Removed some duplication from merge

app.py

@@ -112,13 +112,12 @@ with gr.Blocks() as demo:
             </div>""")
     markdown_instructions = """## How It Works
 
-1. Your intitial text along with the prompt is sent to Llama 3 70b to generate a python dictionary.
-2. This new text will populate in interactive text fields. If it isn't perfect you can edit the text to fit your item.
-3. The final text field is the Stable Diffusion prompt, these generate like one sentence stories describing the scene of your item. This field can also be edited.
-## The first image generation take about 2 minutes for model to 'cold boot' after that it's ~10s per image.
-4. **Image and Text Generation**: Now generate 4 card template without text and pick your favorite.
-5. Finally, add text to your favorite template.
-3. **Result**: The final product is a beautifully crafted D&D item card, ready for use in your gaming sessions."""
+1. Your intitial text along with the prompt is sent to OpenAI's GPT-4o to generate a JSON.
+2. This JSON will be parsed into textboxes to review and edit. 
+3. The final text field is the image prompt, these generate like one sentence stories describing the scene of your pet.
+4. **Image and Text Generation**: Now generate 4 blank cards in about 15 seconds.
+5. Finally, click the add text button to add text to your favorite template.
+3. **Result**: The final product is a beautifully crafted collectible pet card."""
 
     gr.Markdown(markdown_instructions)
 

card_generator.py

@@ -59,21 +59,11 @@ def render_text_on_card(image_path, pet_name,
                                     pet_energy,
                                     pet_noise,
                                     pet_play) : 
-def render_text_on_card(image_path, pet_name,
-                                    pet_species,
-                                    pet_breed,
-                                    pet_fur,
-                                    pet_intelligence,
-                                    pet_affection,
-                                    pet_energy,
-                                    pet_noise,
-                                    pet_play) : 
+
     # Card Properties 
     image_list = []
     pet_properties = f"Intelligence : {pet_intelligence} \n Affection : {pet_affection} \n Energy : {pet_energy} \n Noise : {pet_noise} \n Play : {pet_play}"
     output_image_path = f"./{pet_name}.png"
-    pet_properties = f"Intelligence : {pet_intelligence} \n Affection : {pet_affection} \n Energy : {pet_energy} \n Noise : {pet_noise} \n Play : {pet_play}"
-    output_image_path = f"./{pet_name}.png"
     print(f"Saving image to {output_image_path}")
     font_path = "./fonts/Balgruf.ttf"
     italics_font_path = './fonts/BalgrufItalic.ttf'
@@ -109,20 +99,17 @@ def render_text_on_card(image_path, pet_name,
     # open image and render text
     image = u.open_image_from_url(image_path)
     image = rend.render_text_with_dynamic_spacing(image, pet_name, title_center_position, title_area_width, title_area_height,font_path,initial_font_size)
-    image = rend.render_text_with_dynamic_spacing(image, pet_name, title_center_position, title_area_width, title_area_height,font_path,initial_font_size)
     image = rend.render_text_with_dynamic_spacing(image,type_text , type_center_position, type_area_width, type_area_height,font_path,initial_font_size)
     image = rend.render_text_with_dynamic_spacing(image, pet_properties, description_position, description_area_width, description_area_height,font_path,initial_font_size, description = True)
     # paste_image_and_resize(image, value_overlay_path,x_position= 0,y_position=0, img_width= 768, img_height= 1024)
     #Paste Sizzek Sticker
     paste_image_and_resize(image, sticker_path_dictionary['Default'],x_position= 0,y_position=909, img_width= 115, img_height= 115, purchased_item_key= None)
-    paste_image_and_resize(image, sticker_path_dictionary['Default'],x_position= 0,y_position=909, img_width= 115, img_height= 115, purchased_item_key= None)
 
     # Add blur, gives it a less artificial look, put into list and return the list since gallery requires lists
     image = image.filter(ImageFilter.GaussianBlur(.5))
     image_list.append(image)
    
     image = image.save(f"./output/{pet_name}.png")
-    image = image.save(f"./output/{pet_name}.png")
     
     
 

img2img.py

@@ -26,7 +26,7 @@ def preview_and_generate_image(num_images, sd_prompt, user_input_template):
     print(f"sd_prompt: {sd_prompt}")
     print(f"user_input_template: {user_input_template}")
     num_images = int(4)
-    sd_prompt = f"magnum opus, blank card, no text, blank textboxes, detailed high quality animal properties borders, {sd_prompt}"
+    sd_prompt = f"magnum opus, blank card, no text, blank textbox at top for title, mid for details and bottom for description, detailed high quality animal properties borders, {sd_prompt}"
     try:
         # Save the image to a temporary file
         with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp_file:

item_dict_gen.py

@@ -68,9 +68,6 @@ pet_prompt_instructions = """ **Purpose**: ONLY Generate a structured json follo
 - **Input Placeholder**:
     - "{pet}": Replace with the pet name, ensuring it's wrapped in single quotes.
     
-    - "{pet}": Replace with the pet name, ensuring it's wrapped in single quotes.
-    
-
 **Output Examples**:
 1. Mignon the Toy Sized Chihuahua