import os
from pathlib import Path
import torch

# Model configuration - For Hugging Face, model is in the same directory
MODEL_PATH = Path(__file__).parent / "ffpp_efficientnet_best.pth"

# Device configuration
if torch.cuda.is_available():
    DEVICE = "cuda"
elif torch.backends.mps.is_available():
    DEVICE = "mps"
else:
    DEVICE = "cpu"

# Prediction threshold (0.5 works well based on your notebook testing)
PREDICTION_THRESHOLD = float(os.environ.get("PREDICTION_THRESHOLD", 0.5))

# Video processing
FRAMES_PER_CLIP = 16
IMG_SIZE = 224

# ImageNet normalization (same as training)
IMAGENET_MEAN = [0.485, 0.456, 0.406]
IMAGENET_STD = [0.229, 0.224, 0.225]

# Logging
LOG_LEVEL = os.environ.get("LOG_LEVEL", "INFO")