Update app.py

app.py

@@ -172,12 +172,13 @@ def predict(input_image:Image.Image, true_label:str):
  }
  return confidences, true_label, face_with_mask
 
-title = "Deepfake Image Detection"
-description = "~ AI - ML implementation for fake and real image detection..."
-article = "<p style='text-align: center'>...</p>"
+title1 = "Deepfake Image Detection"
+description1 = "~ AI - ML implementation for fake and real image detection..."
+article1 = "<p style='text-align: center'>...</p>"
 
-#interface
+interface1 = gr.Interface(fn=predict, inputs=gr.Image(type="pil"), outputs="label", theme = my_theme, title=title1, description=description1, article = article1)
 
+'''
 interface1 = gr.Interface(
  fn=predict,
  inputs=[
@@ -191,15 +192,16 @@ interface1 = gr.Interface(
  #ValueError: Invalid value for parameter `type`: auto. Please choose from one of: ['numpy', 'pil', 'filepath']
  ],
  theme = my_theme, #gr.themes.Soft(),
- title = title,
- description = description,
- article = article
+ title = title1,
+ description = description1,
+ article = article1
  #examples=[[examples[i]["path"], examples[i]["label"]] for i in range(10)]
 )
+'''
 
-title1 = "AI Generated Image Detection"
-description1 = "~ AI - ML implementation for AI image detection using older models such as VQGAN+CLIP."
-article1 = """
+title2 = "AI Generated Image Detection"
+description2 = "~ AI - ML implementation for AI image detection using older models such as VQGAN+CLIP."
+article2 = """
 NOTE:
 - To detect pictures generated using older models such as VQGAN+CLIP, please use the updated version of this detector instead.
 - In this model i'm using a ViT model to predict whether an artistic image was generated using AI or not.
@@ -209,11 +211,11 @@ NOTE:
 - Images scoring as very probably artificial (e.g. 90% or higher) could be referred to a human expert for further investigation, if needed.
 """
 
-#interface2 = gr.Interface(fn=image_classifier, inputs=gr.Image(type="pil"), outputs="label", theme = my_theme, title=title1, description=description1, article = article1)
+interface2 = gr.Interface(fn=image_classifier, inputs=gr.Image(type="pil"), outputs="label", theme = my_theme, title=title2, description=description2, article = article2)
 
 #demo.launch(show_api=False)
 
-#'''
+'''
 interface2 = gr.Interface(
  fn=image_classifier,
  inputs=[
@@ -231,8 +233,8 @@ interface2 = gr.Interface(
  description = description1,
  article = article1
 )
-#'''
+'''
  
 gr.TabbedInterface(
  [interface1, interface2], ["Deepfake Image Detection", "AI Image Detection"]
-).launch() #share=True)
+).launch() #share=True)