Added placeholder tabs and textual inversion link tab

app.py

@@ -422,10 +422,98 @@ with gr.Blocks() as noise_steps:
   # output_text = gr.Text(elem_id="output-text")
   # go_button.click(fn=simple_image_prompt, inputs=[prompt, dropdown], outputs=[output, output_text])
 
+
+    
+# -----------------------------------------------------------------------------------------------
+
+# ~~~ Depth Map TAB ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+
+with gr.Blocks() as depth_map:
+  gr.Markdown('''
+      # 🧑‍🚀 Depth Map Processor
+
+      This tool desn't exist yet! 
+      
+      When it's built it will let you input any image from your phone or computer and process it into a depth map image using a Stable Diffusion control net process. 
+      
+      Hopefully it'll be working soon. Check out the example below for now!
+
+      ![Escher hands](https://cdn.discordapp.com/attachments/1065349726007992411/1089030239201534063/IMG_1874.jpg)
+      ![Escher hands depth map](https://cdn.discordapp.com/attachments/1085605267481309197/1089031503612227705/tmp2bsa61a8.png)
+  ''')
+
+
+    
+# -----------------------------------------------------------------------------------------------
+
+# ~~~ Control Net TAB ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+
+with gr.Blocks() as control_net:
+  gr.Markdown('''
+      # 🧑‍🚀 Control Net Processor
+
+      This tool desn't exist yet! 
+      
+      When it's built it will let you input any image from your phone or computer and process it using any text prompt or combination of trained artist styles / concepts. 
+
+      Coming soon! If you want to play with normal control net without ahx artist concepts check out the link below.
+
+      [control net](https://huggingface.co/spaces/hysts/ControlNet)
+  ''')
+
+
+    
+# -----------------------------------------------------------------------------------------------
+
+# ~~~ TEXTUAL INVERSION TAB ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+
+with gr.Blocks() as inversion:
+  gr.Markdown('''
+      # 🧑‍🚀 Concept Trainer
+
+      This tool lets you train your own new models / concepts from any images you want that will appear automatically be added to the Beta Concepts and Advanced Prompting tabs!
+
+      For now the tool lives on Google Colab, which is Google's free tool for using their GPU's. Someday it might live here on our Hugging Face Space, but the process is a little too demanding for our current resources.
+
+      To train your own concept visit the link below and follow the instructions and be prepared to wait several hours.
+
+      [textual inversion training tool](https://colab.research.google.com/drive/1FhOpcEjHT7EN53Zv9MFLQTytZp11wjqg#forceEdit=true&sandboxMode=true&scrollTo=ZajfEoWHKAr3)
+  
+      ---
+
+      Note that you will need a access_token to run this. You can request this on our discord or get your own free one at the link below.
+
+      [hugging face access token](https://huggingface.co/docs/hub/security-tokens)
+  ''')
+
+
+    
+# -----------------------------------------------------------------------------------------------
+
+# ~~~ DREAM BOOTH TAB ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+
+with gr.Blocks() as dream_booth:
+  gr.Markdown('''
+      # 🧑‍🚀 Dream Booth Concept Trainer
+
+      This tool desn't exist yet! 
+      
+      When it's built it will let you input any image from your phone or computer and process it using any text prompt or combination of trained artist styles / concepts. 
+
+      Coming soon! If you want to play with normal control net without ahx artist concepts check out the link below.
+
+      [control net](https://huggingface.co/spaces/hysts/ControlNet)
+  ''')
+
+
     
     
 # -----------------------------------------------------------------------------------------------
 
 
-tabbed_interface = gr.TabbedInterface([new_welcome, dropdown_tab, beta, noise_steps], ["Welcome!", "Advanced Prompting", "Beta Concepts", "Noise Steps"])
+tabbed_interface = gr.TabbedInterface([new_welcome, dropdown_tab, beta, inversion, noise_steps, depth_map, control_net, dream_booth], ["Welcome!", "Advanced Prompting", "Beta Concepts", "Concept Trainer", "Noise Steps", "Depth Map", "Control Net", "Dream Booth"])
 tabbed_interface.launch()