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# config.py | |
""" | |
File: config.py | |
Description: Configuration file for the AI-Driven Multimodal Emotional State Analysis application. | |
License: MIT License | |
""" | |
import toml | |
from typing import Dict | |
from types import SimpleNamespace | |
def flatten_dict(prefix: str, d: Dict) -> Dict: | |
""" | |
Recursively flattens a nested dictionary, concatenating keys with underscores. | |
""" | |
result = {} | |
for k, v in d.items(): | |
if isinstance(v, dict): | |
result.update(flatten_dict(f"{prefix}{k}_", v)) | |
else: | |
result[f"{prefix}{k}"] = v | |
return result | |
# Load configuration from 'config.toml' if it exists | |
try: | |
config = toml.load("config.toml") | |
except FileNotFoundError: | |
config = {} | |
print("Warning: 'config.toml' not found. Using default configuration.") | |
# Flatten the configuration dictionary | |
config_data_dict = flatten_dict("", config) | |
# Convert the dictionary to a SimpleNamespace for easy attribute access | |
config_data = SimpleNamespace(**config_data_dict) | |
# Define emotion labels | |
DICT_EMO = { | |
0: "Neutral", | |
1: "Happiness", | |
2: "Sadness", | |
3: "Surprise", | |
4: "Fear", | |
5: "Disgust", | |
6: "Anger", | |
} | |
# Define colors for plotting or UI elements | |
COLORS = { | |
0: 'blue', | |
1: 'orange', | |
2: 'green', | |
3: 'red', | |
4: 'purple', | |
5: 'brown', | |
6: 'pink' | |
} | |