{"record":{"id":"325063a6baa9839b","repo":"tensorflow/models","slug":"bucket-path-must-be-non-empty-starting-with-gs","errorCode":null,"errorMessage":"Bucket path must be non-empty starting with 'gs://'","messagePattern":"Bucket path must be non-empty starting with 'gs://'","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/client/inference_pipeline.py","lineNumber":101,"sourceCode":"\n_IMAGE_SAVING_WIDTH = 432\n_IMAGE_SAVING_HEIGHT = 432\n_TRACKING_IMAGE_WIDTH = 300\n_TRACKING_IMAGE_HEIGHT = 300\n# https://soft-matter.github.io/trackpy/dev/tutorial/adaptive-search.html\n_ADAPTIVE_STOP = 5\n_ADAPTIVE_STEP = 0.95\n\n\ndef main(_) -> None:\n  # Check if the input and output directories are valid.\n  if (\n      not INPUT_DIRECTORY.value\n      or not OUTPUT_DIRECTORY.value\n      or not INPUT_DIRECTORY.value.startswith(\"gs://\")\n      or not OUTPUT_DIRECTORY.value.startswith(\"gs://\")\n  ):\n    raise ValueError(\"Bucket path must be non-empty starting with 'gs://'\")\n\n  input_directory, prediction_folder, logger = (\n      utils.setup_logger_and_directories(input_dir=INPUT_DIRECTORY.value)\n  )\n  filepaths_to_capture_time_dict = {\n      filepath: utils.get_image_capture_time(filepath)\n      for filepath in utils.files_paths(os.path.basename(input_directory))\n  }\n\n  model_manager = TritonObjectDetector(model_name=MODEL_NAME.value)\n\n  tracking_manager = ObjectTracker(\n      search_range=(SEARCH_RANGE_Y.value, SEARCH_RANGE_X.value),\n      memory=MEMORY.value,\n      adaptive_stop=_ADAPTIVE_STOP,\n      adaptive_step=_ADAPTIVE_STEP,\n  )\n","sourceCodeStart":83,"sourceCodeEnd":119,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/client/inference_pipeline.py#L83-L119","documentation":"Error \"Bucket path must be non-empty starting with 'gs://'\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/projects/waste_identification_ml/Deploy/detr_cloud_deployment/client/inference_pipeline.py:101 when the library encounters an invalid state.","commonSituations":"See trigger scenarios.","solutions":[],"exampleFix":null,"handlingStrategy":null,"validationCode":null,"typeGuard":null,"tryCatchPattern":null,"preventionTips":[],"tags":[],"backgroundTag":null,"analyzedSha":"e006f5f0d534913e49c1f1dae87364039fa607e2","analyzedAt":"2026-08-24T14:09:15.576Z","schemaVersion":2},"datasetVersion":"2026-08-24T17:17:21.512Z"}