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config.py
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'''
Copyright 2023
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
'''
import os
basedir = os.path.abspath(os.path.dirname(__file__))
class Config(object):
LOAD_TESTING = False
DEBUGGING = True if os.environ.get('DEBUGGING').lower()=='true' else False
MAINTENANCE = False
INITIAL_SETUP = False
DISABLE_RESTORE = False
KILL_FILEHANDLER = False
VERSION = 46
HOST_IP = os.environ.get('HOST_IP')
REDIS_IP = os.environ.get('REDIS_IP')
KEY_NAME = os.environ.get('KEY_NAME')
WORKER_NAME = 'celery@'+os.environ.get('WORKER_NAME')
QUEUE = os.environ.get('QUEUE')
BUCKET = os.environ.get('BUCKET')
SKIP_ID = -117
SKY_CONST = 0.33
DETECTOR = 'MDv5b'
VAT=1.15
ADMIN_USERS = ['Admin','WildEye','Dashboard','Wild Parks','Nicholas','Marguerite','API']
AWS_S3_UPLOAD_ACCESS_KEY_ID = os.environ.get('AWS_S3_UPLOAD_ACCESS_KEY_ID')
AWS_S3_UPLOAD_SECRET_ACCESS_KEY = os.environ.get('AWS_S3_UPLOAD_SECRET_ACCESS_KEY')
MONKEY_PATCH = os.environ.get('MONKEY_PATCH')
INITIALISE_IBS = os.environ.get('INITIALISE_IBS')
AWS_ACCOUNT_ID = str(os.environ.get('AWS_ACCOUNT_ID'))
DETECTOR_THRESHOLDS = {
'MDv4': 0.8,
'MDv5a': 0.2,
'MDv5b': 0.1,
'error': 1.0,
'golden': 0.9,
'user': 0,
'api': 0
}
DISALLOWED_USERNAMES = ['admin','dashboard','api']
# SQLAlchemy Config
SECRET_KEY = os.environ.get('SECRET_KEY')
SQLALCHEMY_DATABASE_SERVER = os.environ.get('DATABASE_SERVER')
SQLALCHEMY_DATABASE_NAME = os.environ.get('DATABASE_NAME')
SQLALCHEMY_DATABASE_URI = SQLALCHEMY_DATABASE_SERVER+"/"+SQLALCHEMY_DATABASE_NAME
SQLALCHEMY_TRACK_MODIFICATIONS = False
#Postgres Config
WBIA_DB_NAME = os.environ.get('WBIA_DB_NAME')
WBIA_DB_SERVER = os.environ.get('WBIA_DB_SERVER')
WBIA_DB_URI = WBIA_DB_SERVER+"/"+WBIA_DB_NAME
WBIA_DIR = os.environ.get('WBIA_DIR')
# Email Config
MAIL_SERVER = 'smtp.gmail.com'
SSL_MAIL_PORT = 465
MAIL_PORT = 587
MAIL_USE_TLS = True
MAIL_USE_SSL = False
MAIL_USERNAME = os.environ.get('MAIL_USERNAME')
MAIL_PASSWORD = os.environ.get('MAIL_PASSWORD')
ADMINS = [os.environ.get('MAIL_USERNAME')]
MONITORED_EMAIL_ADDRESS = os.environ.get('MONITORED_EMAIL_ADDRESS')
AWS_REGION = os.environ.get('REGION_NAME')
TOKEN = os.environ.get('TOKEN')
IAM_ADMIN_GROUP = os.environ.get('IAM_ADMIN_GROUP')
#Worker config
PARALLEL_AMI = os.environ.get('PARALLEL_AMI')
LLAVA_AMI = os.environ.get('LLAVA_AMI')
BRANCH = os.environ.get('BRANCH')
GPU_INSTANCE_TYPES = ['g4dn.xlarge'] #['p3.2xlarge', 'g4dn.xlarge', 'g3s.xlarge']
XL_GPU_INSTANCE_TYPES = ['g5.12xlarge']
CPU_INSTANCE_TYPES = ['t2.xlarge','t3a.xlarge'] #['t2.medium', 't3a.medium']
PIPELINE_INSTANCE_TYPES = ['t2.xlarge','t3a.xlarge']
INSTANCE_RATES = {
'celery': {'p3.2xlarge': 11668, 'g4dn.xlarge': 4128, 'g3s.xlarge': 2600}, #measured
'classification': {'p3.2xlarge': 11668, 'g4dn.xlarge': 4128, 'g3s.xlarge': 2600}, #estimated
'parallel': {'t2.xlarge': 1000, 't3a.xlarge': 1000}, #estimated
'parallel_2': {'t2.xlarge': 1000, 't3a.xlarge': 1000}, #estimated
'default': {'t2.xlarge': 1000, 't3a.xlarge': 1000}, #estimated
'statistics': {'t2.xlarge': 1000, 't3a.xlarge': 1000}, #estimated
'pipeline': {'t2.xlarge': 1000, 't3a.xlarge': 1000}, #estimated
'llava': {'g5.12xlarge': 3130}, #measured. 20 min startup
'similarity': {'g4dn.xlarge': 4128},
'utility': {'t2.xlarge': 1000, 't3a.xlarge': 1000},
'utility_2': {'t2.xlarge': 1000, 't3a.xlarge': 1000}
} #Images per hour
SG_ID = os.environ.get('SG_ID')
PUBLIC_SUBNET_ID = os.environ.get('PUBLIC_SUBNET_ID')
PRIVATE_SUBNET_ID = os.environ.get('PRIVATE_SUBNET_ID')
MAX_INFER = 25
MAX_CLASSIFICATION = 18
MAX_PARALLEL = 25
MAX_PARALLEL_2 = 8
MAX_DEFAULT = 8
MAX_STATS = 4
MAX_PIPELINE = 8
MAX_LLAVA = 5
MAX_SIMILARITY = 5
MAX_UTILITY = 15
MAX_UTILITY_2 = 50
DNS = os.environ.get('DNS')
# Species Classification Config
CLUSTER_DET_COUNT = {'trails': 1, 'plains': 5, 'waterhole': 5, 'baited': 1}
DET_RATIO = {'trails': 0.5, 'plains': 0.25, 'waterhole': 0.25, 'baited': 0.5}
CLASSIFICATION_DET_AREA = {'trails': 0.0025, 'plains': 0.002, 'waterhole': 0.002, 'baited': 0.0025}
MIN_CLASSIFICATION_RATIO = {'trails': 0.2, 'plains': 0.1, 'waterhole': 0.1, 'baited': 0.2} #the minimum ratio of detection classifications for a classification to be considered
# maximum number of detections displayed per cluster during annotation - prevents long load times
MAX_DETS_PER_CLUSTER = 500
# maximum length of a cluster in minutes
MAX_CLUSTER_MINUTES = 15
# the time delta between clusters for them to be considered related (in seconds)
# this should probably be kept less than the MAX_CLUSTER_MINUTES
RELATED_CLUSTER_TIME = 600
# Task and survey statuses
TASK_READY_STATUSES = ['ready','success','successinitial','stopped']
SURVEY_READY_STATUSES = ['ready','failed','stopped','cancelled','restoring files']
# Detection statuses
DET_IGNORE_STATUSES = ['deleted','hidden','masked']
# Hotkey info
NUMBER_OF_HOTKEYS = 39
EMPTY_HOTKEY_ID= -967
# Mask Area Config
MIN_MASK_AREA = 0.001
# area for masking small dets
SMALL_DET_AREA = 0.0025
# Static Detection Config
STATIC_MATCHCOUNT = {'trails': 5, 'plains': 10, 'waterhole': 10, 'baited': 10}
STATIC_PERCENTAGE = {'trails': 0.15, 'plains': 0.3, 'waterhole': 0.3, 'baited': 0.3}
STATIC_IOU5 = {'trails': 0.6, 'plains': 0.8, 'waterhole': 0.8, 'baited': 0.8}
STATIC_IOU10 = {'trails': 0.7, 'plains': 0.85, 'waterhole': 0.85, 'baited': 0.85}
STATIC_IOU30 = {'trails': 0.85, 'plains': 0.9, 'waterhole': 0.9, 'baited': 0.9}
STATIC_IOU50 = {'trails': 0.9, 'plains': 0.95, 'waterhole': 0.95, 'baited': 0.95}
STATIC_IOU90 = {'trails': 0.95, 'plains': 0.98, 'waterhole': 0.98, 'baited': 0.98}
# Flank Config (for individual ID)
FLANK_TEXT = { # Database to flank text
'L': 'left',
'R': 'right',
'A': 'ambiguous',
None: 'none'
}
FLANK_DB = { # Flank text to database
'left': 'L',
'right': 'R',
'ambiguous': 'A',
'none': None
}
# Individual ID Config
ID_QUANTILES = [90, 80, 60, 30, 0]
# Zip file folders
SURVEY_ZIP_FOLDER = '_survey_zip_files_'
# Glacier Restore
if DEBUGGING:
RESTORE_TIME = 43200 # 12 hours
else:
RESTORE_TIME= 172800 # 48 hours
RESTORE_COOLDOWN = 14 # 14 days
ID_RESTORE_DAYS=30
DOWNLOAD_RESTORE_DAYS=7
EDIT_RESTORE_DAYS=7
EMPTY_RESTORE_DAYS=7
if DEBUGGING:
RESTORE_TIER = 'Standard'
else:
RESTORE_TIER = 'Bulk'
# Lambda
RDS_HOST = SQLALCHEMY_DATABASE_SERVER.split('@')[1]
RDS_USER = SQLALCHEMY_DATABASE_SERVER.split('@')[0].split('//')[1].split(':')[0]
RDS_PASSWORD = SQLALCHEMY_DATABASE_SERVER.split('@')[0].split(':')[2]
if DEBUGGING:
IMAGE_IMPORT_LAMBDA = 'traptaggerImportImageDev'
VIDEO_IMPORT_LAMBDA = 'traptaggerImportVideoDev'
VIDEO_EXTRACT_LAMBDA = 'traptaggerExtractVideoDev'
SQS_QUEUE = 'traptaggerLambdaDLQDev'
else:
IMAGE_IMPORT_LAMBDA = 'traptaggerImportImage'
VIDEO_IMPORT_LAMBDA = 'traptaggerImportVideo'
VIDEO_EXTRACT_LAMBDA = 'traptaggerExtractVideo'
SQS_QUEUE = 'traptaggerLambdaDLQ'
FFMPEG_LAYER = 'ffmpeg_layer:5'
FFPROBE_LAYER = 'ffprobe_layer:6'
OPENCV_LAYER = 'opencv_layer:2'
LAMBDA_SUBNET_ID = os.environ.get('LAMBDA_SUBNET_ID')
LAMBDA_ROLE = 'TrapTaggerImportLambdaRole'
LAMBDA_DIR = {
IMAGE_IMPORT_LAMBDA: 'importImage',
VIDEO_IMPORT_LAMBDA: 'importVideo',
VIDEO_EXTRACT_LAMBDA: 'extractVideo'
}
# LAMBDA CONFIG
LAMBDA_FUNCTIONS = {
IMAGE_IMPORT_LAMBDA: {
'FunctionName': IMAGE_IMPORT_LAMBDA,
'Handler': 'lambda_function.lambda_handler',
'Role': 'arn:aws:iam::'+AWS_ACCOUNT_ID+':role/'+LAMBDA_ROLE,
'Runtime': 'python3.12',
'Timeout': 900,
'MemorySize': 256,
'EphemeralStorage': {
'Size': 512
},
'Layers': [],
'VpcConfig': {
'SubnetIds': [LAMBDA_SUBNET_ID],
'SecurityGroupIds': [SG_ID]
},
'DeadLetterConfig': {
'TargetArn': 'arn:aws:sqs:'+AWS_REGION+':'+AWS_ACCOUNT_ID+':'+SQS_QUEUE
},
'DestinationConfig': {
'OnSuccess': {
'Destination': 'arn:aws:sqs:'+AWS_REGION+':'+AWS_ACCOUNT_ID+':'+SQS_QUEUE
}
}
},
VIDEO_IMPORT_LAMBDA: {
'FunctionName': VIDEO_IMPORT_LAMBDA,
'Handler': 'lambda_function.lambda_handler',
'Role': 'arn:aws:iam::'+AWS_ACCOUNT_ID+':role/'+LAMBDA_ROLE,
'Runtime': 'python3.9',
'Timeout': 900,
'MemorySize': 1024,
'EphemeralStorage': {
'Size': 640
},
'Layers': [
'arn:aws:lambda:'+AWS_REGION+':'+AWS_ACCOUNT_ID+':layer:'+FFMPEG_LAYER,
'arn:aws:lambda:'+AWS_REGION+':'+AWS_ACCOUNT_ID+':layer:'+FFPROBE_LAYER
],
'VpcConfig': {
'SubnetIds': [LAMBDA_SUBNET_ID],
'SecurityGroupIds': [SG_ID]
},
'DeadLetterConfig': {
'TargetArn': 'arn:aws:sqs:'+AWS_REGION+':'+AWS_ACCOUNT_ID+':'+SQS_QUEUE
},
'DestinationConfig': {
'OnSuccess': {
'Destination': 'arn:aws:sqs:'+AWS_REGION+':'+AWS_ACCOUNT_ID+':'+SQS_QUEUE
}
}
},
VIDEO_EXTRACT_LAMBDA: {
'FunctionName': VIDEO_EXTRACT_LAMBDA,
'Handler': 'lambda_function.lambda_handler',
'Role': 'arn:aws:iam::'+AWS_ACCOUNT_ID+':role/'+LAMBDA_ROLE,
'Runtime': 'python3.9',
'Timeout': 900,
'MemorySize': 512,
'EphemeralStorage': {
'Size': 512
},
'Layers': [
'arn:aws:lambda:'+AWS_REGION+':'+AWS_ACCOUNT_ID+':layer:'+OPENCV_LAYER
],
'VpcConfig': {
'SubnetIds': [LAMBDA_SUBNET_ID],
'SecurityGroupIds': [SG_ID]
},
'DeadLetterConfig': {
'TargetArn': 'arn:aws:sqs:'+AWS_REGION+':'+AWS_ACCOUNT_ID+':'+SQS_QUEUE
},
'DestinationConfig': {
'OnSuccess': {
'Destination': 'arn:aws:sqs:'+AWS_REGION+':'+AWS_ACCOUNT_ID+':'+SQS_QUEUE
}
}
}
}
LAMBDA_LAYERS = {
FFMPEG_LAYER: {
'LayerName': 'ffmpeg_layer',
'CompatibleRuntimes': ['python3.9', 'python3.12'],
'CompatibleArchitectures': ['x86_64'],
},
FFPROBE_LAYER: {
'LayerName': 'ffprobe_layer',
'CompatibleRuntimes': ['python3.9', 'python3.12'],
'CompatibleArchitectures': ['x86_64'],
},
OPENCV_LAYER: {
'LayerName': 'opencv_layer',
'CompatibleRuntimes': ['python3.9'],
'CompatibleArchitectures': ['x86_64'],
}
}
# Result File Type
RESULT_TYPES = {
'csv': 'csv',
'excel': 'xlsx',
'coco': 'json',
'export': 'zip'
}
# Time in seconds allowed for a worker to finish setting up beforte being checked for idleness
SETUP_PERIOD = {
'celery': '300',
'classification': '300',
'parallel': '300',
'parallel_2': '300',
'default': '300',
'statistics': '300',
'pipeline': '300',
'llava': '1500',
'similarity': '300',
'utility': '300',
'utility_2': '300'
}
#Aurora DB stuff
MAX_AURORA = 64
MIN_AURORA = 8
DB_CLUSTER_NAME= os.environ.get('DB_CLUSTER_NAME')
# How many multiples of 5 seconds a worker is checked for idleness
IDLE_MULTIPLIER = {
'celery': 12,
'classification': 12,
'parallel': 24,
'parallel_2': 12,
'default': 12,
'statistics': 12,
'pipeline': 12,
'llava': 12,
'similarity': 12,
'utility': 12,
'utility_2': 12
}
# Celery Worker concurrency
CONCURRENCY = {
'parallel': 1,
'parallel_2': 1,
'default': 1,
'statistics': 1,
'pipeline': 1,
'llava': 1,
'similarity': 1,
'utility': 1,
'utility_2': 1
}
# Queue config
QUEUES = {
'parallel': {
'type': 'CPU',
'ami': PARALLEL_AMI,
'instances': CPU_INSTANCE_TYPES,
'max_instances': MAX_PARALLEL,
'launch_delay': 180,
'rate': 4, #2695
'queue_type': 'rate',
'repo': os.environ.get('MAIN_GIT_REPO'),
'branch': BRANCH,
'user_data':
'bash /home/ubuntu/TrapTagger/launch.sh ' +
'parallel_worker_{}' + ' ' +
'parallel' + " '" +
HOST_IP + "' '" +
SQLALCHEMY_DATABASE_NAME + "' '" +
HOST_IP + "' '" +
DNS + "' '" +
SQLALCHEMY_DATABASE_SERVER + "' '" +
os.environ.get('AWS_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_SECRET_ACCESS_KEY') + "' '" +
AWS_REGION + "' '" +
SECRET_KEY + "' '" +
MAIL_USERNAME + "' '" +
MAIL_PASSWORD + "' '" +
BRANCH + "' '" +
SG_ID + "' '" +
PUBLIC_SUBNET_ID + "' '" +
TOKEN + "' '" +
PARALLEL_AMI + "' '" +
KEY_NAME + "' '" +
SETUP_PERIOD['parallel'] + "' '" +
'IDLE_MULTIPLIER' + "' '" +
os.environ.get('MAIN_GIT_REPO') + "' '" +
str(CONCURRENCY['parallel']) + "' '" +
MONITORED_EMAIL_ADDRESS + "' '" +
BUCKET + "' '" +
IAM_ADMIN_GROUP + "' '" +
PRIVATE_SUBNET_ID + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_SECRET_ACCESS_KEY') + "' '" +
os.environ.get('WBIA_DB_NAME') + "' '" +
os.environ.get('WBIA_DB_SERVER') + "' '" +
os.environ.get('WBIA_DIR') + "' '" +
os.environ.get('DEBUGGING') + "'" +
' -l info'
},
'parallel_2': {
'type': 'CPU',
'ami': PARALLEL_AMI,
'instances': CPU_INSTANCE_TYPES,
'max_instances': MAX_PARALLEL_2,
'launch_delay': 180,
'rate': 4, #2695
'queue_type': 'rate',
'repo': os.environ.get('MAIN_GIT_REPO'),
'branch': BRANCH,
'user_data':
'bash /home/ubuntu/TrapTagger/launch.sh ' +
'parallel_2_worker_{}' + ' ' +
'parallel_2' + " '" +
HOST_IP + "' '" +
SQLALCHEMY_DATABASE_NAME + "' '" +
HOST_IP + "' '" +
DNS + "' '" +
SQLALCHEMY_DATABASE_SERVER + "' '" +
os.environ.get('AWS_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_SECRET_ACCESS_KEY') + "' '" +
AWS_REGION + "' '" +
SECRET_KEY + "' '" +
MAIL_USERNAME + "' '" +
MAIL_PASSWORD + "' '" +
BRANCH + "' '" +
SG_ID + "' '" +
PUBLIC_SUBNET_ID + "' '" +
TOKEN + "' '" +
PARALLEL_AMI + "' '" +
KEY_NAME + "' '" +
SETUP_PERIOD['parallel_2'] + "' '" +
'IDLE_MULTIPLIER' + "' '" +
os.environ.get('MAIN_GIT_REPO') + "' '" +
str(CONCURRENCY['parallel_2']) + "' '" +
MONITORED_EMAIL_ADDRESS + "' '" +
BUCKET + "' '" +
IAM_ADMIN_GROUP + "' '" +
PRIVATE_SUBNET_ID + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_SECRET_ACCESS_KEY') + "' '" +
os.environ.get('WBIA_DB_NAME') + "' '" +
os.environ.get('WBIA_DB_SERVER') + "' '" +
os.environ.get('WBIA_DIR') + "' '" +
os.environ.get('DEBUGGING') + "'" +
' -l info'
},
'default': {
'type': 'CPU',
'ami': PARALLEL_AMI,
'instances': CPU_INSTANCE_TYPES,
'max_instances': MAX_DEFAULT,
'launch_delay': 120,
'rate': 4,
'queue_type': 'rate',
'repo': os.environ.get('MAIN_GIT_REPO'),
'branch': BRANCH,
'user_data':
'bash /home/ubuntu/TrapTagger/launch.sh ' +
'default_worker_{}' + ' ' +
'default' + " '" +
HOST_IP + "' '" +
SQLALCHEMY_DATABASE_NAME + "' '" +
HOST_IP + "' '" +
DNS + "' '" +
SQLALCHEMY_DATABASE_SERVER + "' '" +
os.environ.get('AWS_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_SECRET_ACCESS_KEY') + "' '" +
AWS_REGION + "' '" +
SECRET_KEY + "' '" +
MAIL_USERNAME + "' '" +
MAIL_PASSWORD + "' '" +
BRANCH + "' '" +
SG_ID + "' '" +
PUBLIC_SUBNET_ID + "' '" +
TOKEN + "' '" +
PARALLEL_AMI + "' '" +
KEY_NAME + "' '" +
SETUP_PERIOD['default'] + "' '" +
'IDLE_MULTIPLIER' + "' '" +
os.environ.get('MAIN_GIT_REPO') + "' '" +
str(CONCURRENCY['default']) + "' '" +
MONITORED_EMAIL_ADDRESS + "' '" +
BUCKET + "' '" +
IAM_ADMIN_GROUP + "' '" +
PRIVATE_SUBNET_ID + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_SECRET_ACCESS_KEY') + "' '" +
os.environ.get('WBIA_DB_NAME') + "' '" +
os.environ.get('WBIA_DB_SERVER') + "' '" +
os.environ.get('WBIA_DIR') + "' '" +
os.environ.get('DEBUGGING') + "'" +
' -l info'
},
'statistics': {
'type': 'CPU',
'ami': PARALLEL_AMI,
'instances': CPU_INSTANCE_TYPES,
'max_instances': MAX_STATS,
'launch_delay': 120,
'rate': 4,
'queue_type': 'rate',
'repo': os.environ.get('MAIN_GIT_REPO'),
'branch': BRANCH,
'user_data':
'bash /home/ubuntu/TrapTagger/WorkR/launch.sh ' +
'statistics_worker_{}' + ' ' +
'statistics' + " '" +
HOST_IP + "' '" +
SQLALCHEMY_DATABASE_NAME + "' '" +
HOST_IP + "' '" +
DNS + "' '" +
SQLALCHEMY_DATABASE_SERVER + "' '" +
os.environ.get('AWS_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_SECRET_ACCESS_KEY') + "' '" +
AWS_REGION + "' '" +
SECRET_KEY + "' '" +
MAIL_USERNAME + "' '" +
MAIL_PASSWORD + "' '" +
BRANCH + "' '" +
SG_ID + "' '" +
PUBLIC_SUBNET_ID + "' '" +
TOKEN + "' '" +
PARALLEL_AMI + "' '" +
KEY_NAME + "' '" +
SETUP_PERIOD['statistics'] + "' '" +
'IDLE_MULTIPLIER' + "' '" +
os.environ.get('MAIN_GIT_REPO') + "' '" +
str(CONCURRENCY['statistics']) + "' '" +
MONITORED_EMAIL_ADDRESS + "' '" +
BUCKET + "' '" +
IAM_ADMIN_GROUP + "' '" +
PRIVATE_SUBNET_ID + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_SECRET_ACCESS_KEY') + "'" +
' -l info'
},
'celery': {
'type': 'GPU',
'ami': PARALLEL_AMI,
'instances': GPU_INSTANCE_TYPES,
'max_instances': MAX_INFER,
'launch_delay': 600,
'rate': 35,
'init_size': 0.5,
'queue_type': 'rate',
'repo': os.environ.get('MAIN_GIT_REPO'),
'branch': BRANCH,
'user_data':
'bash /home/ubuntu/TrapTagger/gpuworker/launch.sh ' +
'celery_worker_{}' + ' ' +
HOST_IP + ' ' +
'celery ' +
SETUP_PERIOD['celery'] + " " +
'IDLE_MULTIPLIER' + " '" +
os.environ.get('AWS_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_SECRET_ACCESS_KEY') + "' '" +
os.environ.get('WBIA_DB_NAME') + "' '" +
os.environ.get('WBIA_DB_SERVER') + "' '" +
os.environ.get('WBIA_DIR') + "' " +
'-l info'
},
'pipeline': {
'type': 'CPU',
'ami': PARALLEL_AMI,
'instances': PIPELINE_INSTANCE_TYPES,
'max_instances': MAX_PIPELINE,
'launch_delay': 120,
'rate': 4,
'queue_type': 'rate',
'repo': os.environ.get('MAIN_GIT_REPO'),
'branch': BRANCH,
'user_data':
'bash /home/ubuntu/TrapTagger/launch.sh ' +
'pipeline_worker_{}' + ' ' +
'pipeline' + " '" +
HOST_IP + "' '" +
SQLALCHEMY_DATABASE_NAME + "' '" +
HOST_IP + "' '" +
DNS + "' '" +
SQLALCHEMY_DATABASE_SERVER + "' '" +
os.environ.get('AWS_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_SECRET_ACCESS_KEY') + "' '" +
AWS_REGION + "' '" +
SECRET_KEY + "' '" +
MAIL_USERNAME + "' '" +
MAIL_PASSWORD + "' '" +
BRANCH + "' '" +
SG_ID + "' '" +
PUBLIC_SUBNET_ID + "' '" +
TOKEN + "' '" +
PARALLEL_AMI + "' '" +
KEY_NAME + "' '" +
SETUP_PERIOD['pipeline'] + "' '" +
'IDLE_MULTIPLIER' + "' '" +
os.environ.get('MAIN_GIT_REPO') + "' '" +
str(CONCURRENCY['pipeline']) + "' '" +
MONITORED_EMAIL_ADDRESS + "' '" +
BUCKET + "' '" +
IAM_ADMIN_GROUP + "' '" +
PRIVATE_SUBNET_ID + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_SECRET_ACCESS_KEY') + "' '" +
os.environ.get('WBIA_DB_NAME') + "' '" +
os.environ.get('WBIA_DB_SERVER') + "' '" +
os.environ.get('WBIA_DIR') + "' '" +
os.environ.get('DEBUGGING') + "'" +
' -l info'
},
'llava': {
'type': 'GPU',
'ami': LLAVA_AMI,
'instances': XL_GPU_INSTANCE_TYPES,
'max_instances': MAX_LLAVA,
'launch_delay': 1500,
'rate': 31,
'init_size': 0.5,
'queue_type': 'rate',
'repo': os.environ.get('MAIN_GIT_REPO'),
'branch': BRANCH,
'user_data':
'bash /home/ubuntu/TrapTagger/llavaworker/launch.sh ' +
'celery_worker_{}' + ' ' +
HOST_IP + ' ' +
'llava ' +
SETUP_PERIOD['llava'] + " " +
'IDLE_MULTIPLIER' + " '" +
os.environ.get('AWS_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_SECRET_ACCESS_KEY') + "' " +
'-l info'
},
'similarity': {
'type': 'GPU',
'ami': PARALLEL_AMI,
'instances': GPU_INSTANCE_TYPES,
'max_instances': MAX_SIMILARITY,
'launch_delay': 600,
'rate': 35,
'init_size': 0.5,
'queue_type': 'rate',
'repo': os.environ.get('MAIN_GIT_REPO'),
'branch': BRANCH,
'user_data':
'bash /home/ubuntu/TrapTagger/gpuworker/launch.sh ' +
'similarity_worker_{}' + ' ' +
HOST_IP + ' ' +
'similarity ' +
SETUP_PERIOD['similarity'] + " " +
'IDLE_MULTIPLIER' + " '" +
os.environ.get('AWS_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_SECRET_ACCESS_KEY') + "' '" +
os.environ.get('WBIA_DB_NAME') + "' '" +
os.environ.get('WBIA_DB_SERVER') + "' '" +
os.environ.get('WBIA_DIR') + "' " +
'-l info'
},
'utility': {
'type': 'CPU',
'ami': PARALLEL_AMI,
'instances': CPU_INSTANCE_TYPES,
'max_instances': MAX_UTILITY,
'launch_delay': 120,
'rate': 4,
'queue_type': 'rate',
'repo': os.environ.get('MAIN_GIT_REPO'),
'branch': BRANCH,
'user_data':
'bash /home/ubuntu/TrapTagger/launch.sh ' +
'utility_worker_{}' + ' ' +
'utility' + " '" +
HOST_IP + "' '" +
SQLALCHEMY_DATABASE_NAME + "' '" +
HOST_IP + "' '" +
DNS + "' '" +
SQLALCHEMY_DATABASE_SERVER + "' '" +
os.environ.get('AWS_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_SECRET_ACCESS_KEY') + "' '" +
AWS_REGION + "' '" +
SECRET_KEY + "' '" +
MAIL_USERNAME + "' '" +
MAIL_PASSWORD + "' '" +
BRANCH + "' '" +
SG_ID + "' '" +
PUBLIC_SUBNET_ID + "' '" +
TOKEN + "' '" +
PARALLEL_AMI + "' '" +
KEY_NAME + "' '" +
SETUP_PERIOD['utility'] + "' '" +
'IDLE_MULTIPLIER' + "' '" +
os.environ.get('MAIN_GIT_REPO') + "' '" +
str(CONCURRENCY['utility']) + "' '" +
MONITORED_EMAIL_ADDRESS + "' '" +
BUCKET + "' '" +
IAM_ADMIN_GROUP + "' '" +
PRIVATE_SUBNET_ID + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_SECRET_ACCESS_KEY') + "' '" +
os.environ.get('WBIA_DB_NAME') + "' '" +
os.environ.get('WBIA_DB_SERVER') + "' '" +
os.environ.get('WBIA_DIR') + "' '" +
os.environ.get('DEBUGGING') + "'" +
' -l info'
},
'utility_2': {
'type': 'CPU',
'ami': PARALLEL_AMI,
'instances': CPU_INSTANCE_TYPES,
'max_instances': MAX_UTILITY_2,
'launch_delay': 180,
'rate': 4, #2695
'queue_type': 'rate',
'repo': os.environ.get('MAIN_GIT_REPO'),
'branch': BRANCH,
'user_data':
'bash /home/ubuntu/TrapTagger/launch.sh ' +
'utility_2_worker_{}' + ' ' +
'utility_2' + " '" +
HOST_IP + "' '" +
SQLALCHEMY_DATABASE_NAME + "' '" +
HOST_IP + "' '" +
DNS + "' '" +
SQLALCHEMY_DATABASE_SERVER + "' '" +
os.environ.get('AWS_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_SECRET_ACCESS_KEY') + "' '" +
AWS_REGION + "' '" +
SECRET_KEY + "' '" +
MAIL_USERNAME + "' '" +
MAIL_PASSWORD + "' '" +
BRANCH + "' '" +
SG_ID + "' '" +
PUBLIC_SUBNET_ID + "' '" +
TOKEN + "' '" +
PARALLEL_AMI + "' '" +
KEY_NAME + "' '" +
SETUP_PERIOD['utility_2'] + "' '" +
'IDLE_MULTIPLIER' + "' '" +
os.environ.get('MAIN_GIT_REPO') + "' '" +
str(CONCURRENCY['utility_2']) + "' '" +
MONITORED_EMAIL_ADDRESS + "' '" +
BUCKET + "' '" +
IAM_ADMIN_GROUP + "' '" +
PRIVATE_SUBNET_ID + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_SECRET_ACCESS_KEY') + "' '" +
os.environ.get('WBIA_DB_NAME') + "' '" +
os.environ.get('WBIA_DB_SERVER') + "' '" +
os.environ.get('WBIA_DIR') + "' '" +
os.environ.get('DEBUGGING') + "'" +
' -l info'
},
# 'classification': {
# 'type': 'GPU',
# 'ami': PARALLEL_AMI,
# 'instances': GPU_INSTANCE_TYPES,
# 'max_instances': MAX_CLASSIFICATION,
# 'launch_delay': 600,
# 'rate': 4,
# 'init_size': 2,
# 'queue_type': 'rate',
# 'repo': os.environ.get('MAIN_GIT_REPO'),
# 'branch': BRANCH,
# 'user_data':
# 'bash /home/ubuntu/TrapTagger/gpuworker/launch.sh ' +
# 'classification_worker_{}' + ' ' +
# HOST_IP + ' ' +
# 'classification ' +
# SETUP_PERIOD['classification'] + " " +
# 'IDLE_MULTIPLIER' + " '" +
# os.environ.get('AWS_ACCESS_KEY_ID') + "' '" +
# os.environ.get('AWS_SECRET_ACCESS_KEY') + "' " +
# '-l info'
# },
}
# General classifier settings
CLASSIFIER = {
'launch_delay': 600,
'queue_type': 'rate',
'init_size': 2,
'max_instances': MAX_CLASSIFICATION,
'rate': 35,
'user_data':
'bash /home/ubuntu/TrapTagger/gpuworker/launch.sh ' +
'classification_worker_{}' + ' ' +
HOST_IP + ' ' +
'{} ' +
SETUP_PERIOD['classification'] + " " +
'IDLE_MULTIPLIER' + " '" +
os.environ.get('AWS_S3_DOWNLOAD_ACCESS_KEY_ID') + "' '" +
os.environ.get('AWS_S3_DOWNLOAD_SECRET_ACCESS_KEY') + "' '" +
os.environ.get('WBIA_DB_NAME') + "' '" +
os.environ.get('WBIA_DB_SERVER') + "' '" +
os.environ.get('WBIA_DIR') + "' " +
'-l info'
}
# csv options
CSV_INFO = {
'0':{'name': 'Sighting', 'columns': ['ID','Boxes','Labels','Individuals', 'Flank']},
'1':{'name': 'Image', 'columns': ['Name', 'ID', 'Species Count', 'Labels', 'Sighting Count', 'Tags', 'Timestamp', 'URL', 'Individuals', 'Original Timestamp', 'Video Path']},
'2':{'name': 'Capture', 'columns': ['Number', 'ID', 'Species Count', 'Labels', 'Sighting Count', 'Tags', 'Timestamp', 'Image Count', 'URL', 'Individuals']},
'3':{'name': 'Cluster', 'columns': ['ID', 'Species Count', 'Labels', 'Sighting Count', 'Tags', 'Timestamp', 'Notes', 'Image Count', 'URL', 'Individuals', 'Annotator']},
'4':{'name': 'Camera', 'columns': ['Name', 'Species Count', 'Labels', 'Tags', 'Animal Count', 'Image Count', 'URL', 'Individuals']},
'5':{'name': 'Site', 'columns': ['Name', 'Species Count', 'Labels', 'Tags', 'Latitude', 'Longitude', 'Altitude', 'Animal Count', 'Image Count', 'URL', 'Individuals']},
'6':{'name': 'Survey', 'columns': ['Name', 'Species Count', 'Labels', 'Tags', 'Description', 'Animal Count', 'Image Count', 'URL', 'Individuals']},
'7':{'name': 'Custom', 'columns': []}
}
# blank cluster formats
FINISHED_CLUSTER = {
'id': '-101',
'classification': [],
'required': [],
'images': [{
'id': '-101',
'url': '-101',
'rating': '-101',
'detections': [{
'id': '-101',
'top': '-101',
'bottom': '-101',
'left': '-101',
'right': '-101',
'category': '-101',
'static': '-101'
}]
}],
'label': '-101',
'tags': '-101',
'groundTruth': '-101',
'trapGroup': '-101',
'notes': '-101'
}
EMPTY_CLUSTER = {
'id': '-99',
'classification': [],
'required': [],
'images': [{
'id': '-99',
'url': '-99',
'rating': '-99',
'detections': [{
'id': '-99',
'top': '-99',
'bottom': '-99',
'left': '-99',
'right': '-99',
'category': '-99',
'static': '-99'
}]
}],
'label': '-99',
'tags': '-99',
'groundTruth': '-99',
'trapGroup': '-99'
}
#Random Name generation
COLOURS = ["Red","Coral","Salmon","Crimson","Pink","Violet","Orange","Gold",
"Yellow","Peach","Khaki","Lavender","Plum","Magenta","Purple","Indigo","Blue",
"Chartreuse","Green","Lime","Olive","Aquamarine","Cyan","Teal","Aqua""Cyan",
"Turquoise","Navy","White","Tan","Rose","Brown","Maroon","Mint","Azure",
"Beige","Ivory","Grey","Black","Silver"]
NOUNS = ["apple","bag","balloon","bananas","bed","beef","blouse","book","bookmark",
"boom box","bottle","bottle cap","bow","bowl","box","bracelet","bread","brocolli",
"hair brush","buckel","button","camera","candle","candy wrapper","canvas","car",
"greeting card","playing card","carrots","cat","CD","cell phone","packing peanuts",
"cinder block","chair","chalk","newspaper","soy sauce packet","chapter book",
"checkbook","chocolate","clay pot","clock","clothes","computer","conditioner",
"cookie jar","cork","couch","credit card","cup","deodorant ","desk","door",
"drawer","drill press","eraser","eye liner","face wash","fake flowers","flag",
"floor","flowers","food","fork","fridge","glass","glasses","glow stick","grid paper",
"hair tie","hanger","helmet","house","ipod","charger","key chain","keyboard","keys",
"knife","lace","lamp","lamp shade","leg warmers","lip gloss","lotion","milk","mirror",
"model car","money","monitor","mop","mouse pad","mp3 player","nail clippers","nail file",
"needle","outlet","paint brush","pants","paper","pen","pencil","perfume","phone",
"photo album","picture frame","pillow","plastic fork","plate","pool stick",
"soda can","puddle","purse","blanket","radio","remote","ring","rubber band",
"rubber duck","rug","rusty nail","sailboat","sand paper","sandal","scotch tape",
"screw","seat belt","shampoo","sharpie","shawl","shirt","shoe lace","shoes",
"shovel","sidewalk","sketch pad","slipper","soap","socks","sofa","speakers",
"sponge","spoon","spring","sticky note","stockings","stop sign","street light",
"sun glasses","table","teddies","television","thermometer","thread","tire swing",
"tissue box","toe ring","toilet","tomato","tooth picks","toothbrush","toothpaste",
"towel","tree","truck","tv","twezzers","twister","vase","video games","wallet",
"washing machine","watch","water bottle","doll","magnet","wagon","headphones",
"clamp","USB drive","air freshener","piano","ice cube tray","white out","window",
"controller","coasters","thermostat","zipper"]
ADJECTIVES = ["aback","abaft","abandoned","abashed","aberrant","abhorrent","abiding",
"abject","ablaze","able","abnormal","aboard","aboriginal","abortive","abounding",
"abrasive","abrupt","absent","absorbed","absorbing","abstracted","absurd","abundant",
"abusive","acceptable","accessible","accidental","accurate","acid","acidic","acoustic",
"acrid","actually","ad hoc","adamant","adaptable","addicted","adhesive","adjoining",
"adorable","adventurous","afraid","aggressive","agonizing","agreeable","ahead","ajar",
"alcoholic","alert","alike","alive","alleged","alluring","aloof","amazing","ambiguous",
"ambitious","amuck","amused","amusing","ancient","angry","animated","annoyed","annoying",
"anxious","apathetic","aquatic","aromatic","arrogant","ashamed","aspiring","assorted",
"astonishing","attractive","auspicious","automatic","available","average","awake",
"aware","awesome","awful","axiomatic","bad","barbarous","bashful","bawdy","beautiful",
"befitting","belligerent","beneficial","bent","berserk","best","better","bewildered",
"big","billowy","bite-sized","bitter","bizarre","black","black-and-white","bloody",
"blue","blue-eyed","blushing","boiling","boorish","bored","boring","bouncy","boundless",
"brainy","brash","brave","brawny","breakable","breezy","brief","bright","bright","broad",
"broken","brown","bumpy","burly","bustling","busy","cagey","calculating","callous","calm",
"capable","capricious","careful","careless","caring","cautious","ceaseless","certain",
"changeable","charming","cheap","cheerful","chemical","chief","childlike","chilly",
"chivalrous","chubby","chunky","clammy","classy","clean","clear","clever","cloistered",
"cloudy","closed","clumsy","cluttered","coherent","cold","colorful","colossal","combative",
"comfortable","common","complete","complex","concerned","condemned","confused","conscious",
"cooing","cool","cooperative","coordinated","courageous","cowardly","crabby","craven","crazy",
"creepy","crooked","crowded","cruel","cuddly","cultured","cumbersome","curious","curly",
"curved","curvy","cut","cute","cute","cynical","daffy","daily","damaged","damaging","damp",
"dangerous","dapper","dark","dashing","dazzling","dead","deadpan","deafening","dear","debonair",
"decisive","decorous","deep","deeply","defeated","defective","defiant","delicate","delicious",
"delightful","demonic","delirious","dependent","depressed","deranged","descriptive","deserted",
"detailed","determined","devilish","didactic","different","difficult","diligent","direful",
"dirty","disagreeable","disastrous","discreet","disgusted","disgusting","disillusioned",
"dispensable","distinct","disturbed","divergent","dizzy","domineering","doubtful","drab",
"draconian","dramatic","dreary","drunk","dry","dull","dusty","dusty","dynamic","dysfunctional",
"eager","early","earsplitting","earthy","easy","eatable","economic","educated","efficacious",
"efficient","eight","elastic","elated","elderly","electric","elegant","elfin","elite","embarrassed",
"eminent","empty","enchanted","enchanting","encouraging","endurable","energetic","enormous",
"entertaining","enthusiastic","envious","equable","equal","erect","erratic","ethereal",
"evanescent","evasive","even","excellent","excited","exciting","exclusive","exotic","expensive",
"extra-large","extra-small","exuberant","exultant","fabulous","faded","faint","fair","faithful",
"fallacious","false","familiar","famous","fanatical","fancy","fantastic","far","far-flung",
"fascinated","fast","fat","faulty","fearful","fearless","feeble","feigned","female","fertile",
"festive","few","fierce","filthy","fine","finicky","first","five","fixed","flagrant","flaky",
"flashy","flat","flawless","flimsy","flippant","flowery","fluffy","fluttering","foamy","foolish",
"foregoing","forgetful","fortunate","four","frail","fragile","frantic","free","freezing","frequent",
"fresh","fretful","friendly","frightened","frightening","full","fumbling","functional","funny",
"furry","furtive","future","futuristic","fuzzy","gabby","gainful","gamy","gaping","garrulous",
"gaudy","general","gentle","giant","giddy","gifted","gigantic","glamorous","gleaming","glib",
"glistening","glorious","glossy","godly","good","goofy","gorgeous","graceful","grandiose",
"grateful","gratis","gray","greasy","great","greedy","green","grey","grieving","groovy",
"grotesque","grouchy","grubby","gruesome","grumpy","guarded","guiltless","gullible","gusty",
"guttural","habitual","half","hallowed","halting","handsome","handsomely","handy","hanging",
"hapless","happy","hard","hard-to-find","harmonious","harsh","hateful","heady","healthy",
"heartbreaking","heavenly","heavy","hellish","helpful","helpless","hesitant","hideous","high",
"highfalutin","high-pitched","hilarious","hissing","historical","holistic","hollow","homeless",
"homely","honorable","horrible","hospitable","hot","huge","hulking","humdrum","humorous","hungry",
"hurried","hurt","hushed","husky","hypnotic","hysterical","icky","icy","idiotic","ignorant","ill",
"illegal","ill-fated","ill-informed","illustrious","imaginary","immense","imminent","impartial",
"imperfect","impolite","important","imported","impossible","incandescent","incompetent","inconclusive",
"industrious","incredible","inexpensive","infamous","innate","innocent","inquisitive","insidious",
"instinctive","intelligent","interesting","internal","invincible","irate","irritating","itchy",
"jaded","jagged","jazzy","jealous","jittery","jobless","jolly","joyous","judicious","juicy","jumbled",
"jumpy","juvenile","kaput","keen","kind","kindhearted","kindly","knotty","knowing","knowledgeable",
"known","labored","lackadaisical","lacking","lame","lamentable","languid","large","last","late",
"laughable","lavish","lazy","lean","learned","left","legal","lethal","level","lewd","light","like",
"likeable","limping","literate","little","lively","lively","living","lonely","long","longing",
"long-term","loose","lopsided","loud","loutish","lovely","loving","low","lowly","lucky","ludicrous",
"lumpy","lush","luxuriant","lying","lyrical","macabre","macho","maddening","madly","magenta","magical",
"magnificent","majestic","makeshift","male","malicious","mammoth","maniacal","many","marked","massive",
"married","marvelous","material","materialistic","mature","mean","measly","meaty","medical","meek","mellow",
"melodic","melted","merciful","mere","messy","mighty","military","milky","mindless","miniature","minor",
"miscreant","misty","mixed","moaning","modern","moldy","momentous","motionless","mountainous","muddled",
"mundane","murky","mushy","mute","mysterious","naive","nappy","narrow","nasty","natural","naughty","nauseating",
"near","neat","nebulous","necessary","needless","needy","neighborly","nervous","new","next","nice","nifty",
"nimble","nine","nippy","noiseless","noisy","nonchalant","nondescript","nonstop","normal","nostalgic","nosy",
"noxious","null","numberless","numerous","nutritious","nutty","oafish","obedient","obeisant","obese","obnoxious",
"obscene","obsequious","observant","obsolete","obtainable","oceanic","odd","offbeat","old","old-fashioned",
"omniscient","one","onerous","open","opposite","optimal","orange","ordinary","organic","ossified","outgoing",
"outrageous","outstanding","oval","overconfident","overjoyed","overrated","overt","overwrought","painful",
"painstaking","pale","paltry","panicky","panoramic","parallel","parched","parsimonious","past","pastoral",
"pathetic","peaceful","penitent","perfect","periodic","permissible","perpetual","petite","petite","phobic",
"physical","picayune","pink","piquant","placid","plain","plant","plastic","plausible","pleasant","plucky",