Add FastAPI Docker app and model files

Dockerfile

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+FROM python:3.10-slim
+
+# Prevents Python from writing pyc files
+ENV PYTHONDONTWRITEBYTECODE=1
+ENV PYTHONUNBUFFERED=1
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+# Set working directory
+WORKDIR /app
+
+# Copy requirements first (better caching)
+COPY requirements.txt .
+
+# Install Python dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy app files
+COPY app.py .
+COPY mobilenetv3_gender_weights.pth .
+COPY metadata.json .
+
+# Expose HF-required port
+EXPOSE 7860
+
+# Start FastAPI server
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+import torch
+import torch.nn as nn
+import timm
+import json
+import io
+
+from fastapi import FastAPI, File, UploadFile
+from PIL import Image
+from torchvision import transforms
+
+# --------------------------------------------------
+# Load model ONCE at startup
+# --------------------------------------------------
+
+DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+WEIGHTS_PATH = "mobilenetv3_gender_weights.pth"
+METADATA_PATH = "metadata.json"
+
+# Load metadata
+with open(METADATA_PATH, "r") as f:
+    metadata = json.load(f)
+
+# Build model
+model = timm.create_model(
+    metadata["model_name"],
+    pretrained=False,
+    num_classes=metadata["num_classes"]
+)
+
+# Rebuild classifier
+config = metadata["classifier_config"]
+model.classifier = nn.Sequential(
+    nn.Linear(config["in_features"], config["hidden_dim"]),
+    nn.ReLU(),
+    nn.Dropout(config["dropout"]),
+    nn.Linear(config["hidden_dim"], metadata["num_classes"])
+)
+
+# Load weights safely
+state_dict = torch.load(WEIGHTS_PATH, map_location=DEVICE, weights_only=True)
+model.load_state_dict(state_dict)
+model.to(DEVICE)
+model.eval()
+
+# Image preprocessing
+transform = transforms.Compose([
+    transforms.Resize((224, 224)),
+    transforms.ToTensor(),
+    transforms.Normalize(
+        mean=[0.485, 0.456, 0.406],
+        std=[0.229, 0.224, 0.225]
+    )
+])
+
+# --------------------------------------------------
+# FastAPI app
+# --------------------------------------------------
+
+app = FastAPI(
+    title="Gender Classification API",
+    description="MobileNetV3 Gender Prediction",
+    version="1.0"
+)
+
+@app.get("/")
+def root():
+    return {
+        "message": "Gender Classification API is running 🚀",
+        "model": metadata["model_name"],
+        "classes": metadata["class_names"]
+    }
+
+@app.post("/predict")
+async def predict(file: UploadFile = File(...)):
+    image_bytes = await file.read()
+    image = Image.open(io.BytesIO(image_bytes)).convert("RGB")
+
+    image_tensor = transform(image).unsqueeze(0).to(DEVICE)
+
+    with torch.no_grad():
+        outputs = model(image_tensor)
+        probs = torch.softmax(outputs, dim=1)
+
+    confidence, predicted = torch.max(probs, 1)
+
+    return {
+        "predicted_class": metadata["class_names"][predicted.item()],
+        "confidence": round(confidence.item() * 100, 2),
+        "probabilities": {
+            metadata["class_names"][0]: round(probs[0][0].item() * 100, 2),
+            metadata["class_names"][1]: round(probs[0][1].item() * 100, 2),
+        }
+    }

metadata.json

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+{
+    "model_name": "mobilenetv3_large_100",
+    "num_classes": 2,
+    "class_names": [
+        "Female",
+        "Male"
+    ],
+    "accuracy": 0.9285714285714286,
+    "confusion_matrix": [
+        [
+            104,
+            7
+        ],
+        [
+            9,
+            104
+        ]
+    ],
+    "epochs_trained": 10,
+    "loss_history": [
+        0.6070853605352599,
+        0.4011639428549799,
+        0.3184526763085661,
+        0.27616333987178476,
+        0.24627566992722708,
+        0.21110220202084246,
+        0.13941147615169658,
+        0.1258032820348082,
+        0.13784673257634558,
+        0.12205909436632847
+    ],
+    "classifier_config": {
+        "in_features": 1280,
+        "hidden_dim": 128,
+        "dropout": 0.4
+    }
+}

mobilenetv3_gender_weights.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c039486323ad7c626f511d63e854cbc632804070448a721930016608b934af1b
+size 17676312

requirements.txt

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+fastapi
+uvicorn
+torch
+torchvision
+timm
+pillow