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Update app.py
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app.py
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@@ -5,6 +5,8 @@ from transformers import BlipProcessor, BlipForConditionalGeneration # 4. BLIP
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from PIL import Image # 5. Pillow for image processing
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import openai # 6. OpenAI library for DALL路E API calls
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import os # 7. OS for environment variables
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# 8. Create the FastAPI app
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app = FastAPI()
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@@ -23,13 +25,18 @@ async def generate(
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style: str = Form("chibi"), # 13. The desired style (chibi/anime/cartoon), defaults to "chibi"
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# 14. Load and convert the uploaded image to RGB
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img_bytes = await image.read()
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img = Image.open(io.BytesIO(img_bytes)).convert("RGB")
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inputs = processor(img, return_tensors="pt")
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out = model.generate(**inputs)
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caption = processor.decode(out[0], skip_special_tokens=True)
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# 16. Construct the DALL路E prompt using the style and the caption
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prompt = (
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from PIL import Image # 5. Pillow for image processing
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import openai # 6. OpenAI library for DALL路E API calls
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import os # 7. OS for environment variables
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from face_to_prompt import extract_face_prompt
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# 8. Create the FastAPI app
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app = FastAPI()
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style: str = Form("chibi"), # 13. The desired style (chibi/anime/cartoon), defaults to "chibi"
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):
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# 14. Load and convert the uploaded image to RGB
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# img_bytes = await image.read()
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# img = Image.open(io.BytesIO(img_bytes)).convert("RGB")
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# # 15. Caption the image using BLIP
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# inputs = processor(img, return_tensors="pt")
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# out = model.generate(**inputs)
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# caption = processor.decode(out[0], skip_special_tokens=True)
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with open("temp_input.jpg", "wb") as f:
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f.write(await image.read())
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caption = extract_face_prompt("temp_input.jpg")
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# 16. Construct the DALL路E prompt using the style and the caption
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prompt = (
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