import os
from os.path import join
import logging
import collections
from dotenv import load_dotenv

from app.settings import types
from app.utils import click_utils
from pathlib import Path

import codecs
codecs.register(lambda name: codecs.lookup('utf8') if name == 'utf8mb4' else None)

# -----------------------------------------------------------------------------
# Enun lists used for custom Click Params
# -----------------------------------------------------------------------------

LogLevelVar = click_utils.ParamVar(types.LogLevel)
MetadataVar = click_utils.ParamVar(types.Metadata)
DatasetVar = click_utils.ParamVar(types.Dataset)
DataStoreVar = click_utils.ParamVar(types.DataStore)

# Face analysis
HaarCascadeVar = click_utils.ParamVar(types.HaarCascade)
FaceDetectNetVar = click_utils.ParamVar(types.FaceDetectNet)
FaceExtractorVar = click_utils.ParamVar(types.FaceExtractor)
FaceLandmark2D_5Var = click_utils.ParamVar(types.FaceLandmark2D_5)
FaceLandmark2D_68Var = click_utils.ParamVar(types.FaceLandmark2D_68)
FaceLandmark3D_68Var = click_utils.ParamVar(types.FaceLandmark3D_68)

# Person/Body detector
BodyDetectNetVar = click_utils.ParamVar(types.BodyDetectNet)


# base path
DIR_SELF = os.path.dirname(os.path.realpath(__file__))
DIR_ROOT = Path(DIR_SELF).parent.parent.parent

# # data_store
DATA_STORE = '/data_store_hdd/'
DATA_STORE_NAS = '/data_store_nas/'
DATA_STORE_HDD = '/data_store_hdd/'
DATA_STORE_SSD = '/data_store_ssd/'
DIR_DATASETS = join(DATA_STORE,'datasets')
DIR_DATSET_NAS = join(DIR_DATASETS, 'people')
DIR_APPS = join(DATA_STORE,'apps')
DIR_APP = join(DIR_APPS,'megapixels')
DIR_MODELS = join(DIR_APP,'models')
DIR_PEOPLE = 'people'

# # Frameworks
DIR_MODELS_CAFFE = join(DIR_MODELS,'caffe')
DIR_MODELS_DARKNET = join(DIR_MODELS,'darknet')
DIR_MODELS_DARKNET_PJREDDIE = join(DIR_MODELS_DARKNET, 'pjreddie')
DIR_MODELS_PYTORCH = join(DIR_MODELS,'pytorch')
DIR_MODELS_TORCH = join(DIR_MODELS,'torch')
DIR_MODELS_MXNET = join(DIR_MODELS,'mxnet')
DIR_MODELS_KERAS = join(DIR_MODELS,'keras')
DIR_MODELS_TF = join(DIR_MODELS,'tensorflow')
DIR_MODELS_DLIB = join(DIR_MODELS,'dlib')
DIR_MODELS_DLIB_CNN = join(DIR_MODELS_DLIB, 'mmod_human_face_detector.dat')
DIR_MODELS_DLIB_5PT = join(DIR_MODELS_DLIB, 'shape_predictor_5_face_landmarks.dat')
DIR_MODELS_DLIB_68PT = join(DIR_MODELS_DLIB, 'shape_predictor_68_face_landmarks.dat')
DIR_MODELS_DLIB_FACEREC_RESNET = join(DIR_MODELS_DLIB, 'dlib_face_recognition_resnet_model_v1.dat')

DIR_FAISS = join(DIR_APP, 'faiss')
DIR_FAISS_INDEXES = join(DIR_FAISS, 'indexes')
DIR_FAISS_METADATA = join(DIR_FAISS, 'metadata')
DIR_FAISS_RECIPES = join(DIR_FAISS, 'recipes')

# Test images
DIR_TEST_IMAGES = join(DIR_APP, 'test', 'images')

# -----------------------------------------------------------------------------
# .env config for keys
# -----------------------------------------------------------------------------
FP_KNOWLEDGE_GRAPH_ENV = join(DIR_ROOT, 'env/google_knowledge_graph_api.env')
# DIR_DOTENV = join(DIR_APP, '.env')
load_dotenv() # dotenv_path=DIR_DOTENV)

# -----------------------------------------------------------------------------
# Drawing, GUI settings
# -----------------------------------------------------------------------------
DIR_ASSETS = join(DIR_APP, 'assets')
FP_FONT = join(DIR_ASSETS, 'font')

# -----------------------------------------------------------------------------
# click chair settings
# -----------------------------------------------------------------------------
DIR_COMMANDS_PROC = 'commands/processor'
DIR_COMMANDS_VIZ = 'commands/visualize'
DIR_COMMANDS_ADMIN = 'commands/admin'
DIR_COMMANDS_DATASETS = 'commands/datasets'
DIR_COMMANDS_FAISS = 'commands/faiss'
DIR_COMMANDS_MISC  = 'commands/misc'
DIR_COMMANDS_SITE = 'commands/site'
DIR_COMMANDS_DEMO = 'commands/demo'
DIR_COMMANDS_MSC = 'commands/msc'

# -----------------------------------------------------------------------------
# Filesystem settings
# hash trees enforce a maximum number of directories per directory
# -----------------------------------------------------------------------------
ZERO_PADDING = 6  # padding for enumerated image filenames
#FRAME_NAME_ZERO_PADDING = 6  # is this active??
CKPT_ZERO_PADDING = 9
HASH_TREE_DEPTH = 3
HASH_BRANCH_SIZE = 3

DLIB_FACEREC_JITTERS = 5  # number of face recognition jitters
#DLIB_FACEREC_PADDING = 0.25  # default dlib
FACEREC_PADDING = 0.3  # VGG FACE2 recommended
DEFAULT_SIZE_FACE_DETECT = (480,480)
DEFAULT_JITTER_AMT = 0.015  # used for OpenCV DNN face detector with VGG2 face feature extractor
DEFAULT_NUM_JITTERS = 4  # used for smothing the facial feature extraction
DEFAULT_FACE_PADDING_VGG_FACE2 = 0.3
POSE_MINMAX_YAW = (-25,25)
POSE_MINMAX_ROLL = (-15,15)
POSE_MINMAX_PITCH = (-10,10)

POSE_MINMAX_YAW = (-40,40)
POSE_MINMAX_ROLL = (-35,35)
POSE_MINMAX_PITCH = (-25,25)

# -----------------------------------------------------------------------------
# Pandas data
# -----------------------------------------------------------------------------

FILE_RECORD_DTYPES = {'fn':str, 'subdir': str}

# -----------------------------------------------------------------------------
# Logging options exposed for custom click Params
# -----------------------------------------------------------------------------
LOGGER_NAME = 'app'
LOGLEVELS = {
  types.LogLevel.DEBUG: logging.DEBUG,
  types.LogLevel.INFO: logging.INFO,
  types.LogLevel.WARN: logging.WARN,
  types.LogLevel.ERROR: logging.ERROR,
  types.LogLevel.CRITICAL: logging.CRITICAL
}
LOGLEVEL_OPT_DEFAULT = types.LogLevel.DEBUG.name
#LOGFILE_FORMAT = "%(asctime)s: %(levelname)s: %(message)s"
#LOGFILE_FORMAT = "%(levelname)s:%(name)s: %(message)s"
#LOGFILE_FORMAT = "%(levelname)s: %(message)s"
#LOGFILE_FORMAT = "%(filename)s:%(lineno)s  %(funcName)s()  %(message)s"
# colored logs
"""
black, red, green, yellow, blue, purple, cyan and white.
{color}, fg_{color}, bg_{color}: Foreground and background colors.
bold, bold_{color}, fg_bold_{color}, bg_bold_{color}: Bold/bright colors.
reset: Clear all formatting (both foreground and background colors).
"""
LOGFILE_FORMAT = "%(log_color)s%(levelname)-8s%(reset)s %(cyan)s%(filename)s:%(lineno)s:%(bold_cyan)s%(funcName)s() %(reset)s%(message)s"

# -----------------------------------------------------------------------------
# S3 storage
# -----------------------------------------------------------------------------
S3_ROOT_URL = 's3://megapixels/v1/'
S3_MEDIA_URL = join(S3_ROOT_URL, 'media')
S3_METADATA_URL = join(S3_ROOT_URL, 'metadata')
S3_HTTP_URL = 'https://megapixels.nyc3.digitaloceanspaces.com/v1/'
S3_HTTP_MEDIA_URL = join(S3_HTTP_URL, 'media')
S3_HTTP_METADATA_URL = join(S3_HTTP_URL, 'metadata')

# -----------------------------------------------------------------------------
# Static site generator
# -----------------------------------------------------------------------------
S3_SITE_PATH = "v1/site"
S3_DATASETS_PATH = "v1" # datasets is already in the filename
DIR_SITE_PUBLIC = "../site/public"
DIR_SITE_CONTENT = "../site/content/pages"
DIR_SITE_TEMPLATES = "../site/templates"
DIR_SITE_INCLUDES = "../site/includes"
DIR_SITE_USER_CONTENT = "../site/public/user_content"
DIR_SITE_DATASETS = "../site/datasets/"
DIR_SITE_FINAL_CITATIONS = "../site/datasets/final/"
GOOGLE_ACCOUNT_CREDS_PATH = os.path.join("../", os.getenv("GOOGLE_ACCOUNT_CREDS_PATH"))

# -----------------------------------------------------------------------------
# Celery
# -----------------------------------------------------------------------------
CELERY_BROKER_URL = 'redis://localhost:6379/0'
CELERY_RESULT_BACKEND = 'redis://localhost:6379/0'

# -----------------------------------------------------------------------------
# Build settings
# -----------------------------------------------------------------------------
BUILD_RESEARCH = False