{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<!-- Autogenerated by `scripts/make_examples.py` -->\n",
"<table align=\"left\">\n",
" <td>\n",
" <a target=\"_blank\" href=\"https://colab.research.google.com/github/voxel51/fiftyone-examples/blob/master/examples/Tips_and_Tricks_CLI.ipynb\">\n",
" <img src=\"https://user-images.githubusercontent.com/25985824/104791629-6e618700-5769-11eb-857f-d176b37d2496.png\" height=\"32\" width=\"32\">\n",
" Try in Google Colab\n",
" </a>\n",
" </td>\n",
" <td>\n",
" <a target=\"_blank\" href=\"https://nbviewer.jupyter.org/github/voxel51/fiftyone-examples/blob/master/examples/Tips_and_Tricks_CLI.ipynb\">\n",
" <img src=\"https://user-images.githubusercontent.com/25985824/104791634-6efa1d80-5769-11eb-8a4c-71d6cb53ccf0.png\" height=\"32\" width=\"32\">\n",
" Share via nbviewer\n",
" </a>\n",
" </td>\n",
" <td>\n",
" <a target=\"_blank\" href=\"https://github.com/voxel51/fiftyone-examples/blob/master/examples/Tips_and_Tricks_CLI.ipynb\">\n",
" <img src=\"https://user-images.githubusercontent.com/25985824/104791633-6efa1d80-5769-11eb-8ee3-4b2123fe4b66.png\" height=\"32\" width=\"32\">\n",
" View on GitHub\n",
" </a>\n",
" </td>\n",
" <td>\n",
" <a href=\"https://github.com/voxel51/fiftyone-examples/raw/master/examples/Tips_and_Tricks_CLI.ipynb\" download>\n",
" <img src=\"https://user-images.githubusercontent.com/25985824/104792428-60f9cc00-576c-11eb-95a4-5709d803023a.png\" height=\"32\" width=\"32\">\n",
" Download notebook\n",
" </a>\n",
" </td>\n",
"</table>\n"
]
},
{
"cell_type": "markdown",
"id": "abc8d229",
"metadata": {},
"source": [
"# FiftyOne CLI Tips and Tricks"
]
},
{
"cell_type": "markdown",
"id": "a1337b1d",
"metadata": {},
"source": [
" Leveraging CLI commands can be a powerful way to improve your workflow. We will do a quick dive on some powerful options FiftyOne provides that can save you time on your next computer vision project. Let's take a look: "
]
},
{
"cell_type": "markdown",
"id": "4ce1dec5",
"metadata": {},
"source": [
"## Tab Completion"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "06402547",
"metadata": {},
"outputs": [],
"source": [
"!eval \"$(register-python-argcomplete fiftyone)\""
]
},
{
"cell_type": "markdown",
"id": "e1bc2fa7",
"metadata": {},
"source": [
"## Load Quickstart for demo"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "18b79d81",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Downloading dataset to '/home/dan/fiftyone/quickstart'\n",
"Downloading dataset...\n",
" 100% |████| 187.5Mb/187.5Mb [775.2ms elapsed, 0s remaining, 241.9Mb/s] \n",
"Extracting dataset...\n",
"Parsing dataset metadata\n",
"Found 200 samples\n",
"Dataset info written to '/home/dan/fiftyone/quickstart/info.json'\n",
"Loading 'quickstart'\n",
" 100% |█████████████████| 200/200 [2.1s elapsed, 0s remaining, 94.8 samples/s] \n",
"Dataset 'quickstart' created\n"
]
}
],
"source": [
"import fiftyone as fo\n",
"import fiftyone.zoo as foz\n",
"\n",
"dataset = foz.load_zoo_dataset(\"quickstart\")\n",
"dataset.persistent = True"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "14784f20",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" <iframe\n",
" width=\"100%\"\n",
" height=\"800\"\n",
" src=\"http://localhost:5151/?notebook=True&subscription=36560c76-fe0c-445f-b9c4-e9d311ff4d1f\"\n",
" frameborder=\"0\"\n",
" allowfullscreen\n",
" \n",
" ></iframe>\n",
" "
],
"text/plain": [
"<IPython.lib.display.IFrame at 0x7f2aa56559c0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"session = fo.launch_app(dataset)"
]
},
{
"cell_type": "markdown",
"id": "b16d799b",
"metadata": {},
"source": [
"## List Datasets"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "f3af938e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2023.08.24.12.07.07\r\n",
"evaluate-detections-tutorial\r\n",
"malaria-cell-images\r\n",
"malaria-cell-images2\r\n",
"open-images-v6-validation-200\r\n",
"quickstart\r\n",
"tips+tricks\r\n",
"tips_and_tricks\r\n"
]
}
],
"source": [
"!fiftyone datasets list"
]
},
{
"cell_type": "markdown",
"id": "2e2ff6d2",
"metadata": {},
"source": [
"## Sort By Date Created and Delete Old"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "bed7d368",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"name created_at last_loaded_at version persistent media_type tags num_samples\r\n",
"----------------------------- ------------------- ------------------- --------- ------------ ------------ ------ -------------\r\n",
"quickstart 2023-08-24 20:40:54 2023-08-24 20:41:01 0.21.6 ✓ image 200\r\n",
"tips_and_tricks 2023-08-24 18:47:00 2023-08-24 20:30:03 0.21.6 ✓ image 200\r\n",
"2023.08.24.12.07.07 2023-08-24 16:07:07 2023-08-24 16:09:21 0.21.6 ✓ image 15474\r\n",
"malaria-cell-images2 2023-08-21 20:59:22 2023-08-21 21:08:58 0.21.4 ✓ image 55120\r\n",
"open-images-v6-validation-200 2023-06-29 19:17:58 2023-08-24 17:44:21 0.21.6 ✓ image 200\r\n",
"malaria-cell-images 2023-06-29 15:32:21 2023-06-29 17:10:03 0.21.0 ✓ image 27558\r\n",
"evaluate-detections-tutorial 2023-06-28 20:27:39 2023-08-24 17:55:04 0.21.6 ✓ image 5005\r\n",
"tips+tricks ??? ??? ??? ??? ??? ??? ???\r\n"
]
}
],
"source": [
"!fiftyone datasets info --sort-by created_at"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "3f058dcf",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Dataset '2023.08.24.11.30.28' deleted\r\n"
]
}
],
"source": [
"!fiftyone datasets delete NAME"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "c5664ea9",
"metadata": {},
"outputs": [],
"source": [
"# Delete all non-persistent datasets\n",
"!fiftyone datasets delete --non-persistent"
]
},
{
"cell_type": "markdown",
"id": "fc87e50e",
"metadata": {},
"source": [
"## Grab Quick Information of Your Dataset"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "32a17c64",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"key value\r\n",
"------------- -------\r\n",
"samples_count 200\r\n",
"samples_bytes 1270762\r\n",
"samples_size 1.2MB\r\n",
"total_bytes 1270762\r\n",
"total_size 1.2MB\r\n"
]
}
],
"source": [
"!fiftyone datasets stats quickstart"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "5b4a50e5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Name: quickstart\r\n",
"Media type: image\r\n",
"Num samples: 200\r\n",
"Persistent: True\r\n",
"Tags: []\r\n",
"Sample fields:\r\n",
" id: fiftyone.core.fields.ObjectIdField\r\n",
" filepath: fiftyone.core.fields.StringField\r\n",
" tags: fiftyone.core.fields.ListField(fiftyone.core.fields.StringField)\r\n",
" metadata: fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.metadata.ImageMetadata)\r\n",
" ground_truth: fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.labels.Detections)\r\n",
" uniqueness: fiftyone.core.fields.FloatField\r\n",
" predictions: fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.labels.Detections)\r\n"
]
}
],
"source": [
"!fiftyone datasets info quickstart"
]
},
{
"cell_type": "markdown",
"id": "a97d3c97",
"metadata": {},
"source": [
"## Draw on Labels to Samples and Store"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "0c3f2a9d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" 100% |█████████████████| 200/200 [19.7s elapsed, 0s remaining, 8.6 samples/s] \n",
"Rendered media written to 'drawn_labels'\n"
]
}
],
"source": [
"!fiftyone datasets draw -d drawn_labels -f predictions quickstart"
]
},
{
"cell_type": "markdown",
"id": "081d7674",
"metadata": {},
"source": [
"## Rename Dataset"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "fbb6352e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Dataset 'quickstart' renamed to 'tips_and_tricks'\r\n"
]
}
],
"source": [
"!fiftyone datasets rename quickstart tips_and_tricks"
]
},
{
"cell_type": "markdown",
"id": "b080cdd0",
"metadata": {},
"source": [
"## Plugins CLI"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "07987e7e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"plugin version enabled directory\r\n",
"-------- --------- --------- -----------\r\n"
]
}
],
"source": [
"!fiftyone plugins list"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "56d7a04b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"uri enabled builtin on_startup unlisted dynamic\r\n",
"------------------------------------------ --------- --------- ------------ ---------- ---------\r\n",
"@voxel51/operators/clone_selected_samples ✓ ✓ ✓\r\n",
"@voxel51/operators/clone_sample_field ✓ ✓ ✓\r\n",
"@voxel51/operators/rename_sample_field ✓ ✓ ✓\r\n",
"@voxel51/operators/delete_selected_samples ✓ ✓ ✓\r\n",
"@voxel51/operators/delete_sample_field ✓ ✓ ✓\r\n",
"@voxel51/operators/print_stdout ✓ ✓ ✓\r\n"
]
}
],
"source": [
"!fiftyone operators list"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "72a9b5e5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Downloading voxel51/fiftyone-plugins...\n",
" 311.4Mb [4.2s elapsed, ? remaining, 88.0Mb/s] "
]
}
],
"source": [
"!fiftyone plugins download \\\n",
" https://github.com/voxel51/fiftyone-plugins \\\n",
" --plugin-names @voxel51/hello-world"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "a609bff2",
"metadata": {},
"outputs": [],
"source": [
"!fiftyone plugins disable @voxel51/hello-world"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "bf32bc79",
"metadata": {},
"outputs": [],
"source": [
"!fiftyone plugins enable @voxel51/hello-world"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "a6d5beab",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" <iframe\n",
" width=\"100%\"\n",
" height=\"800\"\n",
" src=\"http://localhost:5151/?notebook=True&subscription=67108d81-3b5a-4e67-8cd8-979cfba9a405\"\n",
" frameborder=\"0\"\n",
" allowfullscreen\n",
" \n",
" ></iframe>\n",
" "
],
"text/plain": [
"<IPython.lib.display.IFrame at 0x7f69044a3ee0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r\n",
"Could not connect session, trying again in 10 seconds\r\n",
"\n"
]
}
],
"source": [
"# Try it yourself!\n",
"session = fo.launch_app(dataset)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7d6501e7",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}