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      Upload Images
      • 07 Apr 2025
      • 5 Minutes to read
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      Contents

      Upload Images

      • Updated on 07 Apr 2025
      • 5 Minutes to read
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      Article summary

      This article applies to these versions of LandingLens:

      LandingLensLandingLens on Snowflake
      ✓✓ (see exceptions below)

      After you create a project, upload images to it. LandingLens will train a model based on the images you upload and label.

      Supported Files Types

      File TypeMore Information
      PNGRecommended file type
      BMPN/A
      JPG/JPEGN/A
      TIF/TIFFTIFFs can be uploaded to LandingLens projects, and are converted to PNGs at upload.

      LandingLens offers limited support for running inference on TIFFs:
      • Cloud deployment: Supports inference but images won't display on the Deploy page.
      • LandingEdge: Supports inference. For multi-frame TIFFs, will run inference on the first frame.
      • Docker: Supports inference. For multi-frame TIFFs, will run inference on the first frame. 
      • Try model / Try this model: Does not support inference.
      MPOAn MPO file is a Multi-Picture Object file. It contains two JPG files that create a stereoscopic image when overlaid. When you upload an MPO file to LandingLens, LandingLens selects one of the two JPG files.

      Sometimes, a JPG from a smart phone might be interpreted as an MPO because it contains the main image and an embedded thumbnail. In this case, LandingLens selects the main image.
      Pascal VOCAvailable only for Object Detection projects. For more information, go to Upload Labeled Images to Object Detection Projects.

      If using LandingLens on Snowflake, uploading Pascal VOC files is not supported when loading images from Snowflake.
      Note:
      Do you have DICOM (Digital Imaging and Communications in Medicine) files or images in another non-supported file format? Convert them to PNGs first, and then upload them to LandingLens.

      Image Size

      When uploading images to LandingLens, the maximum image size is based on project type. All image size maximums are based on the number of pixels (and not based on image file size).

      Project TypeImage Size Maximum
      Object Detection100MP
      (images larger than 36MP will load very slowly in the user interface)
      Classification
      Anomaly Detection
      Visual Prompting
      Segmentation36MP
      Note:
      Images might be resized when training a model. For more information, go to Model Training.

      How Do I Know How Many Pixels My Image Has?

      The image size maximums are based on the number of pixels. You can see an image's dimensions in image editors like Photoshop and Illustrator. You can also see the dimensions directly on your computer, without needing to open the image in an application. See the instructions below.

      View Image Dimensions on a Mac

      1. Right-click the image and select Get Info.
        Get Image Info
      2. Expand the More Info section.
      3. The Dimensions line gives you the image dimensions (in pixels). Multiply the two dimensions together to get the total number of pixels.
        For example, if the dimensions are 4000x3000, the total number of pixels is 12 million, which is 12MP. That means you can upload the image to any project type.
        View the Image Dimensions

      View Image Dimensions in Windows

      1. Right-click the image and select Properties.
        Properties
      2. Click the Details tab.
      3. The Dimensions line gives you the image dimensions (in pixels). Multiply the two dimensions together to get the total number of pixels.
        For example, if the dimensions are 250x250, the total number of pixels is 625,000, which is 62.5KP. That means you can upload the image to any project type.
        View the Image Dimensions

      What If My Image Has Too Many Pixels?

      If you attempt to upload an image that is over the maximum image size (which is in pixels), you'll get an error message. 

      As a short-term solution, resize your image in an image editor like Photoshop or Illustrator, and then upload the image again.

      As a long-term solution, adjust your camera settings so that the new images are below the maximum number of pixels. This might include lowering the resolution or changing the aspect ratio.

      Number of Labeled Images in a Project

      The maximum number of labeled images a model can use for training depends on the project type.

      Project TypeMaximum Number of Labeled Images
      Object Detection10,000 images
      Segmentation10,000 images
      Classification10,000 images
      Anomaly Detection1,000 images
      Visual Prompting20 images (for more information, go to Visual Prompting)

      Number of Images Required for a Project

      You must upload and label at least 10 images before training a model.

      Since every use case is different, there is no recommended number of images for projects. For detailed best practices, go to Curate High-Quality Datasets.

      Upload Options

      LandingLens offers the following methods for uploading images to your project. Click the hyperlink for each method to learn more.

      Upload MethodDescription
      Drag and dropSelect the files or folders you want to upload, and drag and drop them into an Upload pop-up window or directly into the project.
      Upload images from a directorySome Upload pop-up windows offer the option to select files from a directory. Select the files or folders you want to upload and click Open.
      Upload sample imagesIf you haven't added any images to a project, you have the option to upload a sample dataset. To add the sample images, click Load Sample Data and select a dataset. The available datasets are based on the project type.

      This is not available in LandingLens on Snowflake.
      Take photos with your webcamClick the Webcam option and take photos with your computer webcam.

      This is not available in LandingLens on Snowflake.
      Upload images from your phoneChoose this option to generate a QR code in LandingLens. Scan that code with your smart phone, and then upload images from your phone directly to your project.

      This is not available in LandingLens on Snowflake.
      Upload labeled images to Object Detection projectsUpload images in the Pascal VOC file format.

      If you're using LandingLens on Snowflake, uploading Pascal VOC files is not supported when loading images from Snowflake.
      Upload labeled images to Segmentation projectsUpload images with Segmentation masks.

      If you're using LandingLens on Snowflake, uploading Segmentation masks is not supported when loading images from Snowflake.
      Label images at upload for Classification projectsCreate folders named after the classes you want to use. Put images in their respective folders, and then upload the folders to the project using the Classified Images Upload workflow.
      Label images at upload for Anomaly Detection projectsOpen an Anomaly Detection project and use the on-screen instructions to label images as Normal or Abnormal at upload.
      Upload images via LandingEdgeUpload images with LandingEdge.
      Load images from SnowflakeIf you're using LandingLens on Snowflake, you can load images from a Snowflake stage.
      Load sample datasets from Snowflake MarketplaceIf you're using LandingLens on Snowflake, you can load sample datasets from LandingAI in the Snowflake Marketplace.

      Upload Images to a New Project vs. a Project that Already Has Images

      If you haven't uploaded images to a project yet, all of the upload options appear directly on the project page.

      Upload Options for Projects that Don't Have Images Yet

      After you've uploaded images to a project, click the Upload icon to see the upload options. Or, you can drag and drop images directly into the project page.

      Detect Duplicate Images

      LandingLens automatically prevents duplicate images from being uploaded to a project. When you upload an image to a project, LandingLens checks the MD5 checksum of the image. If another image in the project has the same MD5 checksum, LandingLens doesn't upload the image and displays an error message that explains the image is already in the project.

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