Create app.py

images/app.py

@@ -0,0 +1,115 @@
+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()