Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -23,7 +23,7 @@ os.chdir("Stable_Diffusion_Finetuned_Minecraft_Skin_Generator")
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@spaces.GPU()
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def run_inference(prompt, stable_diffusion_model, num_inference_steps, guidance_scale, model_precision_type, seed, filename, verbose):
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if stable_diffusion_model == '2':
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sd_model = "minecraft-skins"
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@@ -35,20 +35,17 @@ def run_inference(prompt, stable_diffusion_model, num_inference_steps, guidance_
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os.system(inference_command)
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# view it in 3d
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os.chdir("Scripts")
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command_3d_model = f"python to_3d_model.py '{filename}'"
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os.system(command_3d_model)
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os.chdir("..")
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# Return the generated image and the processed model
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return os.path.join(f"output_minecraft_skins/{filename}"), os.path.join(f"output_minecraft_skins/{filename}_3d_model.glb")
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# Define Gradio UI components
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prompt = gr.Textbox(label="Your Prompt", info="What the Minecraft Skin should look like")
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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")
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@@ -56,8 +53,9 @@ num_inference_steps = gr.Number(label="Number of Inference Steps", precision=0,
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guidance_scale = 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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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 gives better results")
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seed = gr.Number(value=42, label="Seed", info="A starting point to initiate generation, put 0 for a random one")
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filename = gr.Textbox(label="Output Image Name", info="The name of the file of the output image skin, keep the
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verbose = gr.Checkbox(label="Verbose Output", info="Produce more detailed output while running", value=False)
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# Create the Gradio interface
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@@ -71,12 +69,12 @@ gr.Interface(
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model_precision_type,
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seed,
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filename,
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verbose
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],
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outputs=[
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gr.Image(label="Generated Minecraft Skin Image Asset"),
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gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0], label="3D Model")
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],
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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>Credits: [Monadical-SAS](https://github.com/Monadical-SAS/minecraft_skin_generator) (Creators of the model), [Nick088](https://linktr.ee/Nick088) (Improving usage of the model), daroche (helping me fix the 3d model texture isue), [Brottweiler](https://gist.github.com/Brottweiler/483d0856c6692ef70cf90bf1a85ce364)
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).launch(show_api=False, share=True)
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@spaces.GPU()
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def run_inference(prompt, stable_diffusion_model, num_inference_steps, guidance_scale, model_precision_type, seed, filename, verbose, see_in_3d):
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if stable_diffusion_model == '2':
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sd_model = "minecraft-skins"
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os.system(inference_command)
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# view it in 3d
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if see_in_3d:
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os.chdir("Scripts")
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command_3d_model = f"python to_3d_model.py '{filename}'"
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os.system(command_3d_model)
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os.chdir("..")
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glb_path = os.path.join(f"output_minecraft_skins/{filename}_3d_model.glb")
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return os.path.join(f"output_minecraft_skins/{filename}"), glb_path
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else:
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return os.path.join(f"output_minecraft_skins/{filename}"), None
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# Define Gradio UI components
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prompt = gr.Textbox(label="Your Prompt", info="What the Minecraft Skin should look like")
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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")
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guidance_scale = 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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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 gives better results")
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seed = gr.Number(value=42, label="Seed", info="A starting point to initiate generation, put 0 for a random one")
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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")
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verbose = gr.Checkbox(label="Verbose Output", info="Produce more detailed output while running", value=False)
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see_in_3d = gr.Checkbox(label="See in 3D", info="View the generated skin in 3D", value=False)
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# Create the Gradio interface
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model_precision_type,
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seed,
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filename,
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verbose,
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see_in_3d
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],
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outputs=[
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gr.Image(label="Generated Minecraft Skin Image Asset"),
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gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0], label="3D Model")
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],
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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>Credits: [Monadical-SAS](https://github.com/Monadical-SAS/minecraft_skin_generator) (Creators of the model), [Nick088](https://linktr.ee/Nick088) (Improving usage of the model), daroche (helping me fix the 3d model texture isue), [Brottweiler](https://gist.github.com/Brottweiler/483d0856c6692ef70cf90bf1a85ce364)
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