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Update raster and confidences scores [SN-60/61/63] (#1127)
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9 files changed

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-784
lines changed

9 files changed

+160
-784
lines changed

‎examples/annotation_import/image.ipynb‎

Lines changed: 20 additions & 32 deletions
Original file line numberDiff line numberDiff line change
@@ -180,14 +180,14 @@
180180
"nested_radio_annotation_ndjson = {\n",
181181
" \"name\": \"nested_radio_question\",\n",
182182
" \"answer\": {\n",
183-
" \"name\": \"first_radio_answer\"\n",
184-
" },\n",
185-
" \"classifications\": [{\n",
186-
" \"name\": \"sub_radio_question\",\n",
187-
" \"answer\": {\n",
188-
" \"name\": \"first_sub_radio_answer\"\n",
189-
" }\n",
190-
" }]\n",
183+
" \"name\": \"first_radio_answer\",\n",
184+
" \"classifications\": [{\n",
185+
" \"name\": \"sub_radio_question\",\n",
186+
" \"answer\": {\n",
187+
" \"name\": \"first_sub_radio_answer\"\n",
188+
" }\n",
189+
" }]\n",
190+
" }\n",
191191
"}\n",
192192
"\n",
193193
"\n",
@@ -431,19 +431,8 @@
431431
"metadata": {},
432432
"source": [
433433
"# Identifying what values in the numpy array correspond to the mask annotation\n",
434-
"color = (0, 0, 0)\n",
435-
"\n",
436-
"# convert a polygon to mask\n",
437-
"im_height, im_width = 100,100 # need to provide the height and width of image\n",
438-
"mask_data = lb_types.MaskData(arr=\n",
439-
" polygon_annotation.value.draw(height=im_height,width=im_width,color=color))\n",
440-
"\n",
441-
"# convert a 2D array to 3D array\n",
442-
"arr_2d = np.zeros((100,100), dtype=\"uint8\")\n",
443-
"mask_data = lb_types.MaskData.from_2D_arr(arr_2d)\n",
444-
"\n",
445-
"# a 3D array where 3rd axis is RGB values\n",
446-
"mask_data = lb_types.MaskData(arr=np.zeros([400,450,3],dtype=\"uint8\"))\n",
434+
"color = (255, 255, 255)\n",
435+
"mask_data = lb_types.MaskData(url=\"https://storage.googleapis.com/labelbox-datasets/image_sample_data/raster_seg.png\")\n",
447436
"\n",
448437
"# Python annotation\n",
449438
"mask_annotation = lb_types.ObjectAnnotation(\n",
@@ -455,8 +444,8 @@
455444
"mask_annotation_ndjson = {\n",
456445
" \"name\": \"mask\",\n",
457446
" \"classifications\": [],\n",
458-
" \"mask\": {\"instanceURI\": \"https://storage.labelbox.com/cjhfn5y6s0pk507024nz1ocys%2F1d60856c-59b7-3060-2754-83f7e93e0d01-1?Expires=1666901963361&KeyName=labelbox-assets-key-3&Signature=t-2s2DB4YjFuWEFak0wxYqfBfZA\",\n",
459-
" \"colorRGB\": (0, 0, 0)}\n",
447+
" \"mask\": {\"instanceURI\": \"https://storage.googleapis.com/labelbox-datasets/image_sample_data/raster_seg.png\",\n",
448+
" \"colorRGB\": (255, 255, 255)}\n",
460449
"}"
461450
],
462451
"cell_type": "code",
@@ -746,7 +735,7 @@
746735
" options=[lb.Option(value=\"first_sub_radio_answer\")]),\n",
747736
" ]),\n",
748737
" lb.Tool(tool=lb.Tool.Type.POLYGON, name=\"polygon\"),\n",
749-
" lb.Tool(tool=lb.Tool.Type.SEGMENTATION, name=\"mask\"),\n",
738+
" lb.Tool(tool=lb.Tool.Type.RASTER_SEGMENTATION, name=\"mask\"),\n",
750739
" lb.Tool(tool=lb.Tool.Type.POINT, name=\"point\"),\n",
751740
" lb.Tool(tool=lb.Tool.Type.LINE, name=\"polyline\"),\n",
752741
" lb.Tool(tool=lb.Tool.Type.RELATIONSHIP, name=\"relationship\")\n",
@@ -831,7 +820,7 @@
831820
{
832821
"metadata": {},
833822
"source": [
834-
"labels = []\n",
823+
"label = []\n",
835824
"annotations = [\n",
836825
" radio_annotation,\n",
837826
" nested_radio_annotation,\n",
@@ -848,7 +837,7 @@
848837
" bbox_target,\n",
849838
" relationship,\n",
850839
"]\n",
851-
"labels.append(\n",
840+
"label.append(\n",
852841
" lb_types.Label(data=lb_types.ImageData(global_key=global_key),\n",
853842
" annotations=annotations))"
854843
],
@@ -867,7 +856,7 @@
867856
{
868857
"metadata": {},
869858
"source": [
870-
"ndjson_labels = []\n",
859+
"ndjson_label = []\n",
871860
"annotations = [\n",
872861
" radio_annotation_ndjson,\n",
873862
" nested_radio_annotation_ndjson,\n",
@@ -890,7 +879,7 @@
890879
" \"globalKey\": global_key\n",
891880
" },\n",
892881
" })\n",
893-
" ndjson_labels.append(annotation)"
882+
" ndjson_label.append(annotation)"
894883
],
895884
"cell_type": "code",
896885
"outputs": [],
@@ -919,7 +908,7 @@
919908
" client=client,\n",
920909
" project_id=project.uid,\n",
921910
" name=\"mal_job\" + str(uuid.uuid4()),\n",
922-
" predictions=labels\n",
911+
" predictions=label\n",
923912
")\n",
924913
"upload_job.wait_until_done()\n",
925914
"\n",
@@ -948,11 +937,10 @@
948937
"# client = client, \n",
949938
"# project_id = project.uid, \n",
950939
"# name=\"label_import_job\"+str(uuid.uuid4()), \n",
951-
"# labels=ndjson_labels)\n",
940+
"# labels=label)\n",
952941
"\n",
953942
"# print(\"Errors:\", upload_job.errors)\n",
954-
"# print(\"Status of uploads: \", upload_job.statuses)\n",
955-
"# print(\" \")"
943+
"# print(\"Status of uploads: \", upload_job.statuses)"
956944
],
957945
"cell_type": "code",
958946
"outputs": [],

‎examples/annotation_import/video.ipynb‎

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -509,10 +509,11 @@
509509
"# NDJSON\n",
510510
"nested_radio_annotation_ndjson = {\n",
511511
" \"name\": \"nested_radio_question\",\n",
512-
" \"answer\": {\"name\": \"first_radio_answer\"},\n",
512+
" \"answer\": {\"name\": \"first_radio_answer\",\n",
513513
" \"classifications\" : [\n",
514514
" {\"name\": \"sub_radio_question\", \"answer\": {\"name\": \"first_sub_radio_answer\"}}\n",
515515
" ]\n",
516+
" }\n",
516517
"}\n",
517518
"\n",
518519
"# Python Annotation\n",

‎examples/basics/ontologies.ipynb‎

Lines changed: 5 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -71,7 +71,7 @@
7171
"metadata": {},
7272
"source": [
7373
"# Add your api key\n",
74-
"API_KEY = \"Enter api key here\"\n",
74+
"API_KEY = \"\"\n",
7575
"client = lb.Client(api_key=API_KEY)"
7676
],
7777
"cell_type": "code",
@@ -261,7 +261,7 @@
261261
"# Create normalized json with a bounding box and segmentation tool\n",
262262
"ontology_builder = lb.OntologyBuilder(tools=[\n",
263263
" lb.Tool(tool=lb.Tool.Type.BBOX, name=\"dog\"),\n",
264-
" lb.Tool(tool=lb.Tool.Type.SEGMENTATION, name=\"cat\"),\n",
264+
" lb.Tool(tool=lb.Tool.Type.RASTER_SEGMENTATION, name=\"cat\"),\n",
265265
"])\n",
266266
"# Creating an ontology from this is easy\n",
267267
"ontology = client.create_ontology(\"ontology-builder-ontology\",\n",
@@ -286,7 +286,7 @@
286286
"ontology_builder = lb.OntologyBuilder()\n",
287287
"# Append tools\n",
288288
"tool_dog = lb.Tool(tool=lb.Tool.Type.BBOX, name=\"dog\")\n",
289-
"tool_cat = lb.Tool(tool=lb.Tool.Type.SEGMENTATION, name=\"cat\")\n",
289+
"tool_cat = lb.Tool(tool=lb.Tool.Type.RASTER_SEGMENTATION, name=\"cat\")\n",
290290
"ontology_builder.add_tool(tool_dog)\n",
291291
"ontology_builder.add_tool(tool_cat)\n",
292292
"ontology = client.create_ontology(\"ontology-builder-ontology\",\n",
@@ -310,7 +310,7 @@
310310
"ontology_builder = lb.OntologyBuilder(\n",
311311
" tools=[\n",
312312
" lb.Tool(tool=lb.Tool.Type.BBOX, name=\"dog\"),\n",
313-
" lb.Tool(tool=lb.Tool.Type.SEGMENTATION,\n",
313+
" lb.Tool(tool=lb.Tool.Type.RASTER_SEGMENTATION,\n",
314314
" name=\"cat\",\n",
315315
" classifications=[\n",
316316
" lb.Classification(class_type=lb.Classification.Type.TEXT,\n",
@@ -370,7 +370,7 @@
370370
"source": [
371371
"bbox_tool = lb.Tool(tool=lb.Tool.Type.BBOX, name=\"dog_box\")\n",
372372
"poly_tool = lb.Tool(tool=lb.Tool.Type.POLYGON, name=\"dog_poly\")\n",
373-
"seg_tool = lb.Tool(tool=lb.Tool.Type.SEGMENTATION, name=\"dog_seg\")\n",
373+
"seg_tool = lb.Tool(tool=lb.Tool.Type.RASTER_SEGMENTATION, name=\"dog_seg\")\n",
374374
"point_tool = lb.Tool(tool=lb.Tool.Type.POINT, name=\"dog_center\")\n",
375375
"line_tool = lb.Tool(tool=lb.Tool.Type.LINE, name=\"dog_orientation\")\n",
376376
"ner_tool = lb.Tool(tool=lb.Tool.Type.NER, name=\"dog_reference\")\n",

‎examples/integrations/sam/meta_sam_labelbox.ipynb‎

Lines changed: 41 additions & 177 deletions
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