Gecko [ v3.cesa.co.za ]

Name	Size	Permission	Date
__pycache__	[ DIR ]	drwxr-xr-x	2026-06-08 18:08
operations	[ DIR ]	drwxr-xr-x	2026-06-08 18:08
product_search	[ DIR ]	drwxr-xr-x	2026-06-08 18:08
__init__.py	910 B	-rw-r--r--	1980-01-01 08:00
__init__.yaml	1.85 KB	-rw-r--r--	1980-01-01 08:00
detect_document.yaml	2.07 KB	-rw-r--r--	1980-01-01 08:00
detect_faces.yaml	1.05 KB	-rw-r--r--	1980-01-01 08:00
detect_image_properties.yaml	1.08 KB	-rw-r--r--	1980-01-01 08:00
detect_labels.yaml	1.25 KB	-rw-r--r--	1980-01-01 08:00
detect_landmarks.yaml	1.27 KB	-rw-r--r--	1980-01-01 08:00
detect_logos.yaml	1.13 KB	-rw-r--r--	1980-01-01 08:00
detect_objects.yaml	763 B	-rw-r--r--	1980-01-01 08:00
detect_product.yaml	2.66 KB	-rw-r--r--	1980-01-01 08:00
detect_safe_search.yaml	1.3 KB	-rw-r--r--	1980-01-01 08:00
detect_text.yaml	1.65 KB	-rw-r--r--	1980-01-01 08:00
detect_text_pdf.yaml	1.87 KB	-rw-r--r--	1980-01-01 08:00
detect_text_tiff.yaml	1.86 KB	-rw-r--r--	1980-01-01 08:00
detect_web.yaml	1.41 KB	-rw-r--r--	1980-01-01 08:00
suggest_crop.yaml	2.01 KB	-rw-r--r--	1980-01-01 08:00

Rename

- release_tracks: [BETA, ALPHA]

help_text:
    brief: detect products within an image
    description: |
      detect products within an image
    examples: |
      To detect product in image 'gs://my-bucket/my-image.jpg' by searching in product set
      'my-product-set', in category 'toys', run:

$ {command} gs://my-bucket/my-image.jpg --product-set='my-product-set' --product-set-location=us-east1 --category='toys'

request:
    _COMMON_: request
    static_fields:
      requests.features.type: PRODUCT_SEARCH
    modify_request_hooks:
    - googlecloudsdk.command_lib.ml.vision.product_search.utils:AddProductSetToDetectProductRequest
    - googlecloudsdk.command_lib.ml.vision.product_search.utils:AddBoundingPolygonToDetectProductRequest

response:
    _COMMON_: response

arguments:
    params:
    - _COMMON_: args.image_field
    - _COMMON_: args.max_results_field
    - api_field: requests.imageContext.productSearchParams.productCategories
      arg_name: category
      help_text: Product category to search in.
      required: true
      choices:
      - arg_value: apparel
        enum_value: apparel
      - arg_value: homegoods
        enum_value: homegoods
      - arg_value: toys
        enum_value: toys
    - api_field: requests.imageContext.productSearchParams.filter
      arg_name: filter
      help_text: |-
        Filter expression to restrict search results based on product labels. ANDs of ORs of
        key-value expressions are supported, where expressions within an OR must
        have the same key. Expressions separated by AND must have different keys.
        An '=' should be used to connect the key and value. For example,
        '(color = red OR color = blue) AND brand = Google' is acceptable, but not
        '(color = red OR brand = Google)' or 'color: red'.
    - arg_name: bounding-polygon
      help_text: |-
        Bounding polygon around the areas of interest in the image. If it is not specified, system
        discretion will be applied. A bounding polygon can be specified by a list of vertices or
        normalized vertices. A vertex (x, y) represents a 2D point in the image. x, y are integers
        and are in the same scale as the original image. The normalized vertex coordinates are
        relative to orginal image and range from 0 to 1. For example,
        --bounding-polygon=0.,0.,0.,0.3,0.3,0.,0.3,0.3 specifies a polygon with 4 normalized
        vertices - (0., 0.), (0., 0.3), (0.3, 0.), (0.3, 0.3). Notice that the decimal point is
        needed for normalized vertex coordindates.
    additional_arguments_hook: googlecloudsdk.command_lib.ml.vision.product_search.utils:ProductSetArgsForDetectProduct
  output:
    format: json