Merge pull request #719 from Labelbox/develop

v.3.27.2

Author: jtsodapop

.dockerignore

@@ -0,0 +1,19 @@
+__pycache__/
+*.py[cod]
+*$py.class
+.Python
+env
+pip-log.txt
+pip-delete-this-directory.txt
+.tox
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.log
+.git
+.mypy_cache
+.pytest_cache
+.hypothesis

CHANGELOG.md

@@ -1,5 +1,18 @@
 # Changelog
 
+# Version 3.27.2 (2022-10-04)
+
+### Added
+* Added deprecation warning for missing `media_type` in `create_project` in `Client`.
+
+### Changed
+* Updated docs for deprecated methods `_update_queue_mode` and `get_queue_mode` in `Project`
+    * Use the `queue_mode` attribute in `Project` to get and set the queue mode instead
+    * For more information, visit https://docs.labelbox.com/reference/migrating-to-workflows#upcoming-changes
+* Updated `project.export_labels` to support filtering by start/end time formats "YYYY-MM-DD" and "YYYY-MM-DD hh:mm:ss"
+
+### Fixed
+
 # Version 3.27.1 (2022-09-16)
 ### Changed
 * Removed `client.get_data_rows_for_global_keys` until further notice
@@ -17,7 +30,7 @@
 ### Changed
 * Increase scalar metric value limit to 100m
 * Added deprecation warnings when updating project `queue_mode`
-## Fixed
+### Fixed
 * Fix bug in `feature_confusion_matrix` and `confusion_matrix` causing FPs and FNs to be capped at 1 when there were no matching annotations 
 
 # Version 3.26.2 (2022-09-06)

Dockerfile

@@ -10,9 +10,9 @@ RUN apt install -y libsm6 \
                 libgl1-mesa-glx \
                 libgeos-dev
 
-WORKDIR /usr/src/labelbox
-COPY requirements.txt /usr/src/labelbox
+WORKDIR /usr/src/
+COPY requirements.txt /usr/src/
 RUN pip install -r requirements.txt
-COPY . /usr/src/labelbox
+COPY . /usr/src/
 
 RUN python setup.py install

docs/source/conf.py

@@ -17,11 +17,11 @@
 
 # -- Project information -----------------------------------------------------
 
-project = 'Labelbox Python API reference'
+project = 'Python SDK reference'
 copyright = '2021, Labelbox'
 author = 'Labelbox'
 
-release = '3.27.1'
+release = '3.27.2'
 
 # -- General configuration ---------------------------------------------------
 

examples/annotation_import/basics.ipynb

@@ -116,6 +116,7 @@
         "    ClassificationAnnotation, ClassificationAnswer\n",
         ")\n",
         "from labelbox.data.serialization import NDJsonConverter\n",
+        "from labelbox.schema.media_type import MediaType\n",
         "import uuid\n",
         "import json"
       ]
@@ -203,8 +204,14 @@
         "])\n",
         "\n",
         "\n",
-        "mal_project = client.create_project(name=\"image_mal_project\")\n",
-        "li_project = client.create_project(name=\"image_label_import_project\")\n",
+        "mal_project = client.create_project(\n",
+        "    name=\"image_mal_project\",\n",
+        "    media_type=MediaType.Image\n",
+        ")\n",
+        "li_project = client.create_project(\n",
+        "    name=\"image_label_import_project\",\n",
+        "    media_type=MediaType.Image\n",
+        ")\n",
         "\n",
         "\n",
         "dataset = client.create_dataset(name=\"annotation_import_demo_dataset\")\n",

examples/annotation_import/image.ipynb

@@ -81,16 +81,16 @@
       "execution_count": 1,
       "id": "4d63074b-2379-48af-b9d6-2a66190f03c4",
       "metadata": {
-        "id": "4d63074b-2379-48af-b9d6-2a66190f03c4",
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
+        "id": "4d63074b-2379-48af-b9d6-2a66190f03c4",
         "outputId": "2560882d-6542-4dda-c075-d197ef2da5e3"
       },
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stdout",
+          "output_type": "stream",
           "text": [
             "\u001b[K     |████████████████████████████████| 172 kB 9.3 MB/s \n",
             "\u001b[K     |████████████████████████████████| 6.3 MB 15.2 MB/s \n",
@@ -130,6 +130,7 @@
         "    ClassificationAnnotation, ClassificationAnswer\n",
         ")\n",
         "from labelbox.data.serialization import NDJsonConverter\n",
+        "from labelbox.schema.media_type import MediaType\n",
         "import uuid\n",
         "import json\n",
         "import numpy as np"
@@ -196,15 +197,15 @@
     },
     {
       "cell_type": "markdown",
+      "id": "49i_juOUr6av",
+      "metadata": {
+        "id": "49i_juOUr6av"
+      },
       "source": [
         "First, we create an ontology with all the possible tools and classifications supported for images. The official list of supported annotations to import can be found here:\n",
         "- [Model-Assisted Labeling](https://docs.labelbox.com/docs/model-assisted-labeling) (annotations/labels are not submitted)\n",
         "- [Ground Truth](https://docs.labelbox.com/docs/import-ground-truth) (annotations/labels are submitted)"
-      ],
-      "metadata": {
-        "id": "49i_juOUr6av"
-      },
-      "id": "49i_juOUr6av"
+      ]
     },
     {
       "cell_type": "code",
@@ -258,13 +259,13 @@
     },
     {
       "cell_type": "markdown",
-      "source": [
-        "To show the two different ways to upload annotations, we create two projects - one to showcase MAL (Model-Assisted Labeling) and one to showcase Label Import."
-      ],
+      "id": "1GdimALBuzRU",
       "metadata": {
         "id": "1GdimALBuzRU"
       },
-      "id": "1GdimALBuzRU"
+      "source": [
+        "To show the two different ways to upload annotations, we create two projects - one to showcase MAL (Model-Assisted Labeling) and one to showcase Label Import."
+      ]
     },
     {
       "cell_type": "code",
@@ -276,8 +277,14 @@
       "outputs": [],
       "source": [
         "# Create two Labelbox projects\n",
-        "mal_project = client.create_project(name=\"image_mal_project\")\n",
-        "li_project = client.create_project(name=\"image_label_import_project\")\n",
+        "mal_project = client.create_project(\n",
+        "    name=\"image_mal_project\",\n",
+        "    media_type=MediaType.Image\n",
+        ")\n",
+        "li_project = client.create_project(\n",
+        "    name=\"image_label_import_project\",\n",
+        "    media_type=MediaType.Image\n",
+        ")\n",
         "\n",
         "# Create one Labelbox dataset\n",
         "dataset = client.create_dataset(name=\"image_annotation_import_demo_dataset\")\n",
@@ -319,6 +326,12 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 33,
+      "id": "qzBqhV4Pv3yp",
+      "metadata": {
+        "id": "qzBqhV4Pv3yp"
+      },
+      "outputs": [],
       "source": [
         "point_annotation=ObjectAnnotation(\n",
         "    value=Point(x=882,y=159), # Coordinates for this point annotation\n",
@@ -363,13 +376,7 @@
         "    ),\n",
         "    name=\"mask\" # Name of the tool in your ontology\n",
         ")"
-      ],
-      "metadata": {
-        "id": "qzBqhV4Pv3yp"
-      },
-      "id": "qzBqhV4Pv3yp",
-      "execution_count": 33,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -383,6 +390,12 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 34,
+      "id": "f2RtQQPCymOB",
+      "metadata": {
+        "id": "f2RtQQPCymOB"
+      },
+      "outputs": [],
       "source": [
         "text_annotation=ClassificationAnnotation(\n",
         "    value=Text( # String value for the text annotation\n",
@@ -409,13 +422,7 @@
         "    ), \n",
         "    name=\"radio\" # Name of the classification in your ontology\n",
         ")"
-      ],
-      "metadata": {
-        "id": "f2RtQQPCymOB"
-      },
-      "id": "f2RtQQPCymOB",
-      "execution_count": 34,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -440,15 +447,14 @@
       },
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stderr",
+          "output_type": "stream",
           "text": [
             "/usr/local/lib/python3.7/dist-packages/labelbox/data/annotation_types/classification/classification.py:85: UserWarning: Dropdown classification is deprecated and will be removed in a future release\n",
             "  warnings.warn(\"Dropdown classification is deprecated and will be \"\n"
           ]
         },
         {
-          "output_type": "execute_result",
           "data": {
             "text/plain": [
               "{'annotations': [ObjectAnnotation(name='point', feature_schema_id=None, extra={}, value=Point(extra={}, x=882.0, y=159.0), classifications=[]),\n",
@@ -464,8 +470,9 @@
               " 'uid': None}"
             ]
           },
+          "execution_count": 35,
           "metadata": {},
-          "execution_count": 35
+          "output_type": "execute_result"
         }
       ],
       "source": [
@@ -518,30 +525,29 @@
     },
     {
       "cell_type": "code",
-      "source": [
-        "import copy # We import this python package so we can create copies of our hard-coded annotations and upload one copy to each"
-      ],
+      "execution_count": 16,
+      "id": "0U_cA2Cw0pH1",
       "metadata": {
         "id": "0U_cA2Cw0pH1"
       },
-      "id": "0U_cA2Cw0pH1",
-      "execution_count": 16,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "import copy # We import this python package so we can create copies of our hard-coded annotations and upload one copy to each"
+      ]
     },
     {
       "cell_type": "code",
       "execution_count": 39,
       "id": "53aaf87b-114f-4b56-a417-8c7cddc1f532",
       "metadata": {
-        "id": "53aaf87b-114f-4b56-a417-8c7cddc1f532",
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
+        "id": "53aaf87b-114f-4b56-a417-8c7cddc1f532",
         "outputId": "e525feac-9f8e-49e7-95d0-33932998b0bd"
       },
       "outputs": [
         {
-          "output_type": "execute_result",
           "data": {
             "text/plain": [
               "[{'classifications': [],\n",
@@ -620,8 +626,9 @@
               "  'uuid': '7e92e01b-740d-48b4-935e-560ba0b63fa5'}]"
             ]
           },
+          "execution_count": 39,
           "metadata": {},
-          "execution_count": 39
+          "output_type": "execute_result"
         }
       ],
       "source": [
@@ -663,8 +670,8 @@
       },
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stdout",
+          "output_type": "stream",
           "text": [
             "Errors: []\n"
           ]
@@ -702,15 +709,14 @@
       "execution_count": 36,
       "id": "e8d4e99b-ad7e-48b9-8073-afb764d7c5b4",
       "metadata": {
-        "id": "e8d4e99b-ad7e-48b9-8073-afb764d7c5b4",
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
+        "id": "e8d4e99b-ad7e-48b9-8073-afb764d7c5b4",
         "outputId": "704fac54-8f45-46f0-ce2d-3769c5b11f23"
       },
       "outputs": [
         {
-          "output_type": "execute_result",
           "data": {
             "text/plain": [
               "[{'classifications': [],\n",
@@ -789,8 +795,9 @@
               "  'uuid': 'f413b3a2-1e71-473c-b3b0-c952791284df'}]"
             ]
           },
+          "execution_count": 36,
           "metadata": {},
-          "execution_count": 36
+          "output_type": "execute_result"
         }
       ],
       "source": [
@@ -832,8 +839,8 @@
       },
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stdout",
+          "output_type": "stream",
           "text": [
             "Errors: []\n"
           ]

examples/annotation_import/pdf_mal.ipynb

@@ -88,6 +88,7 @@
     "    ClassificationAnnotation, ClassificationAnswer\n",
     ")\n",
     "from labelbox.data.serialization import NDJsonConverter\n",
+    "from labelbox.schema.media_type import MediaType\n",
     "import uuid\n",
     "import json"
    ]
@@ -208,7 +209,7 @@
    "outputs": [],
    "source": [
     "# Create two Labelbox projects\n",
-    "mal_project = client.create_project(name=\"pdf_mal_project\")\n",
+    "mal_project = client.create_project(name=\"pdf_mal_project\", media_type=MediaType.Document)\n",
     "\n",
     "# Create one Labelbox dataset\n",
     "dataset = client.create_dataset(name=\"pdf_annotation_import_demo_dataset\")\n",