Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -17,6 +17,7 @@ os.chdir("Stable_Diffusion_Finetuned_Minecraft_Skin_Generator")
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def generate(
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prompt,
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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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@@ -30,13 +31,19 @@ def generate(
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else:
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verbose_opt = ''
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-
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return os.path.join(f"output_minecraft_skins/{output_image_name}")
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prompt = gr.Textbox(label="Prompt", interactive=True)
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num_inference_steps = gr.Number(value=50, minimum=1, interactive=True, label="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")
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@@ -55,6 +62,7 @@ verbose = gr.Checkbox(label="Verbose Output", interactive=True, value=False, inf
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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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25,
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7.5,
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1,
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@@ -67,7 +75,7 @@ examples = [
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gr.Interface(
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fn=generate,
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inputs=[prompt, num_inference_steps, guidance_scale, num_images_per_prompt, model_precision_type, output_image_name, seed, verbose],
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outputs=gr.Image(label="Generated Minecraft Skin"),
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title="Stable Diffusion Finetuned 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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def generate(
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prompt,
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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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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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subprocess.run(["python", f"Python_Script/{sd_model}.py", prompt, num_inference_steps, guidance_scale, num_images_per_prompt, model_precision_type, seed, output_image_name, verbose_opt])
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return os.path.join(f"output_minecraft_skins/{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", 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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examples = [
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[
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"A man in a purple suit wearing a tophat.",
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"xl",
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25,
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7.5,
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1,
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gr.Interface(
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fn=generate,
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inputs=[prompt, stable_diffusion_model, num_inference_steps, guidance_scale, num_images_per_prompt, model_precision_type, output_image_name, seed, verbose],
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outputs=gr.Image(label="Generated Minecraft Skin"),
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title="Stable Diffusion Finetuned 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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