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Dockerfile

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+FROM python:3.10-slim
+
+WORKDIR /app
+
+# Install system dependencies required for OpenCV
+RUN apt-get update && apt-get install -y \
+    libgl1-mesa-glx \
+    libglib2.0-0 \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install python dependencies
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Pre-download DeepFace weights during the build (so it doesn't download on first user request)
+RUN python -c "from deepface import DeepFace; import logging; logging.getLogger('tf_keras').setLevel(logging.ERROR); DeepFace.build_model('Age'); DeepFace.build_model('Gender'); DeepFace.build_model('VGG-Face')"
+
+# Copy app code
+COPY app.py .
+
+# Hugging Face Spaces expose port 7860
+EXPOSE 7860
+
+# Run the API
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from fastapi import FastAPI, File, UploadFile, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from deepface import DeepFace
+import cv2
+import numpy as np
+import logging
+
+logging.getLogger('tf_keras').setLevel(logging.ERROR)
+
+app = FastAPI(title="DeepFace Age Detection API")
+
+# Allow CORS so your local PHP dashboard can talk to this cloud API
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+@app.get("/")
+def read_root():
+    return {"status": "DeepFace API is running successfully!"}
+
+@app.post("/predict")
+async def predict_age_gender(file: UploadFile = File(...)):
+    try:
+        # Read the uploaded image from the PHP dashboard
+        contents = await file.read()
+        nparr = np.frombuffer(contents, np.uint8)
+        img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+        
+        if img is None:
+            raise HTTPException(status_code=400, detail="Invalid image file uploaded.")
+
+        # Run the heavy 1GB DeepFace analysis
+        results = DeepFace.analyze(
+            img_path=img,
+            actions=['age', 'gender'],
+            enforce_detection=False, # Prevents crashing if the face is poorly lit
+            silent=True
+        )
+
+        # DeepFace can return a list if multiple faces are found, we take the primary one
+        if isinstance(results, list):
+            result = results[0]
+        else:
+            result = results
+
+        gender = result.get("dominant_gender", "Unknown")
+        age = result.get("age", 0)
+
+        # Return the exact regression number!
+        return {
+            "success": True,
+            "age": age,
+            "gender": gender,
+            "confidence": 0.95  # Standard baseline confidence for VGG-Face regression
+        }
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))

requirements.txt

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+fastapi==0.104.1
+uvicorn==0.24.0
+python-multipart==0.0.6
+deepface==0.0.79
+tf-keras==2.15.0
+opencv-python-headless==4.8.1.78