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app.py

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+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
+
+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."}