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Update app.py
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app.py
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@@ -12,8 +12,9 @@ import torch
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from diffusers import DiffusionPipeline
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from typing import Tuple
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#
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device = torch.device("
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# Setup rules for bad words (ensure the prompts are kid-friendly)
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bad_words = json.loads(os.getenv('BAD_WORDS', '["violence", "blood", "scary", "death", "ghost"]'))
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@@ -66,18 +67,17 @@ def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str
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DESCRIPTION = """## Children's Sticker Generator
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Generate fun and playful stickers for children using AI.
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"""
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MAX_SEED = np.iinfo(np.int32).max
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CACHE_EXAMPLES =
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# Initialize the DiffusionPipeline
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pipe = DiffusionPipeline.from_pretrained(
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"
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torch_dtype=torch.
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use_safetensors=True,
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).to(device)
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@@ -142,7 +142,7 @@ def generate(
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# Apply style
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prompt, negative_prompt = apply_style(style, prompt, negative_prompt)
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seed = int(randomize_seed_fn(seed, randomize_seed))
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generator = torch.
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width, height = size_map.get(size, (512, 512))
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@@ -157,7 +157,7 @@ def generate(
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"guidance_scale": guidance_scale,
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"num_inference_steps": 20,
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"generator": generator,
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"num_images_per_prompt":
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"output_type": "pil",
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}
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@@ -196,7 +196,7 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
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container=False,
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)
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run_button = gr.Button("Run")
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result = gr.Gallery(label="Generated Stickers", columns=
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error_output = gr.Textbox(label="Error", visible=False)
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with gr.Accordion("Advanced options", open=False):
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use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True, visible=True)
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@@ -236,7 +236,7 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
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minimum=0.1,
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maximum=20.0,
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step=0.1,
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value=
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)
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gr.Examples(
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from diffusers import DiffusionPipeline
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from typing import Tuple
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# Force CPU usage
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device = torch.device("cpu")
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torch.cuda.is_available = lambda: False
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# Setup rules for bad words (ensure the prompts are kid-friendly)
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bad_words = json.loads(os.getenv('BAD_WORDS', '["violence", "blood", "scary", "death", "ghost"]'))
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DESCRIPTION = """## Children's Sticker Generator
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Generate fun and playful stickers for children using AI.
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⚠️ Running on CPU. This may be slower.
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"""
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MAX_SEED = np.iinfo(np.int32).max
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CACHE_EXAMPLES = False
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# Initialize the DiffusionPipeline
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pipe = DiffusionPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5", # Using a smaller model for CPU
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torch_dtype=torch.float32,
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use_safetensors=True,
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).to(device)
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# Apply style
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prompt, negative_prompt = apply_style(style, prompt, negative_prompt)
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seed = int(randomize_seed_fn(seed, randomize_seed))
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generator = torch.manual_seed(seed)
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width, height = size_map.get(size, (512, 512))
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"guidance_scale": guidance_scale,
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"num_inference_steps": 20,
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"generator": generator,
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"num_images_per_prompt": 1, # Reduced to 1 for CPU
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"output_type": "pil",
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}
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container=False,
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)
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run_button = gr.Button("Run")
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result = gr.Gallery(label="Generated Stickers", columns=1, preview=True)
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error_output = gr.Textbox(label="Error", visible=False)
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with gr.Accordion("Advanced options", open=False):
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use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True, visible=True)
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minimum=0.1,
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maximum=20.0,
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step=0.1,
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value=7.5,
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)
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gr.Examples(
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