Add preliminary thesis structure
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@@ -33,7 +33,7 @@
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},
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 2,
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"id": "cfd472e0",
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"metadata": {},
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"outputs": [],
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@@ -99727,16 +99727,48 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 4,
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"id": "9e57cd86",
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"metadata": {},
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"outputs": [],
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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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"Downloading labels from Label Studio...\n",
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"Download complete\n",
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"Loading labels for field 'ground_truth'...\n",
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" 100% |█████████████████| 639/639 [1.1s elapsed, 0s remaining, 576.6 samples/s] \n"
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]
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},
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{
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"data": {
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"text/html": [
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"\n",
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" <iframe\n",
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" width=\"100%\"\n",
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" height=\"800\"\n",
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" src=\"http://localhost:5151/?context=ipython&subscription=f8354b3b-60f0-418a-a49d-f664312d58cc\"\n",
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" frameborder=\"0\"\n",
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" allowfullscreen\n",
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" \n",
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" ></iframe>\n",
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" "
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],
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"text/plain": [
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"<IPython.lib.display.IFrame at 0x7fe94ac02bd0>"
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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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"source": [
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"anno_key = \"labelstudio_basic_recipe\"\n",
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"\n",
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"# Merge annotations back into FiftyOne dataset\n",
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"dataset = fo.load_dataset(\"dataset\")\n",
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"dataset.load_annotations(anno_key)\n",
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"dataset.load_annotations(anno_key, url=LABEL_STUDIO_URL, api_key=API_KEY)\n",
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"\n",
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"# Load the view that was annotated in the App\n",
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"view = dataset.load_annotation_view(anno_key)\n",
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@@ -99745,12 +99777,45 @@
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"# Step 6: Cleanup\n",
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"\n",
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"# Delete tasks from Label Studio\n",
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"results = dataset.load_annotation_results(anno_key)\n",
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"results.cleanup()\n",
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"#results = dataset.load_annotation_results(anno_key)\n",
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"#results.cleanup()\n",
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"\n",
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"# Delete run record (not the labels) from FiftyOne\n",
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"#dataset.delete_annotation_run(anno_key)"
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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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"id": "65f64f8b",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Delete tasks from Label Studio\n",
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"#results = dataset.load_annotation_results(anno_key)\n",
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"#results.cleanup()\n",
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"\n",
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"# Delete run record (not the labels) from FiftyOne\n",
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"dataset.delete_annotation_run(anno_key)"
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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": 6,
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"id": "ef4fd54f",
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"metadata": {},
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"outputs": [],
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"source": [
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"dataset.save()"
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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": null,
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"id": "b099682d",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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