Update app.py

app.py

@@ -1,4 +1,3 @@
-
 import gradio as gr
 import os
 import torch
@@ -8,12 +7,14 @@ from timeit import default_timer as timer
 from typing import Tuple, Dict
 
 # Setup class names
-class_names = ['Real', 'Fake']
+class_names = ['Fake', 'Real']
 
 ### 2. Model and transforms preparation ###
 
 # Create model
-model, model_transforms = create_model(num_classes=2)
+model, transforms = create_model(
+    num_classes=2,
+)
 
 # Load saved weights
 model.load_state_dict(
@@ -33,7 +34,7 @@ def predict(img) -> Tuple[Dict, float]:
     start_time = timer()
 
     # Transform the target image and add a batch dimension
-    img = model_transforms(img).unsqueeze(0)
+    img = transforms(img).unsqueeze(0)
 
     # Put model into evaluation mode and turn on inference mode
     model.eval()
@@ -54,7 +55,22 @@ def predict(img) -> Tuple[Dict, float]:
 
 # Create title, description and article strings
 title = "Reality Check"
-description = "An computer vision model to classify images as Real Or Fake(Ai Generated). The Model can classify the images with 95% Accuracy"
+description = """<h2>AI Image Classifier: Real vs. Fake Faces</h2>
+<p>Our computer vision model is designed to classify images of faces as either real or AI-generated with a 95% accuracy rate. This model is specifically trained to analyze facial features, so please ensure that the images you upload prominently feature visible faces.</p>
+<h3>Important Guidelines:</h3>
+<ul>
+  <li><strong>Focus on Faces:</strong> Ensure the uploaded images clearly show faces. The model is optimized for facial recognition and classification.</li>
+  <li><strong>Image Examples:</strong> Refer to the examples below to understand the type of images suitable for classification.</li>
+  <li><strong>Avoid Other AI-Generated Content:</strong> Do not upload images of objects, landscapes, or any non-facial AI-generated content as the model is not trained to classify these correctly.</li>
+</ul>
+<h3>Usage Instructions:</h3>
+<ol>
+  <li><strong>Prepare Your Image:</strong> Ensure the face is visible and prominent.</li>
+  <li><strong>Upload the Image:</strong> Use the provided interface to upload your image for classification.</li>
+  <li><strong>Receive Classification:</strong> The model will analyze the facial features and classify the image as either real or fake with 95% accuracy.</li>
+</ol>
+<p>Start using the model now to see the power of AI in distinguishing between real and AI-generated faces!</p>
+"""
 article = "Created at [Real Or Fake]"
 
 # Create examples list from "examples/" directory
@@ -72,4 +88,4 @@ demo = gr.Interface(fn=predict, # mapping function from input to output
                     article=article)
 
 # Launch the demo!
-demo.launch()
+demo.launch()