yasintuncer commited on
Commit
87f79e3
·
1 Parent(s): 6a284d0

Add scripts for polygon extraction, validation, and file extraction

Browse files

- Implemented `extract_polygons.py` to generate a CSV of polygons from Gleason CNN masks, including contour simplification and filtering based on area.
- Created `unzip-files.py` to extract tar.gz files from a zip archive into the specified output directory.
- Developed `validate_polygons.py` for validating the generated polygon CSV and producing visual comparisons, with options for filtering by creator and number of samples.

Files changed (4) hide show
  1. dataset_creator.ipynb +1406 -0
  2. extract_polygons.py +155 -0
  3. unzip-files.py +33 -0
  4. validate_polygons.py +212 -0
dataset_creator.ipynb ADDED
@@ -0,0 +1,1406 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "cells": [
3
+ {
4
+ "cell_type": "code",
5
+ "execution_count": 29,
6
+ "id": "a1b2c3d4",
7
+ "metadata": {},
8
+ "outputs": [
9
+ {
10
+ "name": "stdout",
11
+ "output_type": "stream",
12
+ "text": [
13
+ "Importlar başarılı.\n"
14
+ ]
15
+ }
16
+ ],
17
+ "source": [
18
+ "import ast\n",
19
+ "import logging\n",
20
+ "from collections import Counter, defaultdict\n",
21
+ "from pathlib import Path\n",
22
+ "\n",
23
+ "import pandas as pd\n",
24
+ "\n",
25
+ "from histopathai.config import _ensure_env_loaded\n",
26
+ "_ensure_env_loaded()\n",
27
+ "\n",
28
+ "from histopathai.dataset.builder import DatasetBuilder\n",
29
+ "from histopathai.core.model.entities import (\n",
30
+ " Workspace, Patient, Image, Annotation, AnnotationType\n",
31
+ ")\n",
32
+ "from histopathai.core.model.constants import (\n",
33
+ " OrganType, TagType, AnnotationResource,\n",
34
+ " ImageStatus, ProcessingVersion\n",
35
+ ")\n",
36
+ "from histopathai.core.model.vobj import ParentRef, ProcessingInfo, Point\n",
37
+ "\n",
38
+ "logging.basicConfig(level=logging.INFO, format=\"%(levelname)s — %(message)s\")\n",
39
+ "print(\"Importlar başarılı.\")"
40
+ ]
41
+ },
42
+ {
43
+ "cell_type": "code",
44
+ "execution_count": 30,
45
+ "id": "b2c3d4e5",
46
+ "metadata": {},
47
+ "outputs": [
48
+ {
49
+ "name": "stderr",
50
+ "output_type": "stream",
51
+ "text": [
52
+ "INFO — DatasetBuilder started: /Users/yasin/Projects/histopathai/datasets/Gleason_CNN/dataset\n"
53
+ ]
54
+ },
55
+ {
56
+ "name": "stdout",
57
+ "output_type": "stream",
58
+ "text": [
59
+ "Dataset root: /Users/yasin/Projects/histopathai/datasets/Gleason_CNN/dataset\n"
60
+ ]
61
+ }
62
+ ],
63
+ "source": [
64
+ "RESOURCE_ROOT = Path(\".\")\n",
65
+ "DATASET_ROOT = RESOURCE_ROOT / \"dataset\"\n",
66
+ "\n",
67
+ "builder = DatasetBuilder(\n",
68
+ " root=DATASET_ROOT,\n",
69
+ " overwrite=False,\n",
70
+ ")\n",
71
+ "print(f\"Dataset root: {builder.root.resolve()}\")"
72
+ ]
73
+ },
74
+ {
75
+ "cell_type": "markdown",
76
+ "id": "c3d4e5f6",
77
+ "metadata": {},
78
+ "source": [
79
+ "## Workspace"
80
+ ]
81
+ },
82
+ {
83
+ "cell_type": "code",
84
+ "execution_count": 31,
85
+ "id": "d4e5f6a7",
86
+ "metadata": {},
87
+ "outputs": [
88
+ {
89
+ "name": "stdout",
90
+ "output_type": "stream",
91
+ "text": [
92
+ "Workspace ID : n48XxS5gZIFcwEOu7POf\n",
93
+ "Workspace adı: Gleason_CNN\n"
94
+ ]
95
+ }
96
+ ],
97
+ "source": [
98
+ "workspace = Workspace(\n",
99
+ " name=\"Gleason_CNN\",\n",
100
+ " creator_id=\"111111111111111111111\",\n",
101
+ " parent=ParentRef.none(),\n",
102
+ " organ_type=OrganType.PROSTATE,\n",
103
+ " organization=\"Harvard Dataverse\",\n",
104
+ " description=(\n",
105
+ " \"H&E stained images from five prostate cancer Tissue Microarrays (TMAs) \"\n",
106
+ " \"with corresponding Gleason annotation masks. \"\n",
107
+ " \"Pixel indices: 0=Benign, 1=Gleason_3, 2=Gleason_4, 3=Gleason_5, 4=unlabelled.\"\n",
108
+ " ),\n",
109
+ " license=\"CC-BY-4.0\",\n",
110
+ " resource_url=\"https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/OCYCMP\",\n",
111
+ " release_year=2018,\n",
112
+ ")\n",
113
+ "print(f\"Workspace ID : {workspace.id}\")\n",
114
+ "print(f\"Workspace adı: {workspace.name}\")"
115
+ ]
116
+ },
117
+ {
118
+ "cell_type": "markdown",
119
+ "id": "e5f6a7b8",
120
+ "metadata": {},
121
+ "source": [
122
+ "## Annotation Types"
123
+ ]
124
+ },
125
+ {
126
+ "cell_type": "code",
127
+ "execution_count": 32,
128
+ "id": "f6a7b8c9",
129
+ "metadata": {},
130
+ "outputs": [
131
+ {
132
+ "name": "stdout",
133
+ "output_type": "stream",
134
+ "text": [
135
+ "Bulunan annotation type'lar:\n",
136
+ " 2AHDSeH1lhk6YgXA3Pdr → Tümör Bölgesi\n",
137
+ " JAZaK4be0mCXv1WnnByz → Tumor Varlığı\n",
138
+ " JWscAAWHGACNX0eiDsut → Moleküler Alt Grup\n",
139
+ " Y1xEvOgPpFBRGBBN4Lh8 → Gleason Pattern\n",
140
+ " eN6uggp5LkH3nrtmQmQb → Gleason Skorlama\n",
141
+ " z5CeGqSHP7hWLplqlIe1 → Histolojik Alt Tip\n",
142
+ "\n",
143
+ "Gleason Pattern ID : Y1xEvOgPpFBRGBBN4Lh8\n",
144
+ "Tümör Bölgesi ID : 2AHDSeH1lhk6YgXA3Pdr\n"
145
+ ]
146
+ }
147
+ ],
148
+ "source": [
149
+ "from histopathai.cloud.adapter.db.firestore import FirestoreAdapter\n",
150
+ "\n",
151
+ "db = FirestoreAdapter()\n",
152
+ "\n",
153
+ "# workspace.id ile bağlı annotation type'ları Firestore'dan çek\n",
154
+ "at_docs = db.get_all(\n",
155
+ " \"annotation_types\",\n",
156
+ " filters=[\n",
157
+ " (\"is_deleted\", \"==\", False),\n",
158
+ " ],\n",
159
+ ")\n",
160
+ "\n",
161
+ "at_by_name = {d[\"name\"]: d for d in at_docs}\n",
162
+ "print(\"Bulunan annotation type'lar:\")\n",
163
+ "for name, doc in at_by_name.items():\n",
164
+ " print(f\" {doc['id']} → {name}\")\n",
165
+ "\n",
166
+ "AT_GLEASON_PATTERN_ID = at_by_name[\"Gleason Pattern\"][\"id\"]\n",
167
+ "AT_TUMOR_BOLGESI_ID = at_by_name[\"Tümör Bölgesi\"][\"id\"]\n",
168
+ "AT_GLEASON_PATTERN_NAME = at_by_name[\"Gleason Pattern\"][\"name\"]\n",
169
+ "AT_TUMOR_BOLGESI_NAME = at_by_name[\"Tümör Bölgesi\"][\"name\"]\n",
170
+ "\n",
171
+ "print(f\"\\nGleason Pattern ID : {AT_GLEASON_PATTERN_ID}\")\n",
172
+ "print(f\"Tümör Bölgesi ID : {AT_TUMOR_BOLGESI_ID}\")"
173
+ ]
174
+ },
175
+ {
176
+ "cell_type": "code",
177
+ "execution_count": 33,
178
+ "id": "ca1a3c62",
179
+ "metadata": {},
180
+ "outputs": [],
181
+ "source": [
182
+ "workspace.annotation_types = [AT_GLEASON_PATTERN_ID, AT_TUMOR_BOLGESI_ID]"
183
+ ]
184
+ },
185
+ {
186
+ "cell_type": "markdown",
187
+ "id": "a7b8c9d0",
188
+ "metadata": {},
189
+ "source": [
190
+ "## Polygons CSV — yükle ve filtrele\n",
191
+ "\n",
192
+ "- **train** → eğitim görüntüleri \n",
193
+ "- **test_pathologist1** → test görüntüleri \n",
194
+ "- **test_pathologist2** → dışarıda bırakılır"
195
+ ]
196
+ },
197
+ {
198
+ "cell_type": "code",
199
+ "execution_count": 34,
200
+ "id": "b8c9d0e1",
201
+ "metadata": {},
202
+ "outputs": [
203
+ {
204
+ "name": "stdout",
205
+ "output_type": "stream",
206
+ "text": [
207
+ "Kullanılan polygon satırı: 1330\n",
208
+ "\n",
209
+ "creator\n",
210
+ "train 968\n",
211
+ "test_pathologist1 362\n",
212
+ "\n",
213
+ "label\n",
214
+ "G3 528\n",
215
+ "G4 457\n",
216
+ "Benign 183\n",
217
+ "G5 162\n"
218
+ ]
219
+ }
220
+ ],
221
+ "source": [
222
+ "polygons = pd.read_csv(RESOURCE_ROOT / \"polygons.csv\")\n",
223
+ "\n",
224
+ "# test_pathologist2'yi çıkar\n",
225
+ "polygons = polygons[polygons[\"creator\"] != \"test_pathologist2\"].copy()\n",
226
+ "polygons = polygons.reset_index(drop=True)\n",
227
+ "\n",
228
+ "print(f\"Kullanılan polygon satırı: {len(polygons)}\")\n",
229
+ "print()\n",
230
+ "print(polygons[\"creator\"].value_counts().to_string())\n",
231
+ "print()\n",
232
+ "print(polygons[\"label\"].value_counts().to_string())"
233
+ ]
234
+ },
235
+ {
236
+ "cell_type": "markdown",
237
+ "id": "c9d0e1f2",
238
+ "metadata": {},
239
+ "source": [
240
+ "## Patients — TMA bazında (ZT klasörü adı)"
241
+ ]
242
+ },
243
+ {
244
+ "cell_type": "code",
245
+ "execution_count": 35,
246
+ "id": "d0e1f2a3",
247
+ "metadata": {},
248
+ "outputs": [
249
+ {
250
+ "name": "stdout",
251
+ "output_type": "stream",
252
+ "text": [
253
+ "12 hasta (TMA) oluşturuldu:\n",
254
+ " ZT111_4_A → h3S6ektXcUIDjLvn3ZbR\n",
255
+ " ZT111_4_B → Zz2hb7WOoBIGXPbBXh9A\n",
256
+ " ZT111_4_C → uTXDqtQhq7iqHFTBUCjS\n",
257
+ " ZT199_1_A → nlbzszW48oRsoOaEXJ5i\n",
258
+ " ZT199_1_B → rjRhkLchanpEvX5B2lrw\n",
259
+ " ZT204_6_A → oORC1tSmstJ8bdQTbjGM\n",
260
+ " ZT204_6_B → MFMSuAFt8e792MfC5io3\n",
261
+ " ZT76_39_A → puxzFRctrF3YQah70r3V\n",
262
+ " ZT76_39_B → sb5ZaHTYMgFUQ4KxsS4S\n",
263
+ " ZT80_38_A → JhyATjySFaNppJ83uMXq\n",
264
+ " ZT80_38_B → Xc29qeWO9vgqz8TH38RG\n",
265
+ " ZT80_38_C → APSFYGmIZ1GOKQrmgZn0\n"
266
+ ]
267
+ }
268
+ ],
269
+ "source": [
270
+ "def tma_id(image_name: str) -> str:\n",
271
+ " \"\"\"ZT111_4_A_1_12 → ZT111_4_A (ilk 3 segment)\"\"\"\n",
272
+ " return \"_\".join(image_name.split(\"_\")[:3])\n",
273
+ "\n",
274
+ "polygons[\"tma\"] = polygons[\"image_name\"].apply(tma_id)\n",
275
+ "\n",
276
+ "patients = []\n",
277
+ "patient_by_tma = {}\n",
278
+ "\n",
279
+ "for tma in sorted(polygons[\"tma\"].unique()):\n",
280
+ " p = Patient(\n",
281
+ " name=tma,\n",
282
+ " creator_id=\"111111111111111111111\",\n",
283
+ " parent=ParentRef.workspace(workspace.id),\n",
284
+ " )\n",
285
+ " patients.append(p)\n",
286
+ " patient_by_tma[tma] = p\n",
287
+ "\n",
288
+ "print(f\"{len(patients)} hasta (TMA) oluşturuldu:\")\n",
289
+ "for p in patients:\n",
290
+ " print(f\" {p.name} → {p.id}\")"
291
+ ]
292
+ },
293
+ {
294
+ "cell_type": "markdown",
295
+ "id": "e1f2a3b4",
296
+ "metadata": {},
297
+ "source": [
298
+ "## Images"
299
+ ]
300
+ },
301
+ {
302
+ "cell_type": "code",
303
+ "execution_count": 36,
304
+ "id": "f2a3b4c5",
305
+ "metadata": {},
306
+ "outputs": [
307
+ {
308
+ "name": "stdout",
309
+ "output_type": "stream",
310
+ "text": [
311
+ "886 görüntü oluşturuldu.\n"
312
+ ]
313
+ }
314
+ ],
315
+ "source": [
316
+ "IMAGE_W, IMAGE_H = 3100, 3100\n",
317
+ "\n",
318
+ "images = []\n",
319
+ "image_paths = []\n",
320
+ "image_by_name = {}\n",
321
+ "\n",
322
+ "for image_name in sorted(polygons[\"image_name\"].unique()):\n",
323
+ " tma = tma_id(image_name)\n",
324
+ " patient = patient_by_tma[tma]\n",
325
+ " local_path = RESOURCE_ROOT / \"origin\" / tma / f\"{image_name}.jpg\"\n",
326
+ "\n",
327
+ " img = Image(\n",
328
+ " name=image_name,\n",
329
+ " creator_id=\"111111111111111111111\",\n",
330
+ " parent=ParentRef.patient(patient.id),\n",
331
+ " format=\"jpg\",\n",
332
+ " width=IMAGE_W,\n",
333
+ " height=IMAGE_H,\n",
334
+ " ws_id=workspace.id,\n",
335
+ " processing=ProcessingInfo(\n",
336
+ " status=ImageStatus.PENDING,\n",
337
+ " version=ProcessingVersion.V2,\n",
338
+ " ),\n",
339
+ " )\n",
340
+ " images.append(img)\n",
341
+ " image_paths.append(str(local_path))\n",
342
+ " image_by_name[image_name] = img\n",
343
+ "\n",
344
+ "print(f\"{len(images)} görüntü oluşturuldu.\")"
345
+ ]
346
+ },
347
+ {
348
+ "cell_type": "markdown",
349
+ "id": "a3b4c5d6",
350
+ "metadata": {},
351
+ "source": [
352
+ "## Annotations\n",
353
+ "\n",
354
+ "| Label | Tümör Bölgesi (global) | Gleason Pattern (local + polygon) |\n",
355
+ "|----------|------------------------|------------------------------------|\n",
356
+ "| Benign | Benign | — |\n",
357
+ "| G3/G4/G5 | Malign | G3 / G4 / G5 |"
358
+ ]
359
+ },
360
+ {
361
+ "cell_type": "code",
362
+ "execution_count": 38,
363
+ "id": "b4c5d6e7",
364
+ "metadata": {},
365
+ "outputs": [
366
+ {
367
+ "name": "stdout",
368
+ "output_type": "stream",
369
+ "text": [
370
+ "Toplam annotation: 1330\n",
371
+ " Benign : 183\n",
372
+ " G3 : 528\n",
373
+ " G4 : 457\n",
374
+ " G5 : 162\n"
375
+ ]
376
+ }
377
+ ],
378
+ "source": [
379
+ "annotations = []\n",
380
+ "\n",
381
+ "for i, row in polygons.iterrows():\n",
382
+ " image_name = row[\"image_name\"]\n",
383
+ " label = row[\"label\"]\n",
384
+ " img = image_by_name.get(image_name)\n",
385
+ " if img is None:\n",
386
+ " continue\n",
387
+ "\n",
388
+ " pts_raw = ast.literal_eval(row[\"polygon\"])\n",
389
+ " polygon = [Point(x=pt[0], y=pt[1]) for pt in pts_raw]\n",
390
+ "\n",
391
+ " if label == \"Benign\":\n",
392
+ " annotations.append(Annotation(\n",
393
+ " name=AT_TUMOR_BOLGESI_NAME,\n",
394
+ " creator_id=\"111111111111111111111\",\n",
395
+ " parent=ParentRef.image(img.id),\n",
396
+ " annotation_type_id=AT_TUMOR_BOLGESI_ID,\n",
397
+ " ws_id=workspace.id,\n",
398
+ " value=\"Benign\",\n",
399
+ " tag_type=TagType.SELECT,\n",
400
+ " is_global=False,\n",
401
+ " resource=AnnotationResource.IMPORTED,\n",
402
+ " polygon=polygon,\n",
403
+ " ))\n",
404
+ "\n",
405
+ " elif label in {\"G3\", \"G4\", \"G5\"}:\n",
406
+ " annotations.append(Annotation(\n",
407
+ " name=AT_GLEASON_PATTERN_NAME,\n",
408
+ " creator_id=\"111111111111111111111\",\n",
409
+ " parent=ParentRef.image(img.id),\n",
410
+ " annotation_type_id=AT_GLEASON_PATTERN_ID,\n",
411
+ " ws_id=workspace.id,\n",
412
+ " value=label,\n",
413
+ " tag_type=TagType.SELECT,\n",
414
+ " is_global=False,\n",
415
+ " resource=AnnotationResource.IMPORTED,\n",
416
+ " polygon=polygon,\n",
417
+ " ))\n",
418
+ "\n",
419
+ "print(f\"Toplam annotation: {len(annotations)}\")\n",
420
+ "val_counts = Counter(a.value for a in annotations)\n",
421
+ "for v, c in sorted(val_counts.items()):\n",
422
+ " print(f\" {v:8s}: {c:,}\")"
423
+ ]
424
+ },
425
+ {
426
+ "cell_type": "markdown",
427
+ "id": "c5d6e7f8",
428
+ "metadata": {},
429
+ "source": [
430
+ "## Dataset'i yaz"
431
+ ]
432
+ },
433
+ {
434
+ "cell_type": "code",
435
+ "execution_count": 39,
436
+ "id": "d6e7f8a9",
437
+ "metadata": {},
438
+ "outputs": [
439
+ {
440
+ "name": "stderr",
441
+ "output_type": "stream",
442
+ "text": [
443
+ "INFO — Workspace 'n48XxS5gZIFcwEOu7POf' added.\n",
444
+ "INFO — Patient 'h3S6ektXcUIDjLvn3ZbR' added to workspace 'n48XxS5gZIFcwEOu7POf'.\n",
445
+ "INFO — Patient 'Zz2hb7WOoBIGXPbBXh9A' added to workspace 'n48XxS5gZIFcwEOu7POf'.\n",
446
+ "INFO — Patient 'uTXDqtQhq7iqHFTBUCjS' added to workspace 'n48XxS5gZIFcwEOu7POf'.\n",
447
+ "INFO — Patient 'nlbzszW48oRsoOaEXJ5i' added to workspace 'n48XxS5gZIFcwEOu7POf'.\n",
448
+ "INFO — Patient 'rjRhkLchanpEvX5B2lrw' added to workspace 'n48XxS5gZIFcwEOu7POf'.\n",
449
+ "INFO — Patient 'oORC1tSmstJ8bdQTbjGM' added to workspace 'n48XxS5gZIFcwEOu7POf'.\n",
450
+ "INFO — Patient 'MFMSuAFt8e792MfC5io3' added to workspace 'n48XxS5gZIFcwEOu7POf'.\n",
451
+ "INFO — Patient 'puxzFRctrF3YQah70r3V' added to workspace 'n48XxS5gZIFcwEOu7POf'.\n",
452
+ "INFO — Patient 'sb5ZaHTYMgFUQ4KxsS4S' added to workspace 'n48XxS5gZIFcwEOu7POf'.\n",
453
+ "INFO — Patient 'JhyATjySFaNppJ83uMXq' added to workspace 'n48XxS5gZIFcwEOu7POf'.\n",
454
+ "INFO — Patient 'Xc29qeWO9vgqz8TH38RG' added to workspace 'n48XxS5gZIFcwEOu7POf'.\n",
455
+ "INFO — Patient 'APSFYGmIZ1GOKQrmgZn0' added to workspace 'n48XxS5gZIFcwEOu7POf'.\n",
456
+ "INFO — Added 11 annotations for image '3KsreyPHkquQYsOv5tnl'.\n",
457
+ "INFO — Added 2 annotations for image '87K3zWuqkkEH0xViyOML'.\n",
458
+ "INFO — Added 1 annotations for image 'zBMpOhlCozl8shvlvfWq'.\n",
459
+ "INFO — Added 1 annotations for image 'DodCndAezsraLUcjEIJu'.\n",
460
+ "INFO — Added 1 annotations for image 'IzXeu2LAl6NhbAsLdBcF'.\n",
461
+ "INFO — Added 1 annotations for image 'APJwMD9BPiqDyPdZ722m'.\n",
462
+ "INFO — Added 3 annotations for image 'M1hOFEW80mhbUZchoQt9'.\n",
463
+ "INFO — Added 2 annotations for image 'F3jQv01VqFFKUJ6ErhDe'.\n",
464
+ "INFO — Added 1 annotations for image '8HQgnSbQkEnIQY9gOHSM'.\n",
465
+ "INFO — Added 8 annotations for image '0F8gFnK5eNAkPo4BpK21'.\n",
466
+ "INFO — Added 1 annotations for image 'll4M2h94RtTEg4UXM1RI'.\n",
467
+ "INFO — Added 1 annotations for image 'pChpsv5712EXOhCRADND'.\n",
468
+ "INFO — Added 1 annotations for image 'K30A06r7wKSeL71SUfBr'.\n",
469
+ "INFO — Added 1 annotations for image 'XtzcxScWkqYo7twJBNZW'.\n",
470
+ "INFO — Added 1 annotations for image 'tqziCegoD0j7Aba2pHW2'.\n",
471
+ "INFO — Added 1 annotations for image 'ALmFBOkH1B9rF1EplQXS'.\n",
472
+ "INFO — Added 1 annotations for image 'Yv2fHwLakroYijRGA02v'.\n",
473
+ "INFO — Added 1 annotations for image 'oSJRwSH3rcZDycl3v5LQ'.\n",
474
+ "INFO — Added 2 annotations for image 'QVgaLCFrFLzdfCVnfk6z'.\n",
475
+ "INFO — Added 1 annotations for image 'XbRE21Uodf53h3Zy7us7'.\n",
476
+ "INFO — Added 2 annotations for image 'vVyOLyfis1akfjwcZXc1'.\n",
477
+ "INFO — Added 2 annotations for image 'iP4IsEEpsU3jaQyD2pqT'.\n",
478
+ "INFO — Added 1 annotations for image 'rENJOpKC9vIcsmHgPyMg'.\n",
479
+ "INFO — Added 3 annotations for image 'Axs7RcxkVDliXY0OkNJY'.\n",
480
+ "INFO — Added 1 annotations for image '70krqbY8S3QPE1Rs9qOX'.\n",
481
+ "INFO — Added 1 annotations for image 'xjsmQvD0gUywMRevMAXC'.\n",
482
+ "INFO — Added 1 annotations for image '8HjKwOMFSw5nRc3wVkfs'.\n",
483
+ "INFO — Added 4 annotations for image 'SYTW6FFAMaPVj63zst91'.\n",
484
+ "INFO — Added 1 annotations for image 'hvZLABNTYWYuMUo2RT8S'.\n",
485
+ "INFO — Added 2 annotations for image 'wp3fqLmkQBZHNBPnLCPr'.\n",
486
+ "INFO — Added 1 annotations for image '0BoZnGKh0bQvLSNHRmXd'.\n",
487
+ "INFO — Added 3 annotations for image 'iRncNEa565Hv2JiyYj2M'.\n",
488
+ "INFO — Added 1 annotations for image 'h27NiLnL5ls5ZTw7T56Z'.\n",
489
+ "INFO — Added 1 annotations for image 'iMmLsqMdodxWjyt2yNUO'.\n",
490
+ "INFO — Added 1 annotations for image 'VBc163Fxqtt0Qw5gNUZ1'.\n",
491
+ "INFO — Added 1 annotations for image 'idyIxIj3elPUbMNRYIuV'.\n",
492
+ "INFO — Added 4 annotations for image 'IcbszSSDsfID9UamvjHL'.\n",
493
+ "INFO — Added 1 annotations for image 'zmk2MDnlOqFtj93tLQ77'.\n",
494
+ "INFO — Added 2 annotations for image 'BE7KlWqq055euQOMJNKy'.\n",
495
+ "INFO — Added 1 annotations for image 'JGZLmS2hNs5KpfszdVTd'.\n",
496
+ "INFO — Added 1 annotations for image 'IFh6pnMu5xy0Bi2LshYj'.\n",
497
+ "INFO — Added 1 annotations for image 'jZfao68hFHgvSJVm20xo'.\n",
498
+ "INFO — Added 1 annotations for image 'YJDVS3A4LClUQrOOr1lA'.\n",
499
+ "INFO — Added 2 annotations for image 'P3axDy7XKUrESaP3jj8o'.\n",
500
+ "INFO — Added 4 annotations for image 'e8wnw2J4v5FhPdByXUID'.\n",
501
+ "INFO — Added 1 annotations for image 'KxDR2XGw1oAXX0bUMMRE'.\n",
502
+ "INFO — Added 1 annotations for image 'BhJsfOqF9qLZvRJm5VY8'.\n",
503
+ "INFO — Added 1 annotations for image 'tRKZDBfHu1djpwERNbi9'.\n",
504
+ "INFO — Added 1 annotations for image 'AEelP7zqqX5STEGp8o62'.\n",
505
+ "INFO — Added 3 annotations for image 'S0HOw3XPXYK7LvkHlXkj'.\n",
506
+ "INFO — Added 4 annotations for image '9woxmqcI21MKBnnwxifR'.\n",
507
+ "INFO — Added 1 annotations for image 'KSHjYkNA4hN0fadwygsQ'.\n",
508
+ "INFO — Added 1 annotations for image 'zEN28SQGc7fUwSoKr6wB'.\n",
509
+ "INFO — Added 1 annotations for image 'jMUJeN5JKgiosTrF5M9S'.\n",
510
+ "INFO — Added 2 annotations for image '1GvqAxdk6i6pWwhlBNJI'.\n",
511
+ "INFO — Added 1 annotations for image 'AcNPi7N2O50OXKxdNFan'.\n",
512
+ "INFO — Added 2 annotations for image 'vWkf6AiKKPtJTdMY1iaz'.\n",
513
+ "INFO — Added 2 annotations for image 'JGNfddPXWGaliMjTNMdi'.\n",
514
+ "INFO — Added 1 annotations for image 'WV3DJ7KHQAjrzGINtANW'.\n",
515
+ "INFO — Added 2 annotations for image 'b9ZVWX8T44E0Te98yzoU'.\n",
516
+ "INFO — Added 1 annotations for image 'Fc7jVEg2i6RWC240ZIWQ'.\n",
517
+ "INFO — Added 5 annotations for image 'GbUXAP5D6xfMKziS8QPE'.\n",
518
+ "INFO — Added 3 annotations for image 'rFNl2GeI7Z4j3fTIPaWU'.\n",
519
+ "INFO — Added 2 annotations for image 'GFJPCfOgOIvMtzsqL2yZ'.\n",
520
+ "INFO — Added 1 annotations for image 'mbGtMSYWPAlhtTMf4mWI'.\n",
521
+ "INFO — Added 1 annotations for image 'FTaoy0M7F1arumOG2HU0'.\n",
522
+ "INFO — Added 2 annotations for image '2OqKhmvY2FEPbFpjnklr'.\n",
523
+ "INFO — Added 1 annotations for image 'jjiMDNbxhrBKVtCDs1lD'.\n",
524
+ "INFO — Added 1 annotations for image 'rKsCiswYEsqTGrWqwnLE'.\n",
525
+ "INFO — Added 4 annotations for image 'HaqGtr81fvzAwrgUR7df'.\n",
526
+ "INFO — Added 1 annotations for image 'MdhEhnXWlbO3sqUtDbq5'.\n",
527
+ "INFO — Added 1 annotations for image 'rNlfonZBZF5bw6D5fWxk'.\n",
528
+ "INFO — Added 1 annotations for image '8VpLvUB0T6qmtLgdyIxT'.\n",
529
+ "INFO — Added 1 annotations for image 'rXZmNhAXBbdYbYZS5C3D'.\n",
530
+ "INFO — Added 2 annotations for image 'I5hxS7lWsJsqlyXwYqE7'.\n",
531
+ "INFO — Added 2 annotations for image 'rydjaAAyI39bJCD0XqSK'.\n",
532
+ "INFO — Added 3 annotations for image 'HRufpwEPvi8JLfgjQ6E6'.\n",
533
+ "INFO — Added 5 annotations for image '74qdzImg9yyr8LUVoYuP'.\n",
534
+ "INFO — Added 1 annotations for image 'LrF9QitN1KDXKHb9u3i1'.\n",
535
+ "INFO — Added 3 annotations for image 'FgbkpvClbfohoykzfnnu'.\n",
536
+ "INFO — Added 1 annotations for image 'lTR7xPGuINZP4ixyzCfW'.\n",
537
+ "INFO — Added 1 annotations for image 'Dx6z7vq2Vte4ZvSc7Fsy'.\n",
538
+ "INFO — Added 1 annotations for image 'bTMrniMJwTBUiR4quTHE'.\n",
539
+ "INFO — Added 1 annotations for image 'otUuG5hkNhm0JyQctBIt'.\n",
540
+ "INFO — Added 2 annotations for image 'PQRVnSc6ubkrCbgz9CAO'.\n",
541
+ "INFO — Added 1 annotations for image 'bbdYEXBJV7xi6Jp34c7X'.\n",
542
+ "INFO — Added 1 annotations for image 'nBrCUTTiAgKkP2aEBKHK'.\n",
543
+ "INFO — Added 1 annotations for image 'iCCY0oTitEJb7YbQXZHA'.\n",
544
+ "INFO — Added 2 annotations for image 'JJ3j5wu2O6Zg21EbaZJr'.\n",
545
+ "INFO — Added 2 annotations for image 'TViaqAdWRy2PJjC299xQ'.\n",
546
+ "INFO — Added 3 annotations for image 'FtSJOYFjassKkzDqG61K'.\n",
547
+ "INFO — Added 3 annotations for image 'ytR52u50O0iDGRl5anEF'.\n",
548
+ "INFO — Added 2 annotations for image 'htwR8eggs7SPULQ3iN5h'.\n",
549
+ "INFO — Added 1 annotations for image 'DO3Omlg76kPXXNe9DGoQ'.\n",
550
+ "INFO — Added 1 annotations for image 'A9hDm1b0uNqtuCX4UC1d'.\n",
551
+ "INFO — Added 1 annotations for image 'cjt6VDyxwbGTwJYFG57n'.\n",
552
+ "INFO — Added 4 annotations for image 'uYjbbZhhpLVKH2f7Dv1P'.\n",
553
+ "INFO — Added 1 annotations for image 'gQ3K7KHR9FdlWGdZcZLu'.\n",
554
+ "INFO — Added 2 annotations for image 'jvsQjaWLzt9DtWLdJvbN'.\n",
555
+ "INFO — Added 1 annotations for image '6hYDvCG7F6bmVX8u6Lj2'.\n",
556
+ "INFO — Added 1 annotations for image 'ih94GevONH6ElpTaPeIC'.\n",
557
+ "INFO — Added 3 annotations for image 'f850qP1fAtTOrrh2TVlK'.\n",
558
+ "INFO — Added 3 annotations for image 'nwU7a0GIy3WqsRyXWCQa'.\n",
559
+ "INFO — Added 2 annotations for image 'y4RwM43AJCJwq9fQ3Mcs'.\n",
560
+ "INFO — Added 2 annotations for image 'ZzZXgupRwGN3bVSOfJag'.\n",
561
+ "INFO — Added 2 annotations for image 'v29MsgupCqJ9dIz1J6Av'.\n",
562
+ "INFO — Added 1 annotations for image 'Zoqxj5igulSteOkiprdC'.\n",
563
+ "INFO — Added 2 annotations for image 'rb8MPOvt06Zw3M6NP59p'.\n",
564
+ "INFO — Added 1 annotations for image '3SxqNjCL2nh0t9AeE1Mx'.\n",
565
+ "INFO — Added 1 annotations for image 'NT3l8bTZ94UODnJVvaxb'.\n",
566
+ "INFO — Added 1 annotations for image 'XDU7Pj7IPc2oz9X5S0Hy'.\n",
567
+ "INFO — Added 2 annotations for image 'uiRCfAO3NWuDYSN0txvv'.\n",
568
+ "INFO — Added 2 annotations for image 'P8EPxvgnI9SCOgNCbIsC'.\n",
569
+ "INFO — Added 1 annotations for image '2XfGi69uOLiU1fjB24em'.\n",
570
+ "INFO — Added 1 annotations for image 'PnAXHbewuTpQoWmgR9Dv'.\n",
571
+ "INFO — Added 1 annotations for image 'gXRynWJikBp2gz1YHv8m'.\n",
572
+ "INFO — Added 1 annotations for image 'el85AHF0L0LvlDTl7buT'.\n",
573
+ "INFO — Added 1 annotations for image 'kWeNh6nc5ydqAZvZoFLc'.\n",
574
+ "INFO — Added 4 annotations for image 'FZPnz4lPS1yvkna87gqn'.\n",
575
+ "INFO — Added 1 annotations for image 'qz1Gzr56UDEFgctZFIkk'.\n",
576
+ "INFO — Added 2 annotations for image 'b6ikRFrrrknjudSjfHxo'.\n",
577
+ "INFO — Added 1 annotations for image '8Ks8LdNEFYRDyyxFJs0f'.\n",
578
+ "INFO — Added 1 annotations for image '0QP8JVGFbId5KxUVlqwz'.\n",
579
+ "INFO — Added 2 annotations for image 'M2MnqZDYGtWdNtVyWBBa'.\n",
580
+ "INFO — Added 1 annotations for image 'X6YGRYvMnWnn7DyX89DD'.\n",
581
+ "INFO — Added 1 annotations for image 'XsaBHIyIP3Od40xt9Nwa'.\n",
582
+ "INFO — Added 2 annotations for image 'gJJo4vpeC3yzO4H2sSxu'.\n",
583
+ "INFO — Added 4 annotations for image 'xpIHMmxmGfdeA5gUyPGQ'.\n",
584
+ "INFO — Added 2 annotations for image '9qYyzgQONPl1nEcqq5E1'.\n",
585
+ "INFO — Added 1 annotations for image 'MdB8t2rseq7CbCjif7IS'.\n",
586
+ "INFO — Added 1 annotations for image 'WE9v8zGAJnU42c1yEAM9'.\n",
587
+ "INFO — Added 1 annotations for image 'U4Z1LozvRabBzY1nP9Qv'.\n",
588
+ "INFO — Added 1 annotations for image 'SApj4QcaZjFjVnkj74lH'.\n",
589
+ "INFO — Added 1 annotations for image 'CzrahcfGW4OW0Zj0br3G'.\n",
590
+ "INFO — Added 1 annotations for image 'gK0MsFDW9Fa3R37nl6Nd'.\n",
591
+ "INFO — Added 3 annotations for image 'imUuVe1RS4TsfdIJueNS'.\n",
592
+ "INFO — Added 1 annotations for image 'IUbrsAi89xv7EjRqVHmx'.\n",
593
+ "INFO — Added 2 annotations for image 'OOJBu4W6SY7SFOe6a9oz'.\n",
594
+ "INFO — Added 3 annotations for image 'lRfhgKBy7jcPvS4Tc2mw'.\n",
595
+ "INFO — Added 1 annotations for image 'VHjyDKS02cS4kCn6O5c9'.\n",
596
+ "INFO — Added 1 annotations for image 'jr4pCgHorFZ63OM4CE32'.\n",
597
+ "INFO — Added 1 annotations for image 'vpIPeChEqY14zZejyvNI'.\n",
598
+ "INFO — Added 1 annotations for image 'tBAsSdGRdVdIBOdFSujn'.\n",
599
+ "INFO — Added 3 annotations for image 'wQ8zy5j0u8tAuiXAJgi1'.\n",
600
+ "INFO — Added 1 annotations for image '9STIzIEG1CtRVdtau1zz'.\n",
601
+ "INFO — Added 2 annotations for image 'MwwldQmkjTFeUAA3C164'.\n",
602
+ "INFO — Added 1 annotations for image 'Es5hUw6sMCRDYY89q4qx'.\n",
603
+ "INFO — Added 3 annotations for image 'MgscsQgMIw3nahTVKyXf'.\n",
604
+ "INFO — Added 6 annotations for image 'Dph2xVdMQOmpo0vxaACm'.\n",
605
+ "INFO — Added 1 annotations for image 'b5zc3qNCW2sEMmb565XT'.\n",
606
+ "INFO — Added 1 annotations for image 'L2PZXQ1nXAB3MicovSFp'.\n",
607
+ "INFO — Added 3 annotations for image 'RIuY34tLoqO7Y6gz9FSi'.\n",
608
+ "INFO — Added 3 annotations for image 'C9idwT9RQjaIwyw03UQd'.\n",
609
+ "INFO — Added 1 annotations for image 'h4Dbt9fwLOKy7IdoM0yp'.\n",
610
+ "INFO — Added 1 annotations for image 'WqU6g9V68w08IBchxkko'.\n",
611
+ "INFO — Added 7 annotations for image 'uT5BJirp6ORIckRvqsLG'.\n",
612
+ "INFO — Added 2 annotations for image 'izmaJbZ6Swiu5pQizmd1'.\n",
613
+ "INFO — Added 1 annotations for image 'GnZH5qUjGKC7vpAt3Z8R'.\n",
614
+ "INFO — Added 2 annotations for image 'DgvF8O1c1lLOeX4gdnQY'.\n",
615
+ "INFO — Added 4 annotations for image 'UC1nbcj0zrwnWYLbCKS4'.\n",
616
+ "INFO — Added 2 annotations for image '3chrfoKUT5EL5eNDYAYX'.\n",
617
+ "INFO — Added 4 annotations for image 'o4blbVZD3ap3U4m9fxYA'.\n",
618
+ "INFO — Added 3 annotations for image '4AltVsmf16ILWB1Ag4TT'.\n",
619
+ "INFO — Added 1 annotations for image 'CylGwkLcSOtG4IWafNbX'.\n",
620
+ "INFO — Added 2 annotations for image 'SFDTTCXhG5kGenTLcT2k'.\n",
621
+ "INFO — Added 1 annotations for image 'KliradVrRuAUvOSkpu4d'.\n",
622
+ "INFO — Added 1 annotations for image 'CUE9Tbk8hrWb40YxP2Mv'.\n",
623
+ "INFO — Added 1 annotations for image 'tNu2JCJ8BGWM78y3gO8M'.\n",
624
+ "INFO — Added 1 annotations for image '5VMulPN70n3jzjywbJza'.\n",
625
+ "INFO — Added 1 annotations for image 'jXshkUACVVdhgxvQARgb'.\n",
626
+ "INFO — Added 3 annotations for image 'jLaRXw9l8DgjufS7Z4m0'.\n",
627
+ "INFO — Added 1 annotations for image 'xBJjQD4xNWeBCtwRzWZH'.\n",
628
+ "INFO — Added 1 annotations for image 'XUfdenIJDefIqrYWqPb0'.\n",
629
+ "INFO — Added 1 annotations for image 'YXVzKIlhH3rim1G6Sdza'.\n",
630
+ "INFO — Added 1 annotations for image 'oUtZDgrFO8a5zfCwe6oh'.\n",
631
+ "INFO — Added 1 annotations for image 'g90MTLge9dhA3koXeZFZ'.\n",
632
+ "INFO — Added 1 annotations for image '6sIL3jOSGQBJjQBBLhkL'.\n",
633
+ "INFO — Added 1 annotations for image 'v8ePSm3IGiPxEQzyX6hq'.\n",
634
+ "INFO — Added 1 annotations for image 'mrcq59BtUem6u96jUqFD'.\n",
635
+ "INFO — Added 1 annotations for image '5XHkPsATiTFutVQz7DIZ'.\n",
636
+ "INFO — Added 1 annotations for image '8XpwF4qSQypicjVwmogs'.\n",
637
+ "INFO — Added 1 annotations for image 'r2VNbVpypXLQ0wrTt1oO'.\n",
638
+ "INFO — Added 1 annotations for image 'HNhW4X9dvfNb4DujYFSU'.\n",
639
+ "INFO — Added 1 annotations for image '7YvtU9ZoF93gnKxgon9Y'.\n",
640
+ "INFO — Added 1 annotations for image '9RxkknvUdd03XWTxMjdK'.\n",
641
+ "INFO — Added 1 annotations for image 'KhzsdIAN7ySeh4x52GtB'.\n",
642
+ "INFO — Added 1 annotations for image 'yaED2Zi1QxtlSeqZUGoe'.\n",
643
+ "INFO — Added 2 annotations for image 'qInQZm3rKE558Lu6hewP'.\n",
644
+ "INFO — Added 1 annotations for image 'e9h2AX1wctBx5eafawvP'.\n",
645
+ "INFO — Added 1 annotations for image 'cX9CQP8FcMnEQJkaEQqa'.\n",
646
+ "INFO — Added 1 annotations for image 'VvLemnX6a1czDaAwK7h5'.\n",
647
+ "INFO — Added 2 annotations for image 'zJpQk4OC7KOjBCK6hkOI'.\n",
648
+ "INFO — Added 1 annotations for image 'LeTCqSlPcM4nBN1xVN7P'.\n",
649
+ "INFO — Added 1 annotations for image '3ygyssaH3w22HO2U4Nw5'.\n",
650
+ "INFO — Added 1 annotations for image '3b7QJAqYmHxTXimNtnP2'.\n",
651
+ "INFO — Added 1 annotations for image 'ak9uHd307v6umFZhSdfB'.\n",
652
+ "INFO — Added 1 annotations for image 'ICFr8OCCGTjr08PPPzGa'.\n",
653
+ "INFO — Added 1 annotations for image 'YkvD0xZcElknZYCXslw8'.\n",
654
+ "INFO — Added 2 annotations for image 'x1ZIc1iobdTlcNuc7O1H'.\n",
655
+ "INFO — Added 1 annotations for image '5PfwrbusLbAtzAx2Hx5d'.\n",
656
+ "INFO — Added 1 annotations for image 'YND4YQQLRyNPJpfpYfmX'.\n",
657
+ "INFO — Added 2 annotations for image '0XMfMQhFpjROs5mym3lP'.\n",
658
+ "INFO — Added 2 annotations for image 'bWEiiBUFN9cDLzycc9Kk'.\n",
659
+ "INFO — Added 1 annotations for image 'xJu3YjGMVpKgQdMAcqJv'.\n",
660
+ "INFO — Added 2 annotations for image 'WSVCRskKWBRSMMW4p5ez'.\n",
661
+ "INFO — Added 1 annotations for image '7HpgOwE7KHV1DwNFD2BQ'.\n",
662
+ "INFO — Added 1 annotations for image 'TxEWHdhxO6wgZFj3PwHa'.\n",
663
+ "INFO — Added 1 annotations for image 'xzydg3DgzPMYJVLZFchF'.\n",
664
+ "INFO — Added 1 annotations for image 'G2ny9pAql6bfQi7KFk6R'.\n",
665
+ "INFO — Added 1 annotations for image 'qQrVNqmwwfFqrgudmOyJ'.\n",
666
+ "INFO — Added 1 annotations for image 'B0SGKRifIhEfcjPs12Lc'.\n",
667
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668
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669
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670
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675
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677
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678
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679
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680
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681
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683
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684
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685
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686
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688
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906
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907
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908
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909
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910
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911
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912
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913
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914
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915
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916
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917
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918
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919
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920
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921
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922
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923
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924
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925
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926
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930
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950
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951
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954
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955
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958
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963
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967
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969
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980
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986
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987
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988
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989
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990
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991
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992
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993
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994
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995
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996
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997
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998
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1001
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1002
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1005
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1006
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1007
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1008
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1016
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1021
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1024
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1025
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1026
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1027
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1028
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1032
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1033
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1036
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1037
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+ "INFO — Added 1 annotations for image 'ISeao7YTHmF47l3mfYrg'.\n",
1142
+ "INFO — Added 1 annotations for image 'VeGRdNuIVa5BPNGEYaoC'.\n",
1143
+ "INFO — Added 1 annotations for image 'bGNofpEWz4c9nWYMdzvo'.\n",
1144
+ "INFO — Added 3 annotations for image 'E91TVtcW29vlB7aaDMeq'.\n",
1145
+ "INFO — Added 2 annotations for image 'kQVisGkxucTQ4sKJ7KHb'.\n",
1146
+ "INFO — Added 1 annotations for image 'kr9JXya7qlKrTdDMeCnT'.\n",
1147
+ "INFO — Added 2 annotations for image '0FjBCnEZLzi0Y2SUNrvq'.\n",
1148
+ "INFO — Added 1 annotations for image '9QPkDFht6fZVR3heuTqC'.\n",
1149
+ "INFO — Added 1 annotations for image '3KFrubkJZ1KAMHW7F8F6'.\n",
1150
+ "INFO — Added 2 annotations for image '0LsvsFfg90D32YIrdTte'.\n",
1151
+ "INFO — Added 3 annotations for image 'GBxbIT9ZmXLszr5g3uds'.\n",
1152
+ "INFO — Added 1 annotations for image 'E9ShVPAjEaFSBelWb58t'.\n",
1153
+ "INFO — Added 1 annotations for image 'LFWreuhJBv8MsxZ376NM'.\n",
1154
+ "INFO — Added 1 annotations for image 'PkBmZ3ExTaWSxvPCmXPP'.\n",
1155
+ "INFO — Added 1 annotations for image 'Cu7heoh5dY9nZ19qaTjr'.\n",
1156
+ "INFO — Added 2 annotations for image 'hBOGffta2GkYaLbKxjm2'.\n",
1157
+ "INFO — Added 2 annotations for image 'BkIDAjdcPT05OvKJenEB'.\n",
1158
+ "INFO — Added 1 annotations for image 'liW8LicmX3cpa1zs6a3g'.\n",
1159
+ "INFO — Added 1 annotations for image '47oVy1ni1njjJDCw8QR5'.\n",
1160
+ "INFO — Added 1 annotations for image 'eqo4gbVYNiAkSEMYqgUr'.\n",
1161
+ "INFO — Added 2 annotations for image 'xSNt3i79XuZSsd7lKsjr'.\n",
1162
+ "INFO — Added 1 annotations for image 'krRuuBNMeW3w3VCwP6gH'.\n",
1163
+ "INFO — Added 4 annotations for image 'zuIPPy1RitsYI52D7Aqs'.\n",
1164
+ "INFO — Added 1 annotations for image 'VqNZCWFpO8vINhaiAaDO'.\n",
1165
+ "INFO — Added 1 annotations for image 'UPvSOvXyhK3YtYAQg2Bx'.\n",
1166
+ "INFO — Added 1 annotations for image 'SH6qehnDxkMYQSNcFMVQ'.\n",
1167
+ "INFO — Added 2 annotations for image 'K7JswF4O3YXJKQzKleRG'.\n",
1168
+ "INFO — Added 1 annotations for image 'Lj0aHV5tfiJCmrql364t'.\n",
1169
+ "INFO — Added 1 annotations for image '1AhO9ooEnEXq47SZrueb'.\n",
1170
+ "INFO — Added 2 annotations for image 'nnXecKDMJeE7aikkoi0j'.\n",
1171
+ "INFO — Added 4 annotations for image 't1uGDVuRgAVRE5U3yLx5'.\n",
1172
+ "INFO — Added 1 annotations for image '7rPOZahsqPYBvC8peRRt'.\n",
1173
+ "INFO — Added 1 annotations for image 'D41Y00UCxMYppsouf7Rv'.\n",
1174
+ "INFO — Added 1 annotations for image 'qhGKyf5JCDyAlX9e81Lj'.\n",
1175
+ "INFO — Added 1 annotations for image 'y5HJllC20ZT51u2pm7Rf'.\n",
1176
+ "INFO — Added 1 annotations for image '5RLXGlIyCceKkXHEjrwv'.\n",
1177
+ "INFO — Added 2 annotations for image '2kOY8iKyUQBV1Pbeagj6'.\n",
1178
+ "INFO — Added 2 annotations for image '7ZNw3ApzF5ur1gKxCecU'.\n",
1179
+ "INFO — Added 1 annotations for image 'rJeIXFZBbE22SnrDX44D'.\n",
1180
+ "INFO — Added 1 annotations for image '3Y2QUZBxl5HodkRp2Npi'.\n",
1181
+ "INFO — Added 2 annotations for image 'XAsuc2b64cxYr7unoavp'.\n",
1182
+ "INFO — Added 2 annotations for image 'Y0foPU990eCgjYsfAliQ'.\n",
1183
+ "INFO — Added 1 annotations for image 'UqrRw1CQNixc6CCsnR4H'.\n",
1184
+ "INFO — Added 2 annotations for image 'PFuV9qguZ1uVYndcfudA'.\n",
1185
+ "INFO — Added 2 annotations for image 'WP7UAyL7DxORiivmC1p1'.\n",
1186
+ "INFO — Added 3 annotations for image '1WZUyAUqV9BaDHEyFkIG'.\n",
1187
+ "INFO — Added 1 annotations for image 'm9ClMXGffHT3xRRy4tuL'.\n",
1188
+ "INFO — Added 2 annotations for image '4SjiB95Wd7KFrAcejP56'.\n",
1189
+ "INFO — Added 1 annotations for image 'E4xaDy7aVbt7WwdiMwVu'.\n",
1190
+ "INFO — Added 1 annotations for image 'QXbj6zs7Ol8SO18boyws'.\n",
1191
+ "INFO — Added 1 annotations for image 'qDUP2ifDmnDmgY2Cvhbg'.\n",
1192
+ "INFO — Added 1 annotations for image 'Q9hMHcVTYKfNYF8YlZAF'.\n",
1193
+ "INFO — Added 3 annotations for image 'CgFMGyan0K9gQoXiVAla'.\n",
1194
+ "INFO — Added 1 annotations for image 'MoF16cIvaC3T83JpDPy7'.\n",
1195
+ "INFO — Added 2 annotations for image 'euVweSVwSjtj93QS12ww'.\n",
1196
+ "INFO — Added 1 annotations for image 'SUm2qzvh2z97kW38QtPn'.\n",
1197
+ "INFO — Added 1 annotations for image 'sDSBhZmid1SjieE0fVRr'.\n",
1198
+ "INFO — Added 1 annotations for image 'K1B7pEF6kxeNQKCp1H2W'.\n",
1199
+ "INFO — Added 2 annotations for image 'pODzXPhIlMark3xtRDQH'.\n",
1200
+ "INFO — Added 1 annotations for image 'luUT9caKDAPV6HcTgknC'.\n",
1201
+ "INFO — Added 1 annotations for image 'bvF5E94SHSS0KjRGypVH'.\n",
1202
+ "INFO — Added 2 annotations for image 'P1n4B7vAbDVYxxaEVisV'.\n",
1203
+ "INFO — Added 1 annotations for image 'Cd8083MF8bJppr3cYgBU'.\n",
1204
+ "INFO — Added 3 annotations for image 'dWTAT26MGUUSUC23kWyD'.\n",
1205
+ "INFO — Added 1 annotations for image 'yNN8X2L4NKevpd9P7yj7'.\n",
1206
+ "INFO — Added 2 annotations for image '3CFl1GtQmgCBzt4Nk8Ag'.\n",
1207
+ "INFO — Added 1 annotations for image 'cX8ZXcstDrmsUwcf7hhv'.\n",
1208
+ "INFO — Added 1 annotations for image 'Wy6xs2txpAZoyYNEGp89'.\n",
1209
+ "INFO — Added 2 annotations for image 'LK6g5gvuEPSUJRasN8KH'.\n",
1210
+ "INFO — Added 1 annotations for image 'AGCkxMuquyZIWljFEVey'.\n",
1211
+ "INFO — Added 1 annotations for image '6MUXfZsvjbvKhyIBmUtr'.\n",
1212
+ "INFO — Added 3 annotations for image 'oo25Pm1DRLBj6PZZIYlE'.\n",
1213
+ "INFO — Added 1 annotations for image 'Ypjc4AcRHqLEqA1sYyGH'.\n",
1214
+ "INFO — Added 1 annotations for image 'Qg6tizb0cI4CayB0sfha'.\n",
1215
+ "INFO — Added 1 annotations for image 'QaGQydwMk9XCgAx8FCwH'.\n",
1216
+ "INFO — Added 1 annotations for image 'yi0Zrkhz8mi6YNpNIDs0'.\n",
1217
+ "INFO — Added 1 annotations for image 'fNgf1xkDHIayGVNPE9ym'.\n",
1218
+ "INFO — Added 1 annotations for image 'tmjammS1KmAwxgHWP18k'.\n",
1219
+ "INFO — Added 1 annotations for image 'apytndcWkEiOfuurpUl0'.\n",
1220
+ "INFO — Added 3 annotations for image 'I9GkIPVgFmB0uNxmMbu5'.\n",
1221
+ "INFO — Added 1 annotations for image 'l60mqE5kTuRfbOdEcF8u'.\n",
1222
+ "INFO — Added 1 annotations for image 'RfYzqqLdZC87OT9TN2Tp'.\n",
1223
+ "INFO — Added 2 annotations for image 'pwpnptV3b0Bs0ZG3oTG8'.\n",
1224
+ "INFO — Added 1 annotations for image 'xJoJceVEWFKd5mFxSiqc'.\n",
1225
+ "INFO — Added 2 annotations for image 'A0w8CEwY6s0GxnvHrI1l'.\n",
1226
+ "INFO — Added 1 annotations for image 'QOHpImh4g5UJgTaf6Jzn'.\n",
1227
+ "INFO — Added 1 annotations for image 'wqWkSjVciveuUTV94DLz'.\n",
1228
+ "INFO — Added 3 annotations for image 'Q4VZ4nk8jhhIHm5TVj1V'.\n",
1229
+ "INFO — Added 1 annotations for image 'cjF9x541ynzZonyYuxiJ'.\n",
1230
+ "INFO — Added 1 annotations for image 'aFC81awBRnMEbwH2f4M5'.\n",
1231
+ "INFO — Added 3 annotations for image 'psy2LR4QdouWTzGg34UO'.\n",
1232
+ "INFO — Added 1 annotations for image 'oNu9tGB2RypWVDFCZCE9'.\n",
1233
+ "INFO — Added 1 annotations for image 'HwVDrdWt0zHOYFYHSxmW'.\n",
1234
+ "INFO — Added 1 annotations for image 'YzqqpgCQbRKLl6u2EjRY'.\n",
1235
+ "INFO — Added 1 annotations for image 'rYhbFULAJIF0IMQDxPR9'.\n",
1236
+ "INFO — Added 3 annotations for image '5QaODAs6Q0VuQB3xzroc'.\n",
1237
+ "INFO — Added 1 annotations for image '9nCeOG9IJY30R35cgMB9'.\n",
1238
+ "INFO — Added 1 annotations for image 'ZXkk3dziO38dTjxZ2Xqr'.\n",
1239
+ "INFO — Added 1 annotations for image 'HSRFke6uyFMgArnnQf6z'.\n",
1240
+ "INFO — Added 1 annotations for image 'MiWFgE7bDgA0y9DOOJFf'.\n",
1241
+ "INFO — Added 3 annotations for image 'KCgZHsvJWMbVthqeqRBk'.\n",
1242
+ "INFO — Added 2 annotations for image 'gCAgHcQut7eiU1pVKcee'.\n",
1243
+ "INFO — Added 2 annotations for image 'eFn1ZNQiGQDXPj5jZs6Z'.\n",
1244
+ "INFO — Added 2 annotations for image 'oDMFnP6Ymly1VbdF9Gqo'.\n",
1245
+ "INFO — Added 1 annotations for image 'iztck6GrVxoK0ZM6vZmg'.\n",
1246
+ "INFO — Added 2 annotations for image 'HyhoBvcHjRZuQNdP2Z8Q'.\n",
1247
+ "INFO — Added 1 annotations for image '5cD02bgLT7kKSz7fdA8O'.\n",
1248
+ "INFO — Added 1 annotations for image 'EbH75nY4g3kbKkGh9gJb'.\n",
1249
+ "INFO — Added 1 annotations for image '3tNiBbC0IOu4JLUOfbwP'.\n",
1250
+ "INFO — Added 1 annotations for image 'NPcAtbnEhkM4PflCasPb'.\n",
1251
+ "INFO — Added 1 annotations for image 'NCk8iG8bVhWn5O3KKaqq'.\n",
1252
+ "INFO — Added 2 annotations for image 'u8XpOjDL9XBwMxyAZCUy'.\n",
1253
+ "INFO — Added 1 annotations for image 'PEjw6EJg9uAbTdwuifiv'.\n",
1254
+ "INFO — Added 2 annotations for image 'ooWzrSJsx8cv0FConEtx'.\n",
1255
+ "INFO — Added 2 annotations for image 'obmTAIlZdAxxOJsQ3SgA'.\n",
1256
+ "INFO — Added 1 annotations for image 'f4x15vnrNFvAk2EfvIJU'.\n",
1257
+ "INFO — Added 1 annotations for image 'GvIAFYLzJlYEmDOkrTEY'.\n",
1258
+ "INFO — Added 2 annotations for image 'un95Xoegm5JwT5B0GRuD'.\n",
1259
+ "INFO — Added 1 annotations for image 'wiGdGNYNVzsNhZx8OTZO'.\n",
1260
+ "INFO — Added 1 annotations for image 'WLc7Wb9kTQyruuEg3D6c'.\n",
1261
+ "INFO — Added 1 annotations for image '58cuoS70hCtMAEOQj7xM'.\n",
1262
+ "INFO — Added 2 annotations for image '5b97f1zErCflivcGuLIb'.\n",
1263
+ "INFO — Added 1 annotations for image 'du8FvrgMRZnCuKUpu1sZ'.\n",
1264
+ "INFO — Added 1 annotations for image 'CZeHjVV4k4HpPA7iJti0'.\n",
1265
+ "INFO — Added 1 annotations for image 'kYNNPDU4dh8pRGuUz6bw'.\n",
1266
+ "INFO — Added 1 annotations for image 'zS43if6noIQHrSGLhIO1'.\n",
1267
+ "INFO — Added 1 annotations for image 'u5PPUJ7DBFTLRHRK7SpS'.\n",
1268
+ "INFO — Added 1 annotations for image '3PGqyPS28UCmDXjwaRqY'.\n",
1269
+ "INFO — Added 1 annotations for image 'ibaC2AaTAxqRmx7peJDc'.\n",
1270
+ "INFO — Added 1 annotations for image 'fA4YTG0SiqC5kvzHJ9gy'.\n",
1271
+ "INFO — Added 2 annotations for image 'frKjrSObcZcDK3y61uss'.\n",
1272
+ "INFO — Added 3 annotations for image 'OL2UXihRVNJitnWuNHay'.\n",
1273
+ "INFO — Added 2 annotations for image 'dH3lNyrTGFBN5bPZcqq5'.\n",
1274
+ "INFO — Added 1 annotations for image 'RjJoRF0LsyaRW8W6SIPk'.\n",
1275
+ "INFO — Added 2 annotations for image 'NIs90a65LFJNUJUo8twt'.\n",
1276
+ "INFO — Added 1 annotations for image '4N1jFQa4PAMBDWUCm1Bk'.\n",
1277
+ "INFO — Added 1 annotations for image 'wRZpO4RQr80Vs6SprfEm'.\n",
1278
+ "INFO — Added 1 annotations for image 'oqQOpr4MS7xQBccTF1q6'.\n",
1279
+ "INFO — Added 1 annotations for image 'e0nkVxehHa8TMi93qgYH'.\n",
1280
+ "INFO — Added 1 annotations for image 'jkSj4NXJDhUnPcgCbeQQ'.\n",
1281
+ "INFO — Added 2 annotations for image 'LEiVN0brhXUP1cKK2smp'.\n",
1282
+ "INFO — Added 1 annotations for image 'c9jpc0oO3te93nDSEnly'.\n",
1283
+ "INFO — Added 1 annotations for image '6mcH6zcEKU4naALXPMeZ'.\n",
1284
+ "INFO — Added 1 annotations for image '4NlyJkK3X2TcG3uNxOdD'.\n",
1285
+ "INFO — Added 2 annotations for image 'NuhhrXX5AHFgYCCIAk7S'.\n",
1286
+ "INFO — Added 1 annotations for image 'xfrTqERJHVAZi1Dtbj8h'.\n",
1287
+ "INFO — Added 2 annotations for image 'ZzCs8535SnN0iuYkEN4f'.\n",
1288
+ "INFO — Added 1 annotations for image 'hrvGF4OCX9pgQskI1Z1p'.\n",
1289
+ "INFO — Added 1 annotations for image 'ZgaiUtldgSpRB9oaSYEJ'.\n",
1290
+ "INFO — Added 1 annotations for image '2aAlRS5MbM90Ydh52e4S'.\n",
1291
+ "INFO — Added 1 annotations for image 'bclXNFKgqk7xMFb6v611'.\n",
1292
+ "INFO — Added 1 annotations for image 'RnoNVY3NbGf5nTYrKLvT'.\n",
1293
+ "INFO — Added 1 annotations for image 'VwCIxOJrKaqiXdWQDEL9'.\n",
1294
+ "INFO — Added 2 annotations for image 'ynkHmpQlor2cXmpJcwNo'.\n",
1295
+ "INFO — Added 1 annotations for image 'P0UQ9RhEQFclhg2TcjS2'.\n",
1296
+ "INFO — Added 1 annotations for image 'eBLlMSHHSdfCyJ5vFTaX'.\n",
1297
+ "INFO — Added 1 annotations for image '9ZrGdSUdxpJ0YUUdwigi'.\n",
1298
+ "INFO — Added 1 annotations for image 'pVAxoZIKVXfFcG8XI0lh'.\n",
1299
+ "INFO — Added 2 annotations for image 'sMCRwSrvQUkZCpuidpap'.\n",
1300
+ "INFO — Added 1 annotations for image 'JYK3BHjz5p4LDqJQEimz'.\n",
1301
+ "INFO — Added 1 annotations for image 'PDkyBSJmqUKhmkWtg9Hb'.\n",
1302
+ "INFO — Added 1 annotations for image 'N1GDMvgwmx5yE2XvcntV'.\n",
1303
+ "INFO — Added 1 annotations for image '4p2XmBEJjMYP30Oy77bi'.\n",
1304
+ "INFO — Added 2 annotations for image '3JXXyn4UIY3PjBxuXWLd'.\n",
1305
+ "INFO — Added 1 annotations for image 'FFG6VjQfsntjtwDmsgeH'.\n",
1306
+ "INFO — Added 1 annotations for image '2qnLGDNdq43E7lmz97Ze'.\n",
1307
+ "INFO — Added 1 annotations for image 'jytwM9EljjotF80Y574G'.\n",
1308
+ "INFO — Added 1 annotations for image '7E7Vz57XcUDOHcwZSWxv'.\n",
1309
+ "INFO — Added 1 annotations for image 'jYW9ezeCEaoeD1mLlLYX'.\n",
1310
+ "INFO — Added 4 annotations for image 'AgOLsUG6TvxOHbOQhSvz'.\n",
1311
+ "INFO — Added 2 annotations for image '57fhxvaNyqoHGnvwr8B6'.\n",
1312
+ "INFO — Added 2 annotations for image 'xeIBUMM331IchxL4tGUl'.\n",
1313
+ "INFO — Added 1 annotations for image '4YRi5ps8eIBxblYp7EaA'.\n",
1314
+ "INFO — Added 1 annotations for image 'jjbKxdc82XdC3ZOJHoJz'.\n",
1315
+ "INFO — Added 2 annotations for image 'H2DHcHQJRbFjEk3jFTCs'.\n",
1316
+ "INFO — Added 1 annotations for image 'aQjVqtWjTHbux4neyCpw'.\n",
1317
+ "INFO — Added 2 annotations for image 'EsFTWuEK92dWQ7ow7DXU'.\n",
1318
+ "INFO — Added 1 annotations for image 'wJkhTHTG1SRcqMXhDt83'.\n",
1319
+ "INFO — Added 2 annotations for image 'CsT8legafEHTl1tYGifV'.\n",
1320
+ "INFO — Added 5 annotations for image 'UJigsWBn37opK8C1X9Uy'.\n",
1321
+ "INFO — Added 1 annotations for image 'qQl4ljlw595jOS1PhA97'.\n",
1322
+ "INFO — Added 1 annotations for image 'LUw6DIRfIWmIenXMzExw'.\n",
1323
+ "INFO — Added 1 annotations for image 'Ie5eaiklaDqpMNaUKdU6'.\n",
1324
+ "INFO — Added 1 annotations for image 'cS2HiwlwLdxsiOrRoBk5'.\n",
1325
+ "INFO — Added 1 annotations for image 'DulRQRgj1BrKWOuMsy6b'.\n",
1326
+ "INFO — Added 1 annotations for image 'oHddyw9fzrA63TWpHdyN'.\n",
1327
+ "INFO — Added 4 annotations for image 'pAYOzcU9sPHj3xxFnG1V'.\n",
1328
+ "INFO — Added 1 annotations for image 'HzBiGLpvEANa3e9DblGS'.\n",
1329
+ "INFO — Added 4 annotations for image 'QKuQCqxfedQ3ZmJOnKWO'.\n",
1330
+ "INFO — Added 2 annotations for image '9IBXiaRExCKjdlOPJaZ2'.\n",
1331
+ "INFO — Added 2 annotations for image '8UX8JIvWCyEDCGXfj0Ok'.\n",
1332
+ "INFO — Added 1 annotations for image '5shytbFolDWNNihWrhmE'.\n",
1333
+ "INFO — Added 1 annotations for image 'ovlHhZC0zUJBvg6k4U8a'.\n",
1334
+ "INFO — Added 1 annotations for image '5OknFQbZBcxiqnqz6AeK'.\n",
1335
+ "INFO — Added 1 annotations for image 'XLN3vA8rSftNsBroPhOn'.\n",
1336
+ "INFO — Added 1 annotations for image 'DMeOkax68IFzIxRArJnz'.\n",
1337
+ "INFO — Added 1 annotations for image 'O51NZb1oPKzItaHtCEkn'.\n",
1338
+ "INFO — Added 2 annotations for image 's7BcCWXw1B4OnZP29mNT'.\n",
1339
+ "INFO — Added 1 annotations for image 'ypbR7janL8P35NlUFOFC'.\n",
1340
+ "INFO — Added 1 annotations for image 'SB3V9WqEbQ7cxXaoDjcM'.\n",
1341
+ "INFO — Added 1 annotations for image '4AfcRknDnC4OnQrQSOXO'.\n"
1342
+ ]
1343
+ },
1344
+ {
1345
+ "name": "stdout",
1346
+ "output_type": "stream",
1347
+ "text": [
1348
+ "Tüm veriler yazıldı.\n"
1349
+ ]
1350
+ }
1351
+ ],
1352
+ "source": [
1353
+ "builder.add_workspace(workspace)\n",
1354
+ "\n",
1355
+ "for patient in patients:\n",
1356
+ " builder.add_patient(patient)\n",
1357
+ "\n",
1358
+ "for img, img_path in zip(images, image_paths):\n",
1359
+ " builder.add_image_from_local(\n",
1360
+ " image=img,\n",
1361
+ " local_path=img_path,\n",
1362
+ " origin_strategy=\"reference\",\n",
1363
+ " )\n",
1364
+ "\n",
1365
+ "annotations_by_image = defaultdict(list)\n",
1366
+ "for ann in annotations:\n",
1367
+ " annotations_by_image[ann.parent.id].append(ann)\n",
1368
+ "\n",
1369
+ "image_map = {img.id: img for img in images}\n",
1370
+ "for image_id, image_anns in annotations_by_image.items():\n",
1371
+ " builder.add_annotations(image_map[image_id], image_anns)\n",
1372
+ "\n",
1373
+ "print(\"Tüm veriler yazıldı.\")"
1374
+ ]
1375
+ },
1376
+ {
1377
+ "cell_type": "code",
1378
+ "execution_count": null,
1379
+ "id": "9cd290f7",
1380
+ "metadata": {},
1381
+ "outputs": [],
1382
+ "source": []
1383
+ }
1384
+ ],
1385
+ "metadata": {
1386
+ "kernelspec": {
1387
+ "display_name": "Python Common",
1388
+ "language": "python",
1389
+ "name": "common"
1390
+ },
1391
+ "language_info": {
1392
+ "codemirror_mode": {
1393
+ "name": "ipython",
1394
+ "version": 3
1395
+ },
1396
+ "file_extension": ".py",
1397
+ "mimetype": "text/x-python",
1398
+ "name": "python",
1399
+ "nbconvert_exporter": "python",
1400
+ "pygments_lexer": "ipython3",
1401
+ "version": "3.14.3"
1402
+ }
1403
+ },
1404
+ "nbformat": 4,
1405
+ "nbformat_minor": 5
1406
+ }
extract_polygons.py ADDED
@@ -0,0 +1,155 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """
2
+ Gleason_CNN masklerinden polygon CSV'si üretir → polygons.csv
3
+
4
+ Maske değer sözlüğü (palette PNG, tam sayı indeks):
5
+ 0 = Benign
6
+ 1 = Gleason_3 → G3
7
+ 2 = Gleason_4 → G4
8
+ 3 = Gleason_5 → G5
9
+ 4 = unlabelled → atlanır
10
+
11
+ Üç kaynak klasör ve karşılık gelen creator:
12
+ Gleason_masks_train → "train"
13
+ Gleason_masks_test_pathologist1 → "test_pathologist1"
14
+ Gleason_masks_test_pathologist2 → "test_pathologist2"
15
+
16
+ Her polygon seyreltilir (approxPolyDP, epsilon_start=2.0, max_points=50).
17
+ """
18
+
19
+ import csv
20
+ import json
21
+ import os
22
+ import re
23
+ from pathlib import Path
24
+
25
+ import cv2
26
+ import numpy as np
27
+ from PIL import Image
28
+
29
+ # ---------------------------------------------------------------------------
30
+ # Konfigürasyon
31
+ # ---------------------------------------------------------------------------
32
+
33
+ ORIGIN_DIR = Path("origin")
34
+ OUT_CSV = Path("polygons.csv")
35
+
36
+ LABEL_MAP = {0: "Benign", 1: "G3", 2: "G4", 3: "G5"} # 4 = unlabelled, atlanır
37
+
38
+ MIN_AREA = 150 # piksel cinsinden minimum alan (küçük artefaktları at)
39
+ EPSILON_START = 2.0 # approxPolyDP başlangıç epsilonu
40
+ MAX_POINTS = 50 # polygon başına maksimum köşe noktası
41
+
42
+ SOURCES = [
43
+ ("Gleason_masks_train", "train", re.compile(r"^mask_(.+)\.png$")),
44
+ ("Gleason_masks_test_pathologist1", "test_pathologist1", re.compile(r"^mask1_(.+)\.png$")),
45
+ ("Gleason_masks_test_pathologist2", "test_pathologist2", re.compile(r"^mask2_(.+)\.png$")),
46
+ ]
47
+
48
+
49
+ # ---------------------------------------------------------------------------
50
+ # Yardımcı fonksiyonlar
51
+ # ---------------------------------------------------------------------------
52
+
53
+ def simplify_contour(contour) -> list[list[int]] | None:
54
+ """Kontur → basitleştirilmiş kapalı polygon noktaları [[x, y], ...]."""
55
+ approx = cv2.approxPolyDP(contour, EPSILON_START, closed=True)
56
+ eps = EPSILON_START
57
+ while len(approx) > MAX_POINTS and eps <= 20.0:
58
+ eps *= 1.5
59
+ approx = cv2.approxPolyDP(approx.astype(np.float32), eps, closed=True)
60
+ if len(approx) < 3:
61
+ return None
62
+ pts = [[int(p[0][0]), int(p[0][1])] for p in approx]
63
+ pts.append(pts[0]) # kapanış noktası
64
+ return pts
65
+
66
+
67
+ def remove_small_components(binary: np.ndarray) -> np.ndarray:
68
+ n, labels, stats, _ = cv2.connectedComponentsWithStats(binary, connectivity=8)
69
+ clean = np.zeros_like(binary)
70
+ for lid in range(1, n):
71
+ if stats[lid, cv2.CC_STAT_AREA] >= MIN_AREA:
72
+ clean[labels == lid] = 1
73
+ return clean
74
+
75
+
76
+ def process_mask(mask_path: Path, creator: str, image_name: str) -> list[dict]:
77
+ """Maskten polygon satırlarını üretir."""
78
+ try:
79
+ arr = np.array(Image.open(mask_path))
80
+ except Exception as e:
81
+ print(f" UYARI okuma hatası ({mask_path.name}): {e}")
82
+ return []
83
+
84
+ rows = []
85
+ for class_idx, label in LABEL_MAP.items():
86
+ binary = (arr == class_idx).astype(np.uint8)
87
+ if binary.sum() == 0:
88
+ continue
89
+
90
+ binary = remove_small_components(binary)
91
+ if binary.sum() == 0:
92
+ continue
93
+
94
+ contours, _ = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
95
+ for cnt in contours:
96
+ if cv2.contourArea(cnt) < MIN_AREA:
97
+ continue
98
+ pts = simplify_contour(cnt)
99
+ if pts is None:
100
+ continue
101
+ rows.append({
102
+ "image_name": image_name,
103
+ "label": label,
104
+ "polygon": json.dumps(pts),
105
+ "creator": creator,
106
+ })
107
+ return rows
108
+
109
+
110
+ # ---------------------------------------------------------------------------
111
+ # Ana akış
112
+ # ---------------------------------------------------------------------------
113
+
114
+ def main():
115
+ all_rows: list[dict] = []
116
+
117
+ for folder_name, creator, name_re in SOURCES:
118
+ folder = ORIGIN_DIR / folder_name
119
+ if not folder.exists():
120
+ print(f"UYARI: klasör bulunamadı → {folder}")
121
+ continue
122
+
123
+ mask_files = sorted(
124
+ p for p in folder.glob("*.png")
125
+ if not p.name.startswith("._")
126
+ )
127
+ print(f"\n{folder_name} ({len(mask_files)} maske) creator='{creator}'")
128
+
129
+ skipped = 0
130
+ for mf in mask_files:
131
+ m = name_re.match(mf.name)
132
+ if not m:
133
+ skipped += 1
134
+ continue
135
+ image_name = m.group(1)
136
+ rows = process_mask(mf, creator, image_name)
137
+ all_rows.extend(rows)
138
+
139
+ if skipped:
140
+ print(f" {skipped} dosya isim kalıbına uymadı, atlandı.")
141
+
142
+ print(f"\nToplam {len(all_rows)} polygon satırı → {OUT_CSV}")
143
+ with open(OUT_CSV, "w", newline="") as f:
144
+ writer = csv.DictWriter(
145
+ f, fieldnames=["image_name", "label", "polygon", "creator"]
146
+ )
147
+ writer.writeheader()
148
+ writer.writerows(all_rows)
149
+
150
+ print("Tamamlandı.")
151
+
152
+
153
+ if __name__ == "__main__":
154
+ os.chdir(Path(__file__).parent)
155
+ main()
unzip-files.py ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import zipfile
2
+ import tarfile
3
+ import io
4
+ import os
5
+ from pathlib import Path
6
+
7
+ ZIP_PATH = Path("dataverse_files.zip")
8
+ OUTPUT_DIR = Path("origin")
9
+
10
+ OUTPUT_DIR.mkdir(exist_ok=True)
11
+
12
+ with zipfile.ZipFile(ZIP_PATH) as zf:
13
+ entries = zf.namelist()
14
+ tgz_files = [e for e in entries if e.endswith(".tar.gz")]
15
+
16
+ print(f"Found {len(tgz_files)} tar.gz archives in {ZIP_PATH.name}")
17
+
18
+ for tgz_name in tgz_files:
19
+ print(f"\nExtracting {tgz_name} ...")
20
+ with zf.open(tgz_name) as raw:
21
+ with tarfile.open(fileobj=io.BufferedReader(raw), mode="r:gz") as tf:
22
+ members = tf.getmembers()
23
+ for member in members:
24
+ dest = OUTPUT_DIR / member.name
25
+ if member.isdir():
26
+ dest.mkdir(parents=True, exist_ok=True)
27
+ elif member.isfile():
28
+ dest.parent.mkdir(parents=True, exist_ok=True)
29
+ with tf.extractfile(member) as src, open(dest, "wb") as out:
30
+ out.write(src.read())
31
+ print(f" -> {len([m for m in members if m.isfile()])} files extracted to origin/{Path(tgz_name).stem.replace('.tar', '')}/")
32
+
33
+ print("\nDone. All archives extracted to:", OUTPUT_DIR.resolve())
validate_polygons.py ADDED
@@ -0,0 +1,212 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """
2
+ Gleason_CNN polygon CSV'sini doğrular ve görsel karşılaştırma üretir.
3
+
4
+ Kullanım:
5
+ python validate_polygons.py # 3 rastgele patch
6
+ python validate_polygons.py --n 5 --seed 7
7
+ python validate_polygons.py --creator test_pathologist1 --n 2
8
+
9
+ Çıktılar:
10
+ - Konsol: istatistikler (label dağılımı, creator dağılımı, nokta sayıları)
11
+ - PNG: validate_<image_name>.png (maske + orijinal + polygon overlay)
12
+ """
13
+
14
+ import argparse
15
+ import json
16
+ import random
17
+ import sys
18
+ from pathlib import Path
19
+
20
+ import cv2
21
+ import matplotlib.patches as mpatches
22
+ import matplotlib.pyplot as plt
23
+ import numpy as np
24
+ import pandas as pd
25
+ from matplotlib.patches import Polygon as MplPolygon
26
+ from PIL import Image
27
+
28
+ ORIGIN_DIR = Path("origin")
29
+ CSV_PATH = Path("polygons.csv")
30
+
31
+ # Palette PNG'deki sınıf renklerini taklit et (görselleştirme için)
32
+ CLASS_COLORS = {
33
+ "Benign": "#00cc44",
34
+ "G3": "#4488ff",
35
+ "G4": "#ffdd00",
36
+ "G5": "#ff2222",
37
+ }
38
+
39
+ # Her kaynak için maske klasörü ve isim öneki
40
+ SOURCE_INFO = {
41
+ "train": ("Gleason_masks_train", "mask_"),
42
+ "test_pathologist1": ("Gleason_masks_test_pathologist1", "mask1_"),
43
+ "test_pathologist2": ("Gleason_masks_test_pathologist2", "mask2_"),
44
+ }
45
+
46
+ # Maske palette indeks → label
47
+ MASK_LABEL = {0: "Benign", 1: "G3", 2: "G4", 3: "G5"}
48
+
49
+ # ZT klasörü bulma: image_name'in ilk üç alt kısmı TMA kimliği
50
+ def find_image_path(image_name: str) -> Path | None:
51
+ parts = image_name.split("_")
52
+ for n in range(len(parts), 0, -1):
53
+ tma_id = "_".join(parts[:n])
54
+ candidate = ORIGIN_DIR / tma_id / f"{image_name}.jpg"
55
+ if candidate.exists():
56
+ return candidate
57
+ return None
58
+
59
+
60
+ def find_mask_path(image_name: str, creator: str) -> Path | None:
61
+ folder_name, prefix = SOURCE_INFO[creator]
62
+ candidate = ORIGIN_DIR / folder_name / f"{prefix}{image_name}.png"
63
+ return candidate if candidate.exists() else None
64
+
65
+
66
+ # ---------------------------------------------------------------------------
67
+ # İstatistikler
68
+ # ---------------------------------------------------------------------------
69
+
70
+ def print_stats(df: pd.DataFrame):
71
+ print(f"\n{'='*60}")
72
+ print(f"Toplam polygon satırı : {len(df):,}")
73
+ print(f"\nLabel dağılımı:")
74
+ for label, cnt in df["label"].value_counts().items():
75
+ print(f" {label:8s}: {cnt:6,}")
76
+ print(f"\nCreator dağılımı:")
77
+ for creator, cnt in df["creator"].value_counts().items():
78
+ print(f" {creator:25s}: {cnt:6,}")
79
+ lengths = df["polygon"].apply(lambda s: len(json.loads(s)) - 1)
80
+ print(f"\nPolygon nokta sayısı (kapanış hariç):")
81
+ print(f" min={lengths.min()} max={lengths.max()} "
82
+ f"medyan={lengths.median():.0f} ort={lengths.mean():.1f}")
83
+ print(f"{'='*60}\n")
84
+
85
+
86
+ # ---------------------------------------------------------------------------
87
+ # Görselleştirme
88
+ # ---------------------------------------------------------------------------
89
+
90
+ def draw_polygons(ax, image_rgb, polys: list[tuple[str, list]], title: str):
91
+ ax.imshow(image_rgb)
92
+ ax.set_title(title, fontsize=8)
93
+ ax.axis("off")
94
+ legend = {}
95
+ for label, pts in polys:
96
+ color = CLASS_COLORS.get(label, "#ffffff")
97
+ arr = np.array(pts[:-1])
98
+ patch = MplPolygon(arr, closed=True, facecolor=color,
99
+ alpha=0.35, edgecolor=color, linewidth=1.5)
100
+ ax.add_patch(patch)
101
+ if label not in legend:
102
+ legend[label] = mpatches.Patch(color=color, label=label)
103
+ if legend:
104
+ ax.legend(handles=list(legend.values()), loc="upper right",
105
+ fontsize=7, framealpha=0.7)
106
+
107
+
108
+ def visualize_sample(image_name: str, creator: str, df: pd.DataFrame):
109
+ mask_path = find_mask_path(image_name, creator)
110
+ img_path = find_image_path(image_name)
111
+
112
+ mask_rgb = (
113
+ np.array(Image.open(mask_path).convert("RGB"))
114
+ if mask_path else np.zeros((200, 200, 3), dtype=np.uint8)
115
+ )
116
+ image_rgb = (
117
+ cv2.cvtColor(cv2.imread(str(img_path)), cv2.COLOR_BGR2RGB)
118
+ if img_path else np.zeros_like(mask_rgb)
119
+ )
120
+
121
+ rows = df[(df["image_name"] == image_name) & (df["creator"] == creator)]
122
+ polys = [(r["label"], json.loads(r["polygon"])) for _, r in rows.iterrows()]
123
+ n_pts = sum(len(p) - 1 for _, p in polys)
124
+
125
+ fig, axes = plt.subplots(1, 3, figsize=(18, 6))
126
+ fig.suptitle(f"{image_name} [creator={creator}]", fontsize=9)
127
+
128
+ axes[0].imshow(mask_rgb)
129
+ axes[0].set_title("Maske (palette → RGB)")
130
+ axes[0].axis("off")
131
+
132
+ axes[1].imshow(image_rgb)
133
+ axes[1].set_title("Orijinal görüntü")
134
+ axes[1].axis("off")
135
+
136
+ draw_polygons(
137
+ axes[2], image_rgb, polys,
138
+ f"Polygonlar ({len(polys)} adet / {n_pts} nokta)"
139
+ )
140
+
141
+ plt.tight_layout()
142
+ out_path = f"validate_{image_name[:50]}.png"
143
+ plt.savefig(out_path, dpi=110, bbox_inches="tight")
144
+ plt.close(fig)
145
+ print(f" Kaydedildi: {out_path} "
146
+ f"({len(polys)} polygon, {n_pts} nokta)")
147
+
148
+
149
+ # ---------------------------------------------------------------------------
150
+ # Main
151
+ # ---------------------------------------------------------------------------
152
+
153
+ def main():
154
+ parser = argparse.ArgumentParser()
155
+ parser.add_argument("--csv", default=str(CSV_PATH))
156
+ parser.add_argument("--n", type=int, default=3,
157
+ help="Gösterilecek örnek sayısı")
158
+ parser.add_argument("--seed", type=int, default=42)
159
+ parser.add_argument("--creator", default=None,
160
+ help="Filtrele: train / test_pathologist1 / test_pathologist2")
161
+ args = parser.parse_args()
162
+
163
+ csv_path = Path(args.csv)
164
+ if not csv_path.exists():
165
+ sys.exit(f"CSV bulunamadı: {csv_path}")
166
+
167
+ df = pd.read_csv(csv_path)
168
+
169
+ # Temel yapı kontrolleri
170
+ required = {"image_name", "label", "polygon", "creator"}
171
+ missing = required - set(df.columns)
172
+ if missing:
173
+ sys.exit(f"CSV'de eksik kolonlar: {missing}")
174
+
175
+ invalid_labels = set(df["label"].unique()) - {"Benign", "G3", "G4", "G5"}
176
+ if invalid_labels:
177
+ print(f"UYARI: Beklenmeyen label değerleri: {invalid_labels}")
178
+
179
+ invalid_creators = set(df["creator"].unique()) - set(SOURCE_INFO.keys())
180
+ if invalid_creators:
181
+ print(f"UYARI: Beklenmeyen creator değerleri: {invalid_creators}")
182
+
183
+ print_stats(df)
184
+
185
+ subset = df if args.creator is None else df[df["creator"] == args.creator]
186
+ unique_images = subset["image_name"].unique().tolist()
187
+
188
+ if not unique_images:
189
+ sys.exit("Görselleştirme için uygun görüntü bulunamadı.")
190
+
191
+ # Polygon sayısı fazla olanları tercih et (içerik zengini)
192
+ by_count = (
193
+ subset.groupby("image_name")
194
+ .size()
195
+ .sort_values(ascending=False)
196
+ )
197
+ candidates = by_count.head(50).index.tolist()
198
+ random.seed(args.seed)
199
+ selected = random.sample(candidates, min(args.n, len(candidates)))
200
+
201
+ print(f"Görselleştirilen {len(selected)} örnek:\n")
202
+ for img_name in selected:
203
+ creator = df.loc[df["image_name"] == img_name, "creator"].iloc[0]
204
+ visualize_sample(img_name, creator, df)
205
+
206
+ print("\nGörüntüler validate_*.png olarak kaydedildi.")
207
+
208
+
209
+ if __name__ == "__main__":
210
+ import os
211
+ os.chdir(Path(__file__).parent)
212
+ main()