x
+
+# ------------------- Load Model -------------------
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model = SimpleCNN()
+model.load_state_dict(torch.load("age_prediction_model1.pth", map_location=device))
+model.to(device)
+model.eval()
+
+# ------------------- Transform -------------------
+transform = transforms.Compose([
+    transforms.Resize((224, 224)),
+    transforms.ToTensor(),
+    transforms.Normalize([0.485, 0.456, 0.406],
+                         [0.229, 0.224, 0.225])
+])
+
+# ------------------- Prediction Function -------------------
+def predict(image):
+    image = transform(image).unsqueeze(0).to(device)
+    with torch.no_grad():
+        output = model(image).squeeze().item()
+    return f"Predicted Age: {round(output, 2)} years"
+
+# ------------------- Gradio Interface -------------------
+iface = gr.Interface(fn=predict, 
+                     inputs=gr.Image(type="pil"), 
+                     outputs="text",
+                     title="Face Age Prediction",
+                     description="Upload a face image and get a predicted age")
+
+iface.launch()