import gc
import torch
from pathlib import Path


class SatelliteSRRouter:

    def __init__(self, device=None):

        from models.hatsat.hatsat_inference import HATSATInference
        from models.esrgan.esrgan_inference import ESRGANInference
        from models.sen2sr.sen2sr_inference import Sen2SRInference

        self.HATSATInference = HATSATInference
        self.ESRGANInference = ESRGANInference
        self.Sen2SRInference = Sen2SRInference

        if device is None:
            device = "cuda" if torch.cuda.is_available() else "cpu"

        self.device = device

        # Lazy loading:
        # Only the selected model is loaded.
        self.hatsat = None
        self.esrgan = None
        self.sen2sr = None

        print("=" * 55)
        print("SATELLITE SR ROUTER")
        print("=" * 55)
        print("Device:", self.device)
        print("Router initialized.")
        print("Models will be loaded only when selected.")

    def _clear_gpu(self):

        gc.collect()

        if torch.cuda.is_available():
            torch.cuda.empty_cache()
            torch.cuda.ipc_collect()

    def _unload_hatsat(self):

        if self.hatsat is not None:

            print("Unloading HATSAT...")

            try:
                if hasattr(self.hatsat, "model"):
                    self.hatsat.model.cpu()
            except Exception:
                pass

            self.hatsat = None

            self._clear_gpu()

    def _unload_esrgan(self):

        if self.esrgan is not None:

            print("Unloading ESRGAN...")

            try:
                if hasattr(self.esrgan, "model"):
                    self.esrgan.model.cpu()
            except Exception:
                pass

            self.esrgan = None

            self._clear_gpu()

    def _unload_sen2sr(self):

        if self.sen2sr is not None:

            print("Unloading Sen2SR...")

            try:
                if hasattr(self.sen2sr, "model") and hasattr(self.sen2sr.model, "model"):
                    self.sen2sr.model.model.cpu()
            except Exception:
                pass

            self.sen2sr = None

            self._clear_gpu()

    def _load_hatsat(self):

        if self.hatsat is None:

            print("Loading HATSAT...")

            self.hatsat = self.HATSATInference(
                device=self.device
            )

            print("HATSAT loaded successfully.")

    def _load_esrgan(self):

        if self.esrgan is None:

            print("Loading ESRGAN...")

            checkpoint = (
                Path(__file__).resolve().parent
                / "weights"
                / "esrgan"
                / "RRDB_ESRGAN_x4.pth"
            )

            self.esrgan = self.ESRGANInference(
                checkpoint_path=checkpoint,
                device=self.device
            )

            print("ESRGAN loaded successfully.")

    def _load_sen2sr(self):

        if self.sen2sr is None:

            print("Loading Sen2SR...")

            self.sen2sr = self.Sen2SRInference(
                device=self.device
            )

            print("Sen2SR loaded successfully.")

    def available_models(self):

        return {
            "hatsat": {
                "name": "HATSAT",
                "description": "Satellite-oriented super-resolution model",
                "scale": 4
            },

            "esrgan": {
                "name": "ESRGAN",
                "description": "General-purpose super-resolution baseline",
                "scale": 4
            },

            "sen2sr": {
                "name": "Sen2SR",
                "description": "WEO-SAS Sentinel-2 CNN super-resolution (HuggingFace)",
                "scale": 4
            }
        }

    def predict(self, image, model_name="hatsat"):

        if image is None:
            raise ValueError("Please upload an image.")

        model_name = str(model_name).lower().strip()

        print("=" * 55)
        print("ROUTER INFERENCE")
        print("Selected model:", model_name)
        print("=" * 55)

        # ==========================================
        # HATSAT
        # ==========================================

        if model_name == "hatsat":

            # Free GPU memory used by other models
            self._unload_esrgan()
            self._unload_sen2sr()

            # Load HATSAT only when required
            self._load_hatsat()

            print("Running HATSAT...")

            result = self.hatsat.predict(image)

            print("HATSAT inference complete.")

            return result

        # ==========================================
        # ESRGAN
        # ==========================================

        elif model_name == "esrgan":

            # Free GPU memory used by HATSAT and Sen2SR
            self._unload_hatsat()
            self._unload_sen2sr()

            # Load ESRGAN only when required
            self._load_esrgan()

            print("Running ESRGAN...")

            result = self.esrgan.predict(image)

            print("ESRGAN inference complete.")

            return result

        # ==========================================
        # SEN2SR
        # ==========================================

        elif model_name == "sen2sr":

            # Free GPU memory used by other models
            self._unload_hatsat()
            self._unload_esrgan()

            # Load Sen2SR only when required
            self._load_sen2sr()

            print("Running Sen2SR...")

            result = self.sen2sr.predict(image)

            print("Sen2SR inference complete.")

            return result

        else:

            raise ValueError(
                f"Unknown model '{model_name}'. "
                f"Choose 'hatsat', 'esrgan', or 'sen2sr'."
            )