import os
import sys

import torch
import torch.nn as nn
from torch.nn import functional as F

sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/..')
from models.convnext import ConvNeXt


class DepthEstimation(nn.Module):
    def __init__(self, device='cuda'):
        super().__init__()

        self.convnext = ConvNeXt()
        self.flatten = nn.Flatten()
        self.decoder = ConvNeXt(reversed=True)


    def forward(self, x: torch.Tensor) -> torch.Tensor:
        x = self.convnext(x)
        # x = self.flatten(x)
        x = self.decoder(x)
        
        return x