-
Notifications
You must be signed in to change notification settings - Fork 3
/
Copy pathAnnotationMetadataProcessors.py
262 lines (225 loc) · 9.77 KB
/
AnnotationMetadataProcessors.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
from data_model import *
from processor import Processor
from sqlite3 import connect
from pandas import read_csv, Series, DataFrame, merge, read_sql
import pandas as pd
class MetadataProcessor(Processor):
def __init__(self):
super().__init__()
def uploadData(self, path):
try:
with connect(self.dbPathOrUrl) as con:
path = read_csv(
path,
keep_default_na=False,
dtype={"id": "string", "title": "string", "creator": "string"},
)
creators = pd.DataFrame()
creator_list = []
for value in path["creator"]:
if value != "":
creator_list.append(value)
creators.insert(0, "creator", Series(creator_list, dtype="string"))
creators = creators.rename(columns={"creator": "creator_name"})
creators["creator_name"] = creators["creator_name"].str.split(";")
creators_def = creators.explode("creator_name")
creators_def = creators_def.reset_index(drop=True)
internal_id_dict = {}
creator_internal_id = []
for idx, row in creators_def.iterrows():
creator = row["creator_name"]
if creator in internal_id_dict:
creators_def.drop(idx, inplace=True)
else:
internal_id = "creator-" + str(len(internal_id_dict))
creator_internal_id.append(internal_id)
internal_id_dict[creator] = internal_id
creators_def.insert(
0,
"creator_internal_id",
Series(creator_internal_id, dtype="string"),
)
metadata_entities = path[["id", "title", "creator"]]
metadata_entities["creator"] = metadata_entities["creator"].str.split(
";"
)
metadata_entities = metadata_entities.explode("creator")
metadata_entities = metadata_entities.reset_index(drop=True)
metadata_merged = merge(
metadata_entities,
creators_def,
left_on="creator",
right_on="creator_name",
how="left",
)
metadata_def = metadata_merged[["id", "title", "creator_internal_id"]]
metadata_def = metadata_def.rename(
columns={"creator_internal_id": "creator"}
)
internal_id_dict1 = {}
metadata_internal_id = []
for idx, row in metadata_def.iterrows():
entity = row["id"]
if entity in internal_id_dict1:
metadata_internal_id.append(internal_id_dict1[entity])
else:
internal_id1 = "metadata-" + str(len(internal_id_dict1))
metadata_internal_id.append(internal_id1)
internal_id_dict1[entity] = internal_id1
metadata_def.insert(
0,
"metadata_internal_id",
Series(metadata_internal_id, dtype="string"),
)
try:
query = f"""
SELECT * FROM Annotations
"""
df = pd.read_sql_query(query, con)
if not df.empty:
query = "SELECT * FROM 'Annotations'"
annotation_temp = pd.read_sql_query(query, con)
annotation_merged = merge(
annotation_temp,
metadata_def,
left_on="annotation_targets",
right_on="id",
)
annotation_table = annotation_merged[
[
"annotation_ids",
"annotation_internal_id",
"annotation_bodies",
"metadata_internal_id",
"annotation_motivations",
]
]
annotation_table = annotation_table.rename(
columns={"metadata_internal_id": "annotation_targets"}
)
annotation_table.to_sql(
"Annotations", con, if_exists="replace", index=False
)
except:
pass
metadata_def.to_sql(
"EntitiesWithMetadata", con, if_exists="replace", index=False
)
creators_def.to_sql("Creators", con, if_exists="replace", index=False)
con.commit()
return True
except Exception as e:
print(e)
return False
class AnnotationProcessor(Processor):
def __init__(self):
super().__init__()
def uploadData(self, path2):
try:
with connect(self.dbPathOrUrl) as con:
path2 = read_csv(
path2,
keep_default_na=False,
dtype={
"id": "string",
"body": "string",
"target": "string",
"motivation": "string",
},
)
annotation_table = pd.DataFrame()
annotation_ids = []
for idx, value in path2["id"].items():
annotation_ids.append(value)
annotation_table.insert(
0, "annotation_ids", Series(annotation_ids, dtype="string")
)
annotation_internal_id = []
for idx, row in path2.iterrows():
annotation_internal_id.append("annotation-" + str(idx))
annotation_table.insert(
0,
"annotation_internal_id",
Series(annotation_internal_id, dtype="string"),
)
annotation_bodies = []
for idx, value in path2["body"].items():
annotation_bodies.append(value)
annotation_table.insert(
2, "annotation_bodies", Series(annotation_bodies, dtype="string")
)
annotation_targets = []
for idx, value in path2["target"].items():
annotation_targets.append(value)
annotation_table.insert(
3, "annotation_targets", Series(annotation_targets, dtype="string")
)
annotation_motivations = []
for idx, value in path2["motivation"].items():
annotation_motivations.append(value)
annotation_table.insert(
4,
"annotation_motivations",
Series(annotation_motivations, dtype="string"),
)
try:
query = "SELECT * FROM EntitiesWithMetadata"
metadata_temp = pd.read_sql_query(query, con)
annotation_merged = merge(
annotation_table,
metadata_temp,
left_on="annotation_targets",
right_on="id",
)
annotation_table = annotation_merged[
[
"annotation_ids",
"annotation_internal_id",
"annotation_bodies",
"metadata_internal_id",
"annotation_motivations",
]
]
annotation_table = annotation_table.rename(
columns={"metadata_internal_id": "annotation_targets"}
)
except:
pass
image = pd.DataFrame()
image_ids = []
for index, value in path2["body"].items():
image_ids.append(value)
image.insert(0, "image_ids", Series(image_ids, dtype="string"))
image_internal_id = []
for idx, rows in image.iterrows():
image_internal_id.append("images-" + str(idx))
image.insert(
0, "images_internal_id", Series(image_internal_id, dtype="string")
)
annotation_merged2 = merge(
annotation_table,
image,
left_on="annotation_bodies",
right_on="image_ids",
)
annotation_def = annotation_merged2[
[
"annotation_internal_id",
"annotation_ids",
"images_internal_id",
"annotation_targets",
"annotation_motivations",
]
]
annotation_def = annotation_def.rename(
columns={"images_internal_id": "annotation_bodies"}
)
annotation_def.to_sql(
"Annotations", con, if_exists="replace", index=False
)
image.to_sql("Images", con, if_exists="replace", index=False)
con.commit()
return True
except Exception as e:
print(e)
return False