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Update utils.py
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utils.py
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@@ -1,25 +1,40 @@
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import torch
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from diffusers import StableDiffusionImg2ImgPipeline
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from PIL import Image
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# --- Place any download or path setup here ---
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MODEL_ID = "runwayml/stable-diffusion-v1-5" # Can swap for custom path if using IP-Adapter
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DEVICE = "cpu"
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MODEL_CACHE = "
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# (Optional) Download IP-Adapter weights and patch pipeline if desired
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def generate_sticker(input_image, prompt):
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"""
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Given a user image and a prompt, generates a sticker/emoji-style portrait.
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"""
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# Load the model (download if not present)
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pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
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).to(DEVICE)
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# Preprocess the image (resize, etc)
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init_image = input_image.convert("RGB").resize((512, 512))
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import os
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# Set Hugging Face cache dir to a safe writable location (works in Spaces & Docker)
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os.environ["TRANSFORMERS_CACHE"] = "/workspace/.cache/huggingface"
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os.makedirs("/workspace/.cache/huggingface", exist_ok=True)
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import torch
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from diffusers import StableDiffusionImg2ImgPipeline
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from PIL import Image
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# --- Place any download or path setup here ---
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MODEL_ID = "runwayml/stable-diffusion-v1-5" # Can swap for custom path if using IP-Adapter
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DEVICE = "cpu"
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MODEL_CACHE = "/workspace/.cache/huggingface"
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# (Optional) Download IP-Adapter weights and patch pipeline if desired
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# Load the model ONCE at startup, not per request!
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pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
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MODEL_ID,
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torch_dtype=torch.float32,
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cache_dir=MODEL_CACHE,
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safety_checker=None, # Disable for demo/testing; enable in prod
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).to(DEVICE)
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def generate_sticker(input_image, prompt):
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"""
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Given a user image and a prompt, generates a sticker/emoji-style portrait.
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"""
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# Load the model (download if not present)
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# pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
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# MODEL_ID,
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# torch_dtype=torch.float32,
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# cache_dir=MODEL_CACHE,
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# safety_checker=None, # Disable for demo/testing
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# ).to(DEVICE)
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# Preprocess the image (resize, etc)
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init_image = input_image.convert("RGB").resize((512, 512))
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