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Matt Sokoloff
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clear notebook cells
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‎examples/model_diagnostics/model_diagnostics_demo.ipynb‎

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@@ -80,7 +80,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": null,
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"id": "wooden-worship",
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"metadata": {
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"id": "wooden-worship"
@@ -108,22 +108,12 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": null,
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"id": "committed-richards",
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"metadata": {
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"id": "committed-richards"
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},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2021-09-13 09:27:18.654668: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
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"2021-09-13 09:27:18.655024: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA\n",
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"To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"import sys\n",
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"sys.path.append('../model_assisted_labeling')\n",
@@ -176,7 +166,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": null,
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"id": "economic-chase",
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"metadata": {
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"id": "economic-chase"
@@ -191,38 +181,20 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": null,
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"id": "affecting-myanmar",
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"metadata": {
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"id": "affecting-myanmar"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"WARNING:tensorflow:From ../model_assisted_labeling/image_model.py:17: load (from tensorflow.python.saved_model.loader_impl) is deprecated and will be removed in a future version.\n",
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"Instructions for updating:\n",
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"This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.loader.load or tf.compat.v1.saved_model.load. There will be a new function for importing SavedModels in Tensorflow 2.0.\n",
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"INFO:tensorflow:Restoring parameters from gs://cloud-tpu-checkpoints/mask-rcnn/1555659850/variables/variables\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2021-09-13 09:27:38.928229: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:196] None of the MLIR optimization passes are enabled (registered 0 passes)\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"client = Client(api_key=API_KEY)\n",
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"load_model() # initialize Tensorflow Model"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": null,
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"id": "modern-program",
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"metadata": {
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"id": "modern-program"
@@ -260,7 +232,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": null,
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"id": "blank-flower",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": null,
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"id": "asian-savings",
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"metadata": {
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"id": "asian-savings"
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},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "8178b64dc1864f4f833a29b904b7b5e1",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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" 0%| | 0/10 [00:00<?, ?it/s]"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"outputs": [],
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"source": [
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"predictions = LabelList()\n",
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"for (image_url, external_id) in notebook.tqdm(image_data[:10]):\n",
@@ -332,7 +289,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": null,
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"id": "received-nigeria",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": null,
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"id": "stopped-phrase",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Setting up: Diagnostics Demo\n",
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"Dataset Created: cktiom65aclzm0y896zeua5ne\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"print(f\"Setting up: {PROJECT_NAME}\")\n",
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"\n",
@@ -388,30 +336,10 @@
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": null,
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"id": "unavailable-egyptian",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"10it [00:00, 63358.07it/s]\n",
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"10it [00:00, 76818.75it/s]\n",
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"10it [00:00, 60963.72it/s]\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"<labelbox.data.annotation_types.collection.LabelList at 0x17c27fdc0>"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"outputs": [],
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"source": [
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"signer = lambda _bytes: client.upload_data(content=_bytes, sign=True)\n",
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"predictions.add_url_to_masks(signer) \\\n",
@@ -436,21 +364,12 @@
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"execution_count": null,
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"id": "subject-painting",
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"metadata": {
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"id": "subject-painting"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"AnnotationImportState.FINISHED \n",
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"\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"RUN_MAL = True\n",
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"if RUN_MAL:\n",
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": null,
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"id": "MV4U1W4H_eMq",
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"metadata": {
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"id": "MV4U1W4H_eMq"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"https://app.labelbox.com/go-label/cktiom4y2czqg0y9u9qqfdvhk\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"print(f\"https://app.labelbox.com/go-label/{project.uid}\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"execution_count": null,
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"id": "excited-seminar",
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"metadata": {
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"id": "excited-seminar"
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"execution_count": null,
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"id": "mental-minnesota",
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"metadata": {
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"id": "mental-minnesota"
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": null,
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"id": "static-coordinate",
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"metadata": {
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"id": "static-coordinate"
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"True"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"outputs": [],
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"source": [
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"lb_model_run.upsert_labels([label.uid for label in labels])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"execution_count": null,
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"id": "committed-fairy",
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"metadata": {
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"id": "committed-fairy"
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"execution_count": null,
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"id": "anonymous-addition",
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"metadata": {
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"id": "anonymous-addition"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"AnnotationImportState.FINISHED\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"upload_task = lb_model_run.add_predictions(f'diagnostics-import-{uuid.uuid4()}', NDJsonConverter.serialize(predictions))\n",
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"upload_task.wait_until_done()\n",
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"execution_count": null,
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"id": "zrll9K6Q9tGK",
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"metadata": {
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"id": "zrll9K6Q9tGK"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"https://app.labelbox.com/models/9c4cba6e-efb4-03f1-302e-d5718c4eca20/9c4cba6f-8ea1-0202-ec4e-528291bf932e/AllDatarowsSlice/25da00a5-e451-4dbd-824d-a0425ce94ffa?view=carousel\n",
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"https://app.labelbox.com/models/9c4cba6e-efb4-03f1-302e-d5718c4eca20/9c4cba6f-8ea1-0202-ec4e-528291bf932e/AllDatarowsSlice/3d20b8e6-5584-45fd-b0a4-021b3a16f25b?view=carousel\n",
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"https://app.labelbox.com/models/9c4cba6e-efb4-03f1-302e-d5718c4eca20/9c4cba6f-8ea1-0202-ec4e-528291bf932e/AllDatarowsSlice/45e6dab8-c55e-4761-b47f-5a1dd4204f4d?view=carousel\n",
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"https://app.labelbox.com/models/9c4cba6e-efb4-03f1-302e-d5718c4eca20/9c4cba6f-8ea1-0202-ec4e-528291bf932e/AllDatarowsSlice/746b2c7c-25e5-449e-8cce-50e4fcbb9ddd?view=carousel\n",
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"https://app.labelbox.com/models/9c4cba6e-efb4-03f1-302e-d5718c4eca20/9c4cba6f-8ea1-0202-ec4e-528291bf932e/AllDatarowsSlice/7c2bd1f4-7f31-48b4-bc0a-b99ed7533646?view=carousel\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"for idx, annotation_group in enumerate(lb_model_run.annotation_groups()):\n",
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" if idx == 5:\n",

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