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[SN-145] removed buffered stream mentioning #1662

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Merged
merged 1 commit into from
Jun 7, 2024
Merged

[SN-145] removed buffered stream mentioning #1662

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2 changes: 1 addition & 1 deletion examples/annotation_import/pdf.ipynb
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Expand Up @@ -282,7 +282,7 @@
},
{
"metadata": {},
"source": "client.enable_experimental = True\ntask = lb.DataRow.export(client=client, global_keys=[global_key])\ntask.wait_till_done()\nstream = task.get_stream()\n\ntext_layer = \"\"\nfor output in stream:\n output_json = json.loads(output.json_str)\n text_layer = output_json[\"media_attributes\"][\"text_layer_url\"]\nprint(text_layer)",
"source": "client.enable_experimental = True\ntask = lb.DataRow.export(client=client, global_keys=[global_key])\ntask.wait_till_done()\nstream = task.get_buffered_stream()\n\ntext_layer = \"\"\nfor output in stream:\n output_json = json.loads(output.json)\n text_layer = output_json[\"media_attributes\"][\"text_layer_url\"]\nprint(text_layer)",
"cell_type": "code",
"outputs": [],
"execution_count": null
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4 changes: 2 additions & 2 deletions examples/basics/batches.ipynb
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Expand Up @@ -121,7 +121,7 @@
},
{
"metadata": {},
"source": "client.enable_experimental = True\n\nexport_task = dataset.export()\nexport_task.wait_till_done()\n\ndata_rows = []\n\n\ndef json_stream_handler(output: lb.JsonConverterOutput):\n data_row = json.loads(output.json_str)\n data_rows.append(data_row)\n\n\nif export_task.has_errors():\n export_task.get_stream(converter=lb.JsonConverter(),\n stream_type=lb.StreamType.ERRORS).start(\n stream_handler=lambda error: print(error))\n\nif export_task.has_result():\n export_json = export_task.get_stream(\n converter=lb.JsonConverter(), stream_type=lb.StreamType.RESULT).start(\n stream_handler=json_stream_handler)",
"source": "client.enable_experimental = True\n\nexport_task = dataset.export()\nexport_task.wait_till_done()\n\ndata_rows = []\n\n\ndef json_stream_handler(output: lb.BufferedJsonConverterOutput):\n data_row = json.loads(output.json)\n data_rows.append(data_row)\n\n\nif export_task.has_errors():\n export_task.get_buffered_stream(stream_type=lb.StreamType.ERRORS).start(\n stream_handler=lambda error: print(error))\n\nif export_task.has_result():\n export_json = export_task.get_buffered_stream(\n stream_type=lb.StreamType.RESULT).start(\n stream_handler=json_stream_handler)",
"cell_type": "code",
"outputs": [],
"execution_count": null
Expand Down Expand Up @@ -254,7 +254,7 @@
},
{
"metadata": {},
"source": "data_rows = []\n\n\ndef json_stream_handler(output: lb.JsonConverterOutput):\n data_row = json.loads(output.json_str)\n data_rows.append(data_row)\n\n\nif export_task.has_errors():\n export_task.get_stream(converter=lb.JsonConverter(),\n stream_type=lb.StreamType.ERRORS).start(\n stream_handler=lambda error: print(error))\n\nif export_task.has_result():\n export_json = export_task.get_stream(\n converter=lb.JsonConverter(), stream_type=lb.StreamType.RESULT).start(\n stream_handler=json_stream_handler)",
"source": "data_rows = []\n\n\ndef json_stream_handler(output: lb.BufferedJsonConverterOutput):\n data_row = json.loads(output.json)\n data_rows.append(data_row)\n\n\nif export_task.has_errors():\n export_task.get_buffered_stream(stream_type=lb.StreamType.ERRORS).start(\n stream_handler=lambda error: print(error))\n\nif export_task.has_result():\n export_json = export_task.get_buffered_stream(\n stream_type=lb.StreamType.RESULT).start(\n stream_handler=json_stream_handler)",
"cell_type": "code",
"outputs": [],
"execution_count": null
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2 changes: 1 addition & 1 deletion examples/basics/custom_embeddings.ipynb
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Expand Up @@ -102,7 +102,7 @@
},
{
"metadata": {},
"source": "data_rows = []\n\n\ndef json_stream_handler(output: lb.JsonConverterOutput):\n data_row = json.loads(output.json_str)\n data_rows.append(data_row)\n\n\nif export_task.has_errors():\n export_task.get_stream(converter=lb.JsonConverter(),\n stream_type=lb.StreamType.ERRORS).start(\n stream_handler=lambda error: print(error))\n\nif export_task.has_result():\n export_json = export_task.get_stream(\n converter=lb.JsonConverter(), stream_type=lb.StreamType.RESULT).start(\n stream_handler=json_stream_handler)",
"source": "data_rows = []\n\n\ndef json_stream_handler(output: lb.BufferedJsonConverterOutput):\n data_row = json.loads(output.json)\n data_rows.append(data_row)\n\n\nif export_task.has_errors():\n export_task.get_buffered_stream(stream_type=lb.StreamType.ERRORS).start(\n stream_handler=lambda error: print(error))\n\nif export_task.has_result():\n export_json = export_task.get_buffered_stream(\n stream_type=lb.StreamType.RESULT).start(\n stream_handler=json_stream_handler)",
"cell_type": "code",
"outputs": [],
"execution_count": null
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4 changes: 2 additions & 2 deletions examples/basics/data_rows.ipynb
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Expand Up @@ -113,7 +113,7 @@
},
{
"metadata": {},
"source": "data_rows = []\n\n\ndef json_stream_handler(output: lb.JsonConverterOutput):\n data_row = json.loads(output.json_str)\n data_rows.append(data_row)\n\n\nif export_task.has_errors():\n export_task.get_stream(converter=lb.JsonConverter(),\n stream_type=lb.StreamType.ERRORS).start(\n stream_handler=lambda error: print(error))\n\nif export_task.has_result():\n export_json = export_task.get_stream(\n converter=lb.JsonConverter(), stream_type=lb.StreamType.RESULT).start(\n stream_handler=json_stream_handler)",
"source": "data_rows = []\n\n\ndef json_stream_handler(output: lb.BufferedJsonConverterOutput):\n data_row = json.loads(output.json)\n data_rows.append(data_row)\n\n\nif export_task.has_errors():\n export_task.get_buffered_stream(stream_type=lb.StreamType.ERRORS).start(\n stream_handler=lambda error: print(error))\n\nif export_task.has_result():\n export_json = export_task.get_buffered_stream(\n stream_type=lb.StreamType.RESULT).start(\n stream_handler=json_stream_handler)",
"cell_type": "code",
"outputs": [],
"execution_count": null
Expand Down Expand Up @@ -236,7 +236,7 @@
},
{
"metadata": {},
"source": "# Fetch a data row from the first dataset example\nts = dataset.export()\nts.wait_till_done()\nDATA_ROW_ID = [json.loads(output.json_str) for output in ts.get_stream()\n ][0][\"data_row\"][\"id\"]\nGLOBAL_KEY = [json.loads(output.json_str) for output in ts.get_stream()\n ][0][\"data_row\"][\"global_key\"]\n\nprint(f\"Pick either a data row id : {DATA_ROW_ID} or global key: {GLOBAL_KEY}\")",
"source": "# Fetch a data row from the first dataset example\nts = dataset.export()\nts.wait_till_done()\nDATA_ROW_ID = [json.loads(output.json) for output in ts.get_buffered_stream()\n ][0][\"data_row\"][\"id\"]\nGLOBAL_KEY = [json.loads(output.json) for output in ts.get_buffered_stream()\n ][0][\"data_row\"][\"global_key\"]\n\nprint(f\"Pick either a data row id : {DATA_ROW_ID} or global key: {GLOBAL_KEY}\")",
"cell_type": "code",
"outputs": [],
"execution_count": null
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4 changes: 2 additions & 2 deletions examples/exports/composite_mask_export.ipynb
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Expand Up @@ -211,7 +211,7 @@
},
{
"metadata": {},
"source": "stream = export_task.get_stream()\n\nmask_tool_rgb_mapping = {}\n\nfor output in stream:\n # Parse the JSON string from the output\n output_json = json.loads(output.json_str)\n\n # Get the labels for the specified project ID or an empty list if the project ID is not found\n project_labels = (output_json[\"projects\"].get(PROJECT_ID,\n {}).get(\"labels\", []))\n\n # Iterate through each label\n for label in project_labels:\n # Get the list of annotations (objects) for the label\n annotations = label[\"annotations\"].get(\"objects\", [])\n\n # Iterate through each annotation\n for annotation in annotations:\n # Check if the annotation is of type \"ImageSegmentationMask\"\n if annotation.get(\"annotation_kind\") == \"ImageSegmentationMask\":\n # Add the color RGB information to the mapping dictionary\n mask_tool_rgb_mapping.setdefault(annotation[\"name\"], []).append(\n annotation[\"composite_mask\"][\"color_rgb\"])\n\nprint(mask_tool_rgb_mapping)",
"source": "stream = export_task.get_buffered_stream()\n\nmask_tool_rgb_mapping = {}\n\nfor output in stream:\n # Parse the JSON string from the output\n output_json = json.loads(output.json)\n\n # Get the labels for the specified project ID or an empty list if the project ID is not found\n project_labels = (output_json[\"projects\"].get(PROJECT_ID,\n {}).get(\"labels\", []))\n\n # Iterate through each label\n for label in project_labels:\n # Get the list of annotations (objects) for the label\n annotations = label[\"annotations\"].get(\"objects\", [])\n\n # Iterate through each annotation\n for annotation in annotations:\n # Check if the annotation is of type \"ImageSegmentationMask\"\n if annotation.get(\"annotation_kind\") == \"ImageSegmentationMask\":\n # Add the color RGB information to the mapping dictionary\n mask_tool_rgb_mapping.setdefault(annotation[\"name\"], []).append(\n annotation[\"composite_mask\"][\"color_rgb\"])\n\nprint(mask_tool_rgb_mapping)",
"cell_type": "code",
"outputs": [],
"execution_count": null
Expand Down Expand Up @@ -246,7 +246,7 @@
},
{
"metadata": {},
"source": "tools_frames_color = {}\nstream = export_task_video.get_stream()\n\n# Iterate over each output in the stream\nfor output in stream:\n output_json = json.loads(output.json_str)\n\n # Iterate over the labels in the specific project\n for dr in output_json[\"projects\"][VIDEO_PROJECT_ID][\"labels\"]:\n frames_data = dr[\"annotations\"][\"frames\"]\n\n # Iterate over each frame in the frames data\n for frame_key, frame_value in frames_data.items():\n\n # Iterate over each annotation in the frame\n for annotation_key, annotation_value in frame_value.items():\n if \"objects\" in annotation_key and annotation_value.values():\n\n # Iterate over each object in the annotation\n for object_key, object_value in annotation_value.items():\n if (object_value[\"annotation_kind\"] ==\n \"VideoSegmentationMask\"):\n # Update tools_frames_color with object information\n tools_frames_color.setdefault(\n object_value[\"name\"], []).append({\n frame_key:\n object_value[\"composite_mask\"]\n [\"color_rgb\"]\n })\n\nprint(tools_frames_color)",
"source": "tools_frames_color = {}\nstream = export_task_video.get_buffered_stream()\n\n# Iterate over each output in the stream\nfor output in stream:\n output_json = json.loads(output.json)\n\n # Iterate over the labels in the specific project\n for dr in output_json[\"projects\"][VIDEO_PROJECT_ID][\"labels\"]:\n frames_data = dr[\"annotations\"][\"frames\"]\n\n # Iterate over each frame in the frames data\n for frame_key, frame_value in frames_data.items():\n\n # Iterate over each annotation in the frame\n for annotation_key, annotation_value in frame_value.items():\n if \"objects\" in annotation_key and annotation_value.values():\n\n # Iterate over each object in the annotation\n for object_key, object_value in annotation_value.items():\n if (object_value[\"annotation_kind\"] ==\n \"VideoSegmentationMask\"):\n # Update tools_frames_color with object information\n tools_frames_color.setdefault(\n object_value[\"name\"], []).append({\n frame_key:\n object_value[\"composite_mask\"]\n [\"color_rgb\"]\n })\n\nprint(tools_frames_color)",
"cell_type": "code",
"outputs": [],
"execution_count": null
Expand Down
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