Limited Dataset Size: A small dataset of "before" and "after" cleaning images might not be sufficient to train a robust model that generalizes well to unseen scenarios.
Data Quality: Images with poor lighting, clutter, or furniture movement can introduce noise and make it difficult for the model to distinguish between clean and dirty states.
Training Challenges: Training image analysis models can require significant computational resources (GPUs are recommended) which may not be readily available.