Update app.py

app.py

@@ -20,16 +20,16 @@ def run_inference(prompt, stable_diffusion_model, num_inference_steps, guidance_
     else:
         sd_model = "minecraft-skins-sdxl"
 
-    command = f"Python_Scripts/{sd_model}.py '{prompt}' {num_inference_steps} {guidance_scale} {num_images_per_prompt} {model_precision_type} {output_image_name} {'--verbose' if verbose else ''}"
+    command = f"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 ''}"
 
-    subprocess.run(["python", command], shell=True, check=True)
+    subprocess.run(["python", command], check=True)
 
     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'], label="Stable Diffusion Model", info="Choose which Stable Diffusion Model to use, xl understands prompts better")
+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")