Update app.py

app.py

@@ -14,48 +14,5 @@ else:
 subprocess.run(["git", "clone", "https://github.com/Nick088Official/Stable_Diffusion_Finetuned_Minecraft_Skin_Generator.git"])
 os.chdir("Stable_Diffusion_Finetuned_Minecraft_Skin_Generator")
 
-def run_inference(prompt, stable_diffusion_model, num_inference_steps, guidance_scale, num_images_per_prompt, model_precision_type, seed, output_image_name, verbose):
-    if stable_diffusion_model == '2':
-        sd_model = "minecraft-skins"
-    else:
-        sd_model = "minecraft-skins-sdxl"
-
-    command = f"python Python_Scripts/{sd_model}.py '{prompt}' {num_inference_steps} {guidance_scale} {num_images_per_prompt} {model_precision_type} {seed} {output_image_name} {'--verbose' if verbose else ''}"
-    
-    os.system(command)
-
-
-    return os.path.join(f"output_minecraft_skins/{output_image_name}")
-
-    
-# Define Gradio UI components
-prompt_input = gr.Textbox(label="Your Prompt", info="What the Minecraft Skin should look like")
-stable_diffusion_model_input = gr.Dropdown(['2', 'xl'], value="xl", label="Stable Diffusion Model", info="Choose which Stable Diffusion Model to use, xl understands prompts better")
-num_inference_steps_input = gr.Number(label="Number of Inference Steps", precision=0, value=25)
-guidance_scale_input = gr.Number(minimum=0.1, value=7.5, label="Guidance Scale", 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")
-num_images_per_prompt_input = gr.Number(minimum=1, value=1, precision=0, label="Number of Images per Prompt", info="The number of images to make with the prompt")
-model_precision_type_input = 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 gives better results")
-seed_input = gr.Number(value=42, label="Seed", info="A starting point to initiate generation, put 0 for a random one")
-output_image_name_input = gr.Textbox(label="Output Image Name", info="The name of the file of the output image skin, keep the .png", value="output-skin.png")
-verbose_input = gr.Checkbox(label="Verbose Output", info="Produce more detailed output while running", value=False)
-
-
-# Create the Gradio interface
-gr.Interface(
-    fn=run_inference,
-    inputs=[
-        prompt_input,
-        stable_diffusion_model_input,
-        num_inference_steps_input,
-        guidance_scale_input,
-        num_images_per_prompt_input,
-        model_precision_type_input,
-        seed_input,
-        output_image_name_input,
-        verbose_input
-    ],
-    outputs=gr.Image(label="Generated Minecraft Skin Image Asset"),
-    title="Minecraft Skin Generator",
-    description="Make AI generated Minecraft Skins by a Finetuned Stable Diffusion Version!<br>Model used: https://github.com/Nick088Official/Stable_Diffusion_Finetuned_Minecraft_Skin_Generator<br>Hugging Face Space made by [Nick088](https://linktr.ee/Nick088)",
-).launch(show_api=False, share=True)
 
+subprocess.run([r"Run_Inference_UI.bat"] check=True, shell=True)