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PiperOrigin-RevId: 868718798

Author: tensorflower-gardener

official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/client/big_query_ops.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Copyright 2025 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2026 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.

official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/client/big_query_ops_test.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Copyright 2025 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2026 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.

official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/client/inference_pipeline.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Copyright 2025 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2026 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.
@@ -46,9 +46,9 @@
 OUTPUT_DIRECTORY = flags.DEFINE_string(
     "output_directory", None, "The path to the directory to save the results."
 )
-MODEL = flags.DEFINE_string("model", None, "Model name")
+MODEL_NAME = flags.DEFINE_string("model_name", None, "Model name")
 PREDICTION_THRESHOLD = flags.DEFINE_float(
-    "score", None, "Threshold to filter the prediction results"
+    "threshold", None, "Threshold to filter the prediction results"
 )
 SEARCH_RANGE_X = flags.DEFINE_integer(
     "search_range_x",
@@ -102,7 +102,7 @@ def main(_) -> None:
       for filepath in utils.files_paths(os.path.basename(input_directory))
   }
 
-  model_manager = TritonObjectDetector(model_name=MODEL.value)
+  model_manager = TritonObjectDetector(model_name=MODEL_NAME.value)
   tracking_manager = ObjectTracker(
       search_range=(SEARCH_RANGE_Y.value, SEARCH_RANGE_X.value),
       memory=MEMORY.value,

official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/client/object_tracking.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Copyright 2025 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2026 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.

official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/client/object_tracking_test.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Copyright 2025 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2026 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.

official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/client/run_images.sh

@@ -12,28 +12,20 @@ Steps Performed:
                              inference.
  --output_directory        : GCS directory where the model inference outputs will be
                              saved.
- --height                  : Height to which input images are resized for the Mask
-                             R-CNN model.
- --width                   : Width to which input images are resized for the Mask
-                             R-CNN model.
- --model                   : Name of the model to download and use for inference.
- --score                   : Confidence threshold for detections during
+ --model_name              : Name of the model to download and use for inference.
+ --threshold               : Confidence threshold for detections during
                              inference.
  --search_range_x          : Max pixel movement allowed in the X direction for
                              object tracking between missed frames.
  --search_range_y          : Max pixel movement allowed in the Y direction for
                              object tracking between missed frames.
-  --memory                 : Number of frames an object can be missed and still
+ --memory                  : Number of frames an object can be missed and still
                              be tracked.
-  --project_id             : Google Cloud Project ID for BigQuery operations.
-  --bq_dataset_id          : BigQuery Dataset ID where results will be stored.
-  --bq_table_id            : BigQuery Table ID where results will be stored.
-  --overwrite              : If set to True, overwrites the pre-existing
+ --project_id              : Google Cloud Project ID for BigQuery operations.
+ --bq_dataset_id           : BigQuery Dataset ID where results will be stored.
+ --bq_table_id             : BigQuery Table ID where results will be stored.
+ --overwrite               : If set to True, overwrites the pre-existing
                              BigQuery table.
-  --tracking_visualization : If set to True, visualizes the tracking results
-                             from the tracking algorithm.
-  --cropped_objects        : If set to True, crops the objects per category
-                             according to the prediction and tracking results.
 EOF
 #Activate the virtual environment
 source myenv/bin/activate
@@ -47,12 +39,12 @@ fi
 python inference_pipeline.py \
 	--input_directory=gs://recykal/TestData/SmallTestData \
 	--output_directory=gs://recykal/TestData/SmallTestData \
-	--model=detr_seg \
-	--score=0.50 \
+	--model_name=cn_segmentation_trt_model \
+	--threshold=0.50 \
 	--search_range_x=150 \
 	--search_range_y=20 \
 	--memory=3  \
 	--project_id=waste-identification-ml-330916 \
 	--bq_dataset_id=circularnet_dataset \
-	--bq_table_id=vinit_test_table1 \
+	--bq_table_id=test_table1 \
 	--overwrite=True

official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/client/triton_server_inference.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Copyright 2025 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2026 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.
@@ -249,8 +249,9 @@ def predict(
         raw_outputs, confidence_threshold, max_boxes
     )
 
-    # Scale to output dimensions
-    results = self._scale_bbox_and_masks(results, output_dims)
+    if results['labels'].any():
+      # Scale to output dimensions
+      results = self._scale_bbox_and_masks(results, output_dims)
 
     return results
 

official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/client/triton_server_inference_test.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Copyright 2025 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2026 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.

official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/client/utils.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# Copyright 2025 The TensorFlow Authors. All Rights Reserved.
+# Copyright 2026 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.
@@ -207,10 +207,10 @@ def _crop_objects_from_masks(
   Returns:
     A list of numpy arrays, where each array is a cropped object.
   """
-  cropped_objects = []
-  for m in masks.astype(int):
-    cropped_object = np.where(np.expand_dims(m, -1), image, 0)
-    cropped_objects.append(cropped_object)
+  cropped_objects = [
+      np.where(np.expand_dims(m, -1), image, 0) for m in masks.astype(int)
+  ]
+
   return cropped_objects
 
 

official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/server/triton_inference_server.sh

@@ -15,9 +15,9 @@ fi
 
 # Define an associative array with model names and their URLs
 declare -A models=(
-  ["CircularNet_rfdetr_seg_preview_v1"]="https://storage.googleapis.com/"\
+  ["CircularNet_Segmentation_Model_v1"]="https://storage.googleapis.com/"\
 "tf_model_garden/vision/waste_identification_ml/"\
-"CircularNet_rfdetr_seg_preview_v1.zip"
+"CircularNet_Segmentation_Model_v1.zip"
 )
 
 # Download, unzip, and organize models
@@ -38,6 +38,4 @@ echo "Starting Triton server in a screen session."
 # Start Triton server
 screen -dmS server bash -c '
 sudo docker run --gpus all --rm -p 8000:8000 -p 8001:8001 -p 8002:8002 \
--v ${PWD}/model_repository:/models \
-nvcr.io/nvidia/tritonserver:25.03-py3 \
-tritonserver --model-repository=/models --backend-config=pytorch,version=2'
+-v ${PWD}/model_repository:/models nvcr.io/nvidia/tritonserver:25.05-py3 tritonserver --model-repository=/models'