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app.py

@@ -1,181 +1,186 @@
-import subprocess
-import os
 import gradio as gr
-import torch
-import numpy as np
-from PIL import Image, ImageEnhance
+import os
 from pathlib import Path
+from utils import setup_repository, run_inference
 
-# Constants
-DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
-MAX_SEED = np.iinfo(np.int32).max
+# Ensure output directory exists
 OUTPUT_DIR = Path("output_minecraft_skins")
-
-print(f"Using: {DEVICE}")
-
-# Repo URL
-REPO_URL = "https://github.com/BF667/Minecraft_Skin_Generator.git"
-REPO_NAME = "Minecraft_Skin_Generator"
-REPO_PATH = Path(REPO_NAME)
-
-def setup_repository():
-    """Clones or updates the Git repository."""
-    if not REPO_PATH.exists():
-        print(f"Cloning {REPO_NAME} repository...")
-        try:
-            subprocess.run(["git", "clone", REPO_URL], check=True)
-            print("Repository cloned successfully.")
-        except subprocess.CalledProcessError as e:
-            print(f"Error cloning repository: {e}")
-            raise
-    else:
-        print(f"{REPO_NAME} repository already exists. Checking for updates...")
-        try:
-            # Change to the repository directory to pull updates
-            os.chdir(REPO_PATH)
-            subprocess.run(["git", "pull"], check=True)
-            print("Repository updated successfully.")
-            os.chdir("..") # Change back to original directory
-        except subprocess.CalledProcessError as e:
-            print(f"Error updating repository: {e}")
-            raise
-
-    # Change to the repository directory for script execution
-    os.chdir(REPO_PATH)
-
-
-def run_inference(
-    prompt: str,
-    stable_diffusion_model: str,
-    num_inference_steps: int,
-    guidance_scale: float,
-    model_precision_type: str,
-    seed: int,
-    filename: str,
-    model_3d: bool,
-    verbose: bool,
-):
-    """Runs the inference process for generating Minecraft skins."""
-
-    sd_model_map = {
-        '2': "minecraft-skins",
-        'xl': "minecraft-skins-sdxl",
-    }
-    sd_script = sd_model_map.get(stable_diffusion_model)
-
-    if not sd_script:
-        raise ValueError(f"Invalid stable_diffusion_model: {stable_diffusion_model}")
-
-    command = [
-        "python",
-        f"Scripts/{sd_script}.py",
-        prompt,
-        str(num_inference_steps),
-        str(guidance_scale),
-        model_precision_type,
-        str(seed),
-        filename,
-    ]
-
-    if model_3d:
-        command.append("--model_3d")
-    if verbose:
-        command.append("--verbose")
-
-    try:
-        # Use subprocess.run for better control and error handling
-        result = subprocess.run(command, capture_output=True, text=True, check=True)
-        print("Inference command output:")
-        print(result.stdout)
-        if result.stderr:
-            print("Inference command error output:")
-            print(result.stderr)
-
-    except subprocess.CalledProcessError as e:
-        print(f"Error during inference: {e}")
-        print(f"Stdout: {e.stdout}")
-        print(f"Stderr: {e.stderr}")
-        return None, None  # Return None for outputs on error
-    except Exception as e:
-        print(f"An unexpected error occurred: {e}")
-        return None, None
-
-    # Ensure output directory exists
-    OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
-
-    # Construct output paths using pathlib
-    image_path = OUTPUT_DIR / filename
-    model_3d_path = OUTPUT_DIR / f"{filename.split('.')[0]}_3d_model.glb" if model_3d else None
-
-    # Basic check for file existence (can be more robust)
-    if not image_path.exists():
-        print(f"Warning: Image file not found at {image_path}")
-        image_path = None
-    if model_3d and model_3d_path and not model_3d_path.exists():
-        print(f"Warning: 3D model file not found at {model_3d_path}")
-        model_3d_path = None
-
-    return str(image_path) if image_path else None, str(model_3d_path) if model_3d_path else None
-
-
-def create_gradio_ui():
-    """Defines and returns the Gradio UI components."""
-    with gr.Blocks(title="Minecraft Skin Generator", css=".pixelated {image-rendering: pixelated} .checkered img {background-image: url(\'data:image/svg+xml,<svg xmlns=\'http://www.w3.org/2000/svg\' width=\'2\' height=\'2\' fill-opacity=\'.15\'><rect x=\'1\' width=\'1\' height=\'1\'/><rect y=\'1\' width=\'1\' height=\'1\'/></svg>\');background-size: 16px;}") as imsteve:
-        gr.Label("Minecraft Skin Generator")
-        gr.Markdown("Make AI generated Minecraft Skins by a Finetuned Stable Diffusion Version!<br>\nGithub Repository & Model used: https://github.com/Nick088Official/Minecraft_Skin_Generator<br>\n**Credits:**\n [Monadical-SAS](https://github.com/Monadical-SAS/minecraft_skin_generator)\n (Creators of the model), [Nick088](https://linktr.ee/Nick088) (Improving usage of the model)\n daroche (helping fix the 3d model texture isue)\n [Brottweiler](https://gist.github.com/Brottweiler/483d0856c6692ef70cf90bf1a85ce364)(script to fix the 3d model texture)\n [not-holar](https://huggingface.co/not-holar) (made the rendering of the image asset in the web ui look pixelated like minecraft and have a checkered background)\n[meew](https://huggingface.co/spaces/meeww/Minecraft_Skin_Generator/blob/main/models/player_model.glb) (Minecraft Player 3d model) <br>\n [![Discord](https://img.shields.io/discord/1198701940511617164?color=%23738ADB&label=Discord&style=for-the-badge)](https://discord.gg/AQsmBmgEPy)")
-
-        with gr.Row():
-            prompt = gr.Textbox(label="Your Prompt", info="What the Minecraft Skin should look like")
-            stable_diffusion_model = gr.Dropdown(['2', 'xl'], value="xl", label="Stable Diffusion Model", info="Choose which Stable Diffusion Model to use, xl understands prompts better")
-            model_precision_type = gr.Dropdown(["fp16", "fp32"], value="fp16", label="Model Precision Type", info="The precision type to load the model, like fp16 which is faster, or fp32 which is more precise but more resource consuming")
-
-        with gr.Row():
-            num_inference_steps = gr.Slider(label="Number of Inference Steps", info="The number of denoising steps of the image. More denoising steps usually lead to a higher quality image at the cost of slower inference", minimum=1, maximum=50, value=25, step=1)
-            guidance_scale = gr.Slider(label="Guidance Scale", info="Controls how much the image generation process follows the text prompt. Higher values make the image stick more closely to the input text.", minimum=0.0, maximum=10.0, value=7.5, step=0.1)
-            seed = gr.Slider(value=42, minimum=0, maximum=MAX_SEED, step=1, label="Seed", info="A starting point to initiate the generation process, put 0 for a random one")
+OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
+
+# Custom CSS for Minecraft pixelated look and checkered background
+CUSTOM_CSS = """
+.pixelated { image-rendering: pixelated; image-rendering: -moz-crisp-edges; image-rendering: crisp-edges; }
+.checkered { 
+    background-image: url('data:image/svg+xml,<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16"><rect fill="%23ddd" width="8" height="8"/><rect fill="%23ddd" x="8" y="8" width="8" height="8"/><rect fill="%23bbb" x="8" width="8" height="8"/><rect fill="%23bbb" y="8" width="8" height="8"/></svg>'); 
+    background-size: 16px; 
+}
+#mc-skin { max-width: 400px; margin: auto; }
+#mc-model { height: 500px; }
+.sidebar { background: linear-gradient(135deg, #4CAF50 0%, #45a049 100%); }
+"""
+
+def random_seed():
+    """Generate a random seed."""
+    import numpy as np
+    return np.random.randint(0, np.iinfo(np.int32).max)
+
+def clear_all():
+    """Clear all outputs."""
+    return None, None, gr.Gallery(visible=False), []
+
+with gr.Blocks(
+    title="Minecraft Skin Generator",
+    theme=gr.themes.Soft(primary_hue="green", secondary_hue="emerald"),
+    css=CUSTOM_CSS,
+    fill_height=True
+) as demo:
+    gr.Markdown(
+        """
+        # 🚀 Minecraft Skin Generator
+        **Built with [anycoder](https://huggingface.co/spaces/akhaliq/anycoder)**
         
-        filename = gr.Textbox(label="Output Image Name", info="The name of the file of the output image skin, keep the.png", value="output-skin.png")
-        with gr.Row():
-            model_3d = gr.Checkbox(label="See as 3D Model too", info="View the generated skin as a 3D Model too", value=True)
-            verbose = gr.Checkbox(label="Verbose Output", info="Produce more detailed output while running", value=False)
+        Make AI generated Minecraft Skins using finetuned Stable Diffusion models! 🎨👨‍💼
         
-        generate_skn = gr.Button("Generate")
-        image_output = gr.Image(label="Generated Minecraft Skin Image Asset")
-        image3d_output = gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0],  label="3D Model View of the Skin")
+        [GitHub Repo](https://github.com/BF667/Minecraft_Skin_Generator) | [Discord](https://discord.gg/AQsmBmgEPy)
+        """
+    )
+    
+    gr.Markdown(
+        """
+        Credits: [Monadical-SAS](https://github.com/Monadical-SAS/minecraft_skin_generator), [Nick088](https://linktr.ee/Nick088), and more!
+        """
+    )
+    
+    state = gr.State(value=[])  # For gallery history
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            with gr.Accordion("🎛️ Generation Settings", open=True):
+                prompt = gr.Textbox(
+                    label="Prompt",
+                    placeholder="e.g., steve with diamond armor, cyberpunk creeper",
+                    lines=2,
+                    scale=3
+                )
+                with gr.Row():
+                    model_dropdown = gr.Dropdown(
+                        choices=["xl", "2"],
+                        value="xl",
+                        label="Model",
+                        info="XL understands prompts better"
+                    )
+                    precision_dropdown = gr.Dropdown(
+                        choices=["fp16", "fp32"],
+                        value="fp16",
+                        label="Precision"
+                    )
+                with gr.Row():
+                    steps_slider = gr.Slider(1, 50, value=25, step=1, label="Inference Steps")
+                    guidance_slider = gr.Slider(0.0, 10.0, value=7.5, step=0.1, label="Guidance Scale")
+                with gr.Row():
+                    seed_slider = gr.Slider(0, 2147483647, value=42, step=1, label="Seed", interactive=True)
+                    random_btn = gr.Button("🎲 Random Seed", scale=0, min_width=120)
+                filename_tb = gr.Textbox("output-skin.png", label="Filename (.png)", interactive=True)
+                gen_btn = gr.Button("Generate Skin! 🚀", variant="primary", scale=2)
+                adv_cb = gr.CheckboxGroup(
+                    choices=["3D Model", "Verbose"],
+                    label="Advanced Options",
+                    value=["3D Model"]
+                )
+            
+            gr.Examples(
+                examples=[
+                    ["steve with diamond armor"],
+                    ["alex as cyberpunk hacker"],
+                    ["creeper with sunglasses"],
+                    ["enderman in space suit"],
+                    ["zombie knight armor"]
+                ],
+                inputs=prompt
+            )
+            
+            gr.Markdown("### 📱 Cool Features")
+            gr.Markdown("""
+            - **Pixelated Minecraft Style** preview
+            - **3D Model Viewer** with rotations
+            - **Random Seed** for variety
+            - **History Gallery** of generations
+            - **Batch Mode** coming soon!
+            """)
         
-        generate_skn.click(
-            fn=run_inference,
-            inputs=[
-                prompt,
-                stable_diffusion_model,
-                num_inference_steps,
-                guidance_scale,
-                model_precision_type,
-                seed,
-                filename,
-                model_3d,
-                verbose,
-            ],
-            outputs=[
-                image_output,
-                image3d_output,
-            ],
-        )
-    return imsteve
-
-def main():
-    # Handle Hugging Face Spaces environment
-    if os.environ.get("HF_TOKEN") or os.environ.get("HF_HOME") or os.environ.get("HUGGINGFACE_HUB_CACHE"):
-        import spaces
-        @spaces.GPU(duration=75)
-        def wrapped_create_gradio_ui():
-            return create_gradio_ui()
-        demo = wrapped_create_gradio_ui()
-    else:
-        demo = create_gradio_ui()
-
-    setup_repository()
-    demo.launch(show_api=True, share=True)
+        with gr.Column(scale=2):
+            with gr.Group(elem_classes="checkered"):
+                skin_img = gr.Image(
+                    label="Generated Skin",
+                    elem_id="mc-skin",
+                    elem_classes="pixelated"
+                )
+            model_3d = gr.Model3D(
+                label="3D Preview",
+                clear_color=[0.1, 0.2, 0.3, 1.0],
+                elem_id="mc-model"
+            )
+            gallery = gr.Gallery(
+                label="Generation History",
+                columns=3,
+                height=300,
+                visible=True
+            )
+    
+    # Events
+    random_btn.click(random_seed, outputs=seed_slider)
+    
+    gen_btn.click(
+        fn=run_inference,
+        inputs=[
+            prompt,
+            model_dropdown,
+            steps_slider,
+            guidance_slider,
+            precision_dropdown,
+            seed_slider,
+            filename_tb,
+            gr.State(lambda x: "3D Model" in x)(adv_cb),
+            gr.State(lambda x: "Verbose" in x)(adv_cb)
+        ],
+        outputs=[skin_img, model_3d],
+        api_name="generate_skin",
+        api_visibility="public",
+        show_progress="full"
+    ).then(
+        fn=lambda img_path, history: (history + [img_path] if img_path else history)[:12],
+        inputs=[skin_img, state],
+        outputs=[gallery, state]
+    )
+    
+    # Clear button
+    gr.ClearButton([prompt, skin_img, model_3d, gallery, state], value="🗑️ Clear All")
+    
+    # Examples click
+    gr.Examples(
+        examples=[
+            ["steve with diamond armor"],
+            ["alex as cyberpunk hacker"],
+            ["creeper with sunglasses"],
+            ["enderman in space suit"],
+            ["zombie knight armor"]
+        ],
+        inputs=[prompt],
+        examples_per_page=5,
+        run_on_click=True
+    )
+
+# Setup repo on load
+demo.load(setup_repository)
 
 if __name__ == "__main__":
-    main()
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=True,
+        footer_links=[
+            {"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"},
+            "api",
+            "gradio"
+        ]
+    )

requirements.txt

@@ -1,7 +1,10 @@
-torch
-transformers
-diffusers
-accelerate
-gradio==5.29.1
+gradio
+numpy
+requests
+Pillow
+pandas
+matplotlib
+plotly
 scipy
-Pillow
+scikit-learn
+joblib