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PiperOrigin-RevId: 637905830

Author: tensorflower-gardener

official/projects/waste_identification_ml/docker_solution/prediction_pipeline/big_query_schema.py

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+# Copyright 2024 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Stores big query table schema."""
+
+from google.cloud import bigquery
+
+# Create the table within the dataset
+SCHEMA_1 = [
+    bigquery.SchemaField("detection_scores", "FLOAT", mode="REQUIRED"),
+    bigquery.SchemaField("detection_classes_names", "STRING", mode="REQUIRED"),
+    bigquery.SchemaField("detection_classes", "INTEGER", mode="REQUIRED"),
+    bigquery.SchemaField("area", "INTEGER", mode="REQUIRED"),
+    bigquery.SchemaField("bbox_0", "INTEGER", mode="REQUIRED"),
+    bigquery.SchemaField("bbox_1", "INTEGER", mode="REQUIRED"),
+    bigquery.SchemaField("bbox_2", "INTEGER", mode="REQUIRED"),
+    bigquery.SchemaField("bbox_3", "INTEGER", mode="REQUIRED"),
+    bigquery.SchemaField("convex_area", "INTEGER", mode="REQUIRED"),
+    bigquery.SchemaField("bbox_area", "INTEGER", mode="REQUIRED"),
+    bigquery.SchemaField("major_axis_length", "FLOAT", mode="REQUIRED"),
+    bigquery.SchemaField("minor_axis_length", "FLOAT", mode="REQUIRED"),
+    bigquery.SchemaField("eccentricity", "FLOAT", mode="REQUIRED"),
+    bigquery.SchemaField("y", "FLOAT", mode="REQUIRED"),
+    bigquery.SchemaField("x", "FLOAT", mode="REQUIRED"),
+    bigquery.SchemaField("image_name", "STRING", mode="REQUIRED"),
+    bigquery.SchemaField("color", "STRING", mode="REQUIRED"),
+    bigquery.SchemaField("creation_timestamp", "STRING", mode="REQUIRED"),
+    bigquery.SchemaField("video_name", "STRING", mode="REQUIRED"),
+]
+
+# Create the table for object count grouped by object class and color
+SCHEMA_2 = [
+    bigquery.SchemaField("colors_group", "STRING", mode="REQUIRED"),
+    bigquery.SchemaField("particle", "INTEGER", mode="REQUIRED"),
+    bigquery.SchemaField("detection_classes_group", "INTEGER", mode="REQUIRED"),
+    bigquery.SchemaField("material", "STRING", mode="REQUIRED"),
+    bigquery.SchemaField("material_form", "STRING", mode="REQUIRED"),
+    bigquery.SchemaField("creation_timestamp", "STRING", mode="REQUIRED"),
+    bigquery.SchemaField("video_name", "STRING", mode="REQUIRED"),
+]