Delete app.py

app.py

@@ -1,41 +0,0 @@
-import torch
-import torchvision.transforms as transforms
-import gradio as gr
-from PIL import Image
-
-# Load a Pretrained Fashion Classification Model (ResNet18)
-model = torch.hub.load('pytorch/vision:v0.10.0', 'resnet18', pretrained=True)
-model.eval()  # Set model to evaluation mode
-
-# Define Class Labels for Clothing Items
-class_labels = [
-    "T-shirt", "Shirt", "Sweater", "Dress", "Jacket",
-    "Coat", "Pants", "Shorts", "Skirt", "Jeans"
-]
-
-# Image Preprocessing
-transform = transforms.Compose([
-    transforms.Resize((224, 224)),  # Resize image
-    transforms.ToTensor(),  # Convert to tensor
-    transforms.Normalize(mean=[0.485, 0.456, 0.406],
-                         std=[0.229, 0.224, 0.225])  # Normalize
-])
-
-# Classification Function
-def classify_dress(image):
-    image = transform(image).unsqueeze(0)  # Add batch dimension
-    with torch.no_grad():
-        output = model(image)  # Run through model
-    predicted_class_index = output.argmax(dim=1).item()
-    return class_labels[predicted_class_index]
-
-# Gradio Interface
-iface = gr.Interface(
-    fn=classify_dress,
-    inputs=gr.Image(type="pil"),
-    outputs=gr.Label(num_top_classes=3),
-    title="Clothing1M Classifier",
-    description="Upload an image of clothing to classify it into one of 10 categories."
-)
-
-iface.launch()