Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -14,38 +14,24 @@ else:
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subprocess.run(["git", "clone", "https://github.com/Nick088Official/Stable_Diffusion_Finetuned_Minecraft_Skin_Generator.git"])
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os.chdir("Stable_Diffusion_Finetuned_Minecraft_Skin_Generator")
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stable_diffusion_model,
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num_inference_steps,
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guidance_scale,
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num_images_per_prompt,
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model_precision_type,
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seed,
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output_image_name,
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verbose
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):
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if verbose:
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verbose_opt = '--verbose'
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else:
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verbose_opt = ''
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if stable_diffusion_model == 'xl':
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sd_model = "minecraft-skins-sdxl"
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else:
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sd_model = "minecraft-skins"
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return
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prompt = gr.Textbox(label="Prompt", interactive=True)
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stable_diffusion_model = gr.Dropdown(["2", "xl"], interactive=True, label="Stable Diffusion Model", value="xl", info="Choose which Stable Diffusion Model to use, xl understands prompts better")
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num_inference_steps = gr.Number(value=50, minimum=1, interactive=True, label="Inference Steps",
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guidance_scale = gr.Number(value=7.5, minimum=0.1, interactive=True, label="Guidance Scale", info="How closely the generated image adheres to the prompt")
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@@ -59,6 +45,17 @@ output_image_name = gr.Textbox(label="Name of Generated Skin Output", interactiv
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verbose = gr.Checkbox(label="Verbose Output", interactive=True, value=False, info="Produce verbose output while running")
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examples = [
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[
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"A man in a purple suit wearing a tophat.",
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@@ -73,12 +70,23 @@ examples = [
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]
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]
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gr.Interface(
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fn=
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inputs=[
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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)",
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examples=examples,
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subprocess.run(["git", "clone", "https://github.com/Nick088Official/Stable_Diffusion_Finetuned_Minecraft_Skin_Generator.git"])
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os.chdir("Stable_Diffusion_Finetuned_Minecraft_Skin_Generator")
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def run_inference(prompt, stable_diffusion_model, num_inference_steps, guidance_scale, num_images_per_prompt, model_precision_type, output_image_name, verbose):
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if stable_diffusion_model == '2':
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sd_model = "minecraft-skins"
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else:
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sd_model = "minecraft-skins-sdxl"
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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 ''}"
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subprocess.run(["python", command], shell=True, check=True)
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return output_image_name
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prompt = gr.Textbox(label="Prompt", interactive=True)
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stable_diffusion_model = gr.Dropdown(["2", "xl"], interactive=True, label="Stable Diffusion Model", value="xl", info="Choose which Stable Diffusion Model to use, xl understands prompts better")
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num_inference_steps = gr.Number(value=50, minimum=1, interactive=True, label="Inference Steps",)
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guidance_scale = gr.Number(value=7.5, minimum=0.1, interactive=True, label="Guidance Scale", info="How closely the generated image adheres to the prompt")
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verbose = gr.Checkbox(label="Verbose Output", interactive=True, value=False, info="Produce verbose output while running")
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# Define Gradio UI components
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prompt_input = gr.Textbox(label="Your Prompt", info="What the Minecraft Skin should look like")
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stable_diffusion_model_input = gr.Dropdown(['2', 'xl'], label="Stable Diffusion Model", info="Choose which Stable Diffusion Model to use, xl understands prompts better")
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num_inference_steps_input = gr.Number(label="Number of Inference Steps", precision=0, value=25)
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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")
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num_images_per_prompt_input = gr.inputs.Number(minimum=1, value=1, precision=0, label="Number of Images per Prompt", info="The number of images to make with the prompt")
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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")
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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")
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verbose_input = gr.Checkbox(label="Verbose Output", info="Produce more detailed output while running", value=False)
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examples = [
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[
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"A man in a purple suit wearing a tophat.",
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]
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]
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# Create the Gradio interface
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gr.Interface(
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fn=run_inference,
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inputs=[
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prompt_input,
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stable_diffusion_model_input,
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num_inference_steps_input,
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guidance_scale_input,
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num_images_per_prompt_input,
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model_precision_type_input,
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output_image_name_input,
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verbose_input
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],
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outputs=gr.outputs.Image(label="Generated Image"),
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title="Minecraft Skin Generator",
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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)",
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examples=examples,
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).launch(show_api=False, share=True)
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# return os.path.join(f"output_minecraft_skins/{output_image_name}")
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