Update app.py

app.py

@@ -3,13 +3,8 @@ import requests
 import io
 from PIL import Image
 import json
-import os
-import logging
-import time
-from tqdm import tqdm
-from image_processing import downscale_image, limit_colors, resize_image, convert_to_grayscale, convert_to_black_and_white
+from image_processing import downscale_image, limit_colors, convert_to_grayscale, convert_to_black_and_white
 
-# Placeholder class for processed images
 class SomeClass:
     def __init__(self):
         self.images = []
@@ -17,131 +12,63 @@ class SomeClass:
 with open('loras.json', 'r') as f:
     loras = json.load(f)
 
-def update_selection(selected_state: gr.SelectData):
+def update_selection(selected_state):
     selected_lora_index = selected_state.index
     selected_lora = loras[selected_lora_index]
     new_placeholder = f"Type a prompt for {selected_lora['title']}"
     lora_repo = selected_lora["repo"]
     updated_text = f"### Selected: [{lora_repo}](https://huggingface.co/{lora_repo}) ✨"
-    return (
-        gr.update(placeholder=new_placeholder),
-        updated_text,
-        selected_state
-    )
+    return (gr.update(placeholder=new_placeholder), updated_text, selected_state)
 
-def run_lora(prompt, selected_state, pixel_art_options, postprocess_options, progress=gr.Progress(track_tqdm=True)):
+def run_lora(prompt, selected_state, progress=gr.Progress(track_tqdm=True)):
     selected_lora_index = selected_state.index
     selected_lora = loras[selected_lora_index]
     api_url = f"https://api-inference.huggingface.co/models/{selected_lora['repo']}"
-    payload = {
-        "inputs": f"{prompt} {selected_lora['trigger_word']}",
-        "parameters": {"negative_prompt": "bad art, ugly, watermark, deformed"},
-    }
+    payload = {"inputs": f"{prompt} {selected_lora['trigger_word']}", "parameters": {"negative_prompt": "bad art, ugly, watermark, deformed"}}
     response = requests.post(api_url, json=payload)
     if response.status_code == 200:
         original_image = Image.open(io.BytesIO(response.content))
-        
         processed = SomeClass()
         processed.images = [original_image]
-        
-        pixel_art_script = PixelArtScript()
-        postprocess_script = ScriptPostprocessingUpscale()
-        
-        pixel_art_script.postprocess(
-            processed,
-            **pixel_art_options
-        )
-        
-        postprocess_script.process(
-            processed,
-            **postprocess_options
-        )
-        
         refined_image = processed.images[-1]
-        
         return original_image, refined_image
 
-def apply_post_processing(image, image_processing_options):
+def apply_post_processing(image, downscale, limit_colors, grayscale, black_and_white):
     processed_image = image.copy()
-    
-    if image_processing_options['downscale'] > 1:
-        processed_image = downscale_image(processed_image, image_processing_options['downscale'])
-        
-    if image_processing_options['limit_colors']:
+    if downscale > 1:
+        processed_image = downscale_image(processed_image, downscale)
+    if limit_colors:
         processed_image = limit_colors(processed_image)
-        
-    if image_processing_options['grayscale']:
+    if grayscale:
         processed_image = convert_to_grayscale(processed_image)
-        
-    if image_processing_options['black_and_white']:
+    if black_and_white:
         processed_image = convert_to_black_and_white(processed_image)
-        
     return processed_image
 
 with gr.Blocks() as app:
     title = gr.Markdown("# artificialguybr LoRA portfolio")
     description = gr.Markdown("### This is a Pixel Art Generator using SD Loras.")
     selected_state = gr.State()
-    
     with gr.Row():
-        gallery = gr.Gallery(
-            [(item["image"], item["title"]) for item in loras],
-            label="LoRA Gallery",
-            allow_preview=False,
-            columns=3
-        )
-        
+        gallery = gr.Gallery([(item["image"], item["title"]) for item in loras], label="LoRA Gallery", allow_preview=False, columns=3)
         with gr.Column():
             prompt_title = gr.Markdown("### Click on a LoRA in the gallery to create with it")
             selected_info = gr.Markdown("")
-            
             with gr.Row():
                 prompt = gr.Textbox(label="Prompt", show_label=False, lines=1, max_lines=1, placeholder="Type a prompt after selecting a LoRA")
                 button = gr.Button("Run")
-            
             result = gr.Image(interactive=False, label="Generated Image")
             refined_result = gr.Image(interactive=False, label="Refined Generated Image")
-            
-            # New Output for Post-Processed Image
             post_processed_result = gr.Image(interactive=False, label="Post-Processed Image")
-            
-            # New UI elements for pixel art options
-            with gr.Row():
-                pixel_art_options = PixelArtScript().ui(True)
-                postprocess_options = ScriptPostprocessingUpscale().ui()
-                
-            # New UI elements for image processing options
             with gr.Row():
                 downscale = gr.Slider(minimum=1, maximum=10, step=1, label="Downscale")
                 limit_colors = gr.Checkbox(label="Limit Colors")
                 grayscale = gr.Checkbox(label="Grayscale")
                 black_and_white = gr.Checkbox(label="Black and White")
-                
-            image_processing_options = {
-                'downscale': downscale,
-                'limit_colors': limit_colors,
-                'grayscale': grayscale,
-                'black_and_white': black_and_white
-            }
-            
             post_process_button = gr.Button("Apply Post-Processing")
-    
-    gallery.select(
-        update_selection,
-        outputs=[prompt, selected_info, selected_state]
-    )
-    
-    prompt.submit(
-        fn=run_lora,
-        inputs=[prompt, selected_state, pixel_art_options, postprocess_options],
-        outputs=[result, refined_result]
-    )
-    
-    post_process_button.click(
-        fn=apply_post_processing,
-        inputs=[refined_result, image_processing_options],
-        outputs=[post_processed_result]
-    )
+    gallery.select(update_selection, outputs=[prompt, selected_info, selected_state])
+    prompt.submit(fn=run_lora, inputs=[prompt, selected_state], outputs=[result, refined_result])
+    post_process_button.click(fn=apply_post_processing, inputs=[refined_result, downscale, limit_colors, grayscale, black_and_white], outputs=[post_processed_result])
 
 app.queue(max_size=20, concurrency_count=5)
 app.launch()