Delete images/app.py

images/app.py

@@ -1,115 +0,0 @@
-import gradio as gr
-import requests
-import io
-from PIL import Image
-import json
-import os
-import logging
-import time
-from tqdm import tqdm
-
-# Import additional modules
-from pixelart import Script as PixelArtScript
-from postprocessing_pixelart import ScriptPostprocessingUpscale
-from utils import downscale_image, limit_colors, resize_image, convert_to_grayscale, convert_to_black_and_white
-
-# Placeholder class for processed images
-class SomeClass:
-    def __init__(self):
-        self.images = []
-
-with open('loras.json', 'r') as f:
-    loras = json.load(f)
-
-def update_selection(selected_state: gr.SelectData):
-    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
-    )
-
-def run_lora(prompt, selected_state, pixel_art_options, postprocess_options, 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"},
-    }
-    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
-
-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
-        )
-        
-        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
-            
-            # New UI elements for pixel art options
-            with gr.Row():
-                pixel_art_options = PixelArtScript().ui(True)
-                postprocess_options = ScriptPostprocessingUpscale().ui()
-    
-    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]
-    )
-    
-    button.click(
-        fn=run_lora,
-        inputs=[prompt, selected_state, pixel_art_options, postprocess_options],
-        outputs=[result, refined_result]
-    )
-
-app.queue(max_size=20, concurrency_count=5)
-app.launch()