app.py

from fastapi import FastAPI, File, UploadFile, HTTPException
from fastapi.responses import JSONResponse
from PIL import Image
import numpy as np
from transformers import SamModel, SamProcessor
import io
import base64
import uvicorn

app = FastAPI(title="SAM-ViT-Base API")

# SAM modelini ve işlemciyi yükle
model = SamModel.from_pretrained("facebook/sam-vit-base")
processor = SamProcessor.from_pretrained("facebook/sam-vit-base")

@app.post("/segment/")
async def segment_image(file: UploadFile = File(...)):
    try:
        # Görüntüyü oku
        image_data = await file.read()
        image = Image.open(io.BytesIO(image_data)).convert("RGB")
        
        # Görüntüyü işlemciye hazırla
        inputs = processor(image, return_tensors="pt")
        
        # Model ile segmentasyon yap
        outputs = model(**inputs)
        
        # Maskeyi al
        masks = outputs.pred_masks.detach().cpu().numpy()
        mask = masks[0][0]  # İlk maskeyi al (örnek olarak)
        
        # Maskeyi binary hale getir
        mask = (mask > 0).astype(np.uint8) * 255
        
        # Maskeyi görüntü olarak kaydet
        mask_image = Image.fromarray(mask)
        buffered = io.BytesIO()
        mask_image.save(buffered, format="PNG")
        mask_base64 = base64.b64encode(buffered.getvalue()).decode("utf-8")
        
        return JSONResponse(content={"mask": f"data:image/png;base64,{mask_base64}"})
    
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@app.get("/")
async def root():
    return {"message": "SAM-ViT-Base API çalışıyor. /segment endpoint'ine görüntü yükleyin."}

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=7860)