Upload 4 files

Dockerfile

@@ -0,0 +1,23 @@
+# Use a lightweight Python base image
+FROM python:3.11-slim
+
+# Install system libraries required by Pillow (for JPG/PNG handling)
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    libjpeg62-turbo libpng16-16 && \
+    rm -rf /var/lib/apt/lists/*
+
+# Set working directory
+WORKDIR /app
+
+# Copy and install Python dependencies
+COPY requirements.txt /app/requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the app source code
+COPY app /app/app
+
+# Expose port (Hugging Face Spaces uses 7860 by default)
+EXPOSE 7860
+
+# Start the FastAPI app
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]

app/main.py

@@ -0,0 +1,41 @@
+from fastapi import FastAPI, UploadFile, File, Form, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+from PIL import Image
+from io import BytesIO
+import base64
+
+from .processing import increase_contrast, gaussian_smooth, to_png_b64
+
+app = FastAPI(title="Surgical Planning Phase Simulator")
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # restrict later
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+@app.get("/health")
+def health():
+    return {"ok": True}
+
+@app.post("/process")
+async def process(file: UploadFile = File(...), phase: str = Form(...)):
+    if phase not in {"arterial", "venous"}:
+        raise HTTPException(status_code=400, detail="phase must be 'arterial' or 'venous'")
+    if file.content_type not in {"image/png", "image/jpeg"}:
+        raise HTTPException(status_code=400, detail="file must be PNG or JPEG")
+
+    data = await file.read()
+    try:
+        img = Image.open(BytesIO(data)).convert("RGB")
+    except Exception as e:
+        raise HTTPException(status_code=400, detail=f"invalid image: {e}")
+
+    proc = increase_contrast(img) if phase == "arterial" else gaussian_smooth(img)
+
+    orig_b64 = to_png_b64(img)
+    proc_b64 = to_png_b64(proc)
+    return JSONResponse({"original_b64": orig_b64, "processed_b64": proc_b64})

app/processing.py

@@ -0,0 +1,19 @@
+from io import BytesIO
+import base64
+from PIL import Image, ImageEnhance, ImageFilter
+
+def to_png_b64(img: Image.Image) -> str:
+    buf = BytesIO()
+    img.save(buf, format="PNG")
+    return base64.b64encode(buf.getvalue()).decode("utf-8")
+
+def increase_contrast(img: Image.Image, factor: float = 1.6) -> Image.Image:
+    # Simulate arterial phase: boost contrast (and a touch of autocontrast)
+    img = img.convert("RGB")
+    enhanced = ImageEnhance.Contrast(img).enhance(factor)
+    return enhanced
+
+def gaussian_smooth(img: Image.Image, sigma: float = 1.6) -> Image.Image:
+    # Simulate venous phase: gaussian blur
+    img = img.convert("RGB")
+    return img.filter(ImageFilter.GaussianBlur(radius=sigma))

requirements.txt

@@ -0,0 +1,4 @@
+fastapi==0.115.4
+uvicorn==0.32.0
+pillow==10.4.0
+python-multipart==0.0.9