Upload Images, Videos, and Annotations

The first step to training and deploying a model with Roboflow is to upload data to a Project.

First, you will need to create a Project.

Then, you will be taken to a web page from which you can upload data. You can also access this page from the "Upload Data" button available in your project sidebar.

How to Add Data

You can add data to your Roboflow account by:

• Using the web application: Recommended for datasets with fewer than 1,000 images.

• Using the command line: Recommended for datasets with greater than 1,000 images.

• Using the Dataset Upload Workflow Block: Recommended for collecting data from Workflows with a model already in production.

From the web application and command line, you can upload:

• JPG, PNG, WEBP, and BMP images .

• MOV and .mp4 videos.

• Annotations in any supported format.

You can only upload annotations with images. You cannot upload annotations for images that have already been imported into your dataset.

Upload Data with the Web Application

When you create a project, or on the Upload Data page, you will see a box into which you can drag and drop images, videos, and annotations:

Over 40+ formats are supported. The formats supported vary depending on your project type.

Upload Video

Uploaded videos are broken up into individual frames you can annotate. If you upload a video, a window will open from which you can choose how often frames are sampled for use in your dataset:

Once you click "Choose Frame Rate", your video will be split up into frames. These frames will then be uploaded to your dataset.

Once you have uploaded your dataset, you will be able to assign the data for labeling.

Once you drop them into the Web UI, a dialog box will ask you to choose the frame rate. This will tell us how many images we should sample from your video per second.

• The highest frame rate you can select is 60 frames per second, which will generate 60 images for each second of video you upload.

• The lowest frame rate you can select is 1 frame per 60 seconds.

After sampling from your video, the images will appear as if you had originally uploaded images to Roboflow.

Upload a YouTube Video

You can also import a YouTube video directly using a similar process as shown above by pasting a YouTube link on the Upload page.

Upload Datasets with the Command Line

You can upload larger datasets using the Roboflow Python command line interface.

You can only upload images with the command line interface. If you have videos, you will need to split them into frames saved as files. These files can then be uploaded to Roboflow.

To get started, first install roboflow-python:

pip install roboflow-python

Next, retrieve your Workspace ID.

Finally, prepare a command in the following format:

roboflow import -w testupload -p project-1-8zgld /path/to/dataset/folder

Here are the arguments you need to specify:

• -w testupload: This is the name of the batch that will be created.

• -p <project-id>: This is your project ID.

When you run the command, you will see a message that indicates the upload process has started. You will then see logs as images upload:

We have a video walkthrough that shows how to upload data from the command line:

View Your Uploaded Data

All data uploaded to Roboflow is uploaded in a "batch". These batches can be viewed on your Project Annotate page:

Image Size limits

The maximum size for an image is 20 MB

The maximum pixel dimensions are 16,400 × 10,900 pixels.

Duplicate Images

If you try to upload an image that is already in a Project, upload for that image will be skipped.

Data Ownership

You retain ownership over all images and videos you upload to Roboflow. This is defined in our Section 23B of our Terms of Service:

You retain all ownership rights in any content, information, or materials You post, submit, publish, display, or transmit

Data Privacy

Public Plan: If you are on the Public plan unless explicitly specified and arranged by Roboflow, your datasets will be public on Roboflow Universe.

Paid Plans (including Enterprise): Unless otherwise specified, your data is private to your account.