Formatting a bulk import CSV

You can use the import method to create a product set and products with reference images all at the same time using a CSV file. This page describes how you format the CSV file.

Creating your reference images

Reference images are images containing various views of your products. The following recommendations apply:

  • Make sure the size of the file doesn't exceed the maximum size (20MB).
  • Consider viewpoints that logically highlight the product and contain relevant visual information.
  • Create reference images that supplement any missing viewpoints. For example, if you only have images of the right shoe in a pair, provide mirrored versions of those files as the left shoe.
  • Upload the highest resolution image available.
  • Show the product against a white background.
  • Convert PNGs with transparent backgrounds to a solid background.

Images must be stored in a Google Cloud Storage bucket. If you're authenticating your image create call with an API key, the bucket must be public. If you're authenticating with a service account, that service account must have read access on the bucket.

CSV formatting guidelines

To use the import method, both the CSV file and the images it points to must be in a Google Cloud Storage bucket. CSV files are limited to a maximum of 20000 lines. To import more images, split them into multiple CSV files.

The CSV file must contain one image per line and contain the following columns:

  1. image-uri: The Google Cloud Storage URI of the reference image.
  2. image-id: Optional. A unique value if you supply it. Otherwise, the system will assign a unique value.
  3. product-set-id: A unique identifier for the product set to import the images into.
  4. product-id: A user-defined ID for the product identified by the reference image. A product-id can be associated with multiple reference images.

  5. product-category: Allowed values are homegoods-v2, apparel-v2, toys-v2, and packagedgoods-v1 (beta, v1p4beta1 endpoint only)*; the category for the product identified by the reference image. Inferred by the system if not specified in the create request. Allowed values are also listed in the productCategory reference documentation.

  6. product-display-name: Optional. If you don't provide a name for the product displayName will be set to " ". You can update this value later.

  7. labels: Optional. A string (with quotation marks) of key-value pairs that describe the products in the reference image. For example:

    • "category=shoes"
    • "color=black,style=formal"

      Vision Product Search also allows you to provide multiple values for a single key. For example:

    • "category=shoes,category=heels"

    • "color=black,style=formal,style=mens"

  8. bounding-poly: Optional. Specifies the area of interest in the reference image. If a bounding box is not specified:

    1. Bounding boxes for the image are inferred by the Vision API; multiple regions in a single image may be indexed if multiple products are detected by the API.
    2. The line must end with a comma.

    See the example below for a product without a bounding poly specified.

    If you include a bounding box, the boundingPoly column should contain an even number of comma-separated numbers, with the format p1_x,p1_y,p2_x,p2_y,...,pn_x,pn_y. An example line looks like this: 0.1,0.1,0.9,0.1,0.9,0.9,0.1,0.9.

    To define a bounding box with the actual pixel values of your image use non-negative integers. Thus, you could express bounding boxes in 1000 pixel by 1000 pixel images in the following way:

    "gs://example-reference-images/10001-001/10001-001_A.jpg","img001","sample-set-summer","sample-product-123","tan summer bag","apparel","style=womens,color=tan","100,150,450,150,450,550,100,550"
    "gs://example-reference-images/10001-001/10001-001_A.jpg","img001","sample-set-summer","sample-product-456","blue summer bag","apparel","style=womens,color=blue","670,790,980,790,980,920,670,920"
    "gs://example-reference-images/10002-002/10002-002_B.jpg","img002","sample-set-summer","sample-product-123","apparel",,,
    

    Vision Product Search also allows you to use normalized values for bounding boxes. Define a bounding box using normalized values with float values in [0, 1].

    Using normalized values, the above reference image rows could also be expressed as:

    "gs://example-reference-images/10001-001/10001-001_A.jpg","img001","sample-set-summer","sample-product-123","tan summer bag","apparel","style=womens,color=tan","0.10,0.15,0.45,0.15,0.45,0.55,0.10,0.55"
    "gs://example-reference-images/10001-001/10001-001_A.jpg","img001","sample-set-summer","sample-product-456","blue summer bag","apparel","style=womens,color=blue","0.67,0.79,0.98,0.79,0.98,0.92,0.67,0.92"
    "gs://example-reference-images/10002-002/10002-002_B.jpg","img002","sample-set-summer","sample-product-123","apparel",,,
    
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