avatar/content/_plugins/studio.py

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2022-10-26 16:39:43 +00:00
"""
This file implements an avatar studio
"""
import py_avataaars as pa
from py_avataaars import PyAvataaar as Avatar
import pandas as pd
import numpy as np
import transport
from transport import providers
from enum import Enum
import io
import base64
import copy
# _map = {'eye type':pa.EyesType,'frame style':pa.AvatarStyle,'race':pa.SkinColor,'hair color':pa.HairColor,'facial hair':pa.FacialHairType, 'facial hair color':pa.HairColor,'hair dress':pa.TopType,'mouth':pa.MouthType,'nose':pa.NoseType,'eyebrows':pa.EyebrowType }
# _vmap= {'eye type':'eye_type','frame style':'style','race':'skin_color','hair color':'hair_color','facial hair color':'facial_hair_color','facial hair':'facial_hair_type','hair dress':'top_type','eyebrows':'eye_brow','nose':'nose_type','mouth':'mouth_type'}
# _omap = {'eye_type':pa.EyesType,'style':pa.AvatarStyle}
_df = [['eye type','eye_type',pa.EyesType],['frame style','style',pa.AvatarStyle],['hair color','hair_color',pa.HairColor],['race','skin_color',pa.SkinColor],['facial hair','facial_hair_type',pa.FacialHairType],
['facial hair color','facial_hair_color',pa.Color],['mouth','mouth_type',pa.MouthType],['hat color','hat_color',pa.Color],['accessory','accessories_type',pa.AccessoriesType],['nose','nose_type',pa.NoseType],['eyebrows','eyebrow_type',pa.EyebrowType],
['hair dress','top_type',pa.TopType],['clothes', 'clothe_type', pa.ClotheType],['clothe color','clothe_color', pa.Color],['clothe graphics','clothe_graphic_type',pa.ClotheGraphicType]
]
_df = pd.DataFrame(_df,columns=['label','variable','values'])
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# _df.to_csv('/home/steve/me.avatar.csv',index=False)
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def _parameters():
_out = {'basic':{},'face':{},'clothes':{}}
for _index in np.arange(_df.shape[0]) :
row = _df.iloc[_index]
key = row['label']
if key in ['race','nose','mouth','eyebrows','eye type'] :
_id = 'basic'
elif 'clothe' in key or key=='accessory':
_id = 'clothes'
else:
_id = 'face'
if len( list(row['values'])) < 2 :
continue
_out[_id][key] = {'values': [{'name':_item.name.replace('_', ' '),'value':_item.value} for _item in row['values']],'variable':row['variable']}
return _out
def cast(_args) :
_params = {}
for key in _args :
value = int(_args[key])
_info = _df[_df.variable == key].copy()
if _info.shape[0] > 0 :
_params[key] = list(_info['values'].tolist()[0])[value]
# _params[key] = _info['values'].tolist()[value]
return _params
# def _xparameters() :
# """
# This function returns parameters to be used within an HTML context
# """
# _orgout = {'basic':{},'extended':{}}
# _out = {}
# for _key in _map :
# # _out[_key] = {'class':_map[_key].__name__,'values':[],"variable":_vmap[_key]}
# # _out[_key]['values'] = [{'name':_item.name.replace('_', ' '),'value':_item.value} for _item in _map[_key]]
# if _key == 'nose' :
# continue
# if _key in ['race','nose','mouth','eyebrows','eye type'] :
# _out = _orgout['basic']
# else:
# _out = _orgout['extended']
# _out[_key] = {'class':_map[_key].__name__,'values':[],"variable":_vmap[_key]}
# _out[_key]['values'] = [{'name':_item.name.replace('_', ' '),'value':_item.value} for _item in _map[_key]]
# # return _out
# return _orgout
def _build (_args):
"""
This function builds the avatar with a set of arguments
"""
_args = cast(_args)
if _args :
_avatar = Avatar(**_args)
_stream = _avatar.render_png()
_stream =io.BytesIO(_stream)
_stream = base64.encodebytes(_stream.getvalue()).decode('ascii')
else:
_stream = None
return _stream
def _save(_args):
"""
This function will save the data/candidate to the database
:_args {alias,email,stream}
"""
writer = transport.factory.instance(provider=providers.MONGO,context='write',db='genomix',doc='participants')
reader = transport.factory.instance(provider=providers.MONGO,context='read',db='genomix',doc='participants')
#
# Let us make sure the candidate doesn't exist
_df = reader.read(mongo={"find":"participants","filter":{"alias":_args['alias']},"projection":{"_id":0}})
_info = None
try:
if _df.shape[0] == 0 :
writer.write(_args)
else:
writer.set(_args)
_info = "1"
except Exception as e:
pass
return _info
def _participants ():
reader = transport.factory.instance(provider=providers.MONGO,context='read',db='genomix',doc='participants')
_df = reader.read(mongo={"find":"participants","limit":10,"projection":{"_id":0}})
return _df.to_dict(orient='records')