Sieve Video Data Collection Example

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Find samples that are interesting within hours of raw video, for free and completely automatically using Sieve API.


Collecting visual data from a camera typically involves setting it up somewhere and writing a script that saves that footage on-device or in the cloud. Later accessing that data and finding what you want within it however becomes pretty difficult. Sieve makes this simple.

  1. Write script that sends data to Sieve
  2. Sieve processes video data efficiently and automatically
  3. Query and download the exact images and metadata you want using Sieve Dashboard

Getting Started

Get a Sieve API Key

Fill out this form to receive an API key within 10 minutes. It’s completely free if it’s for personal use or if you’re a student. Otherwise, we’ll contact you so you can learn more about pricing.

Clone Repo and Install Dependencies

This repo has been tested with Python 3.7 in an isolated conda environment so to get started, we suggest using conda.

git clone
cd automatic-video-processing
conda create --name myenv python=3.7
conda activate myenv
pip install -r requirements.txt

Run Script

Running this script will start securely pushing your data to Sieve.
python --sieve_api_key YOUR_API_KEY

Custom Modifications

Argument Name Description Default Value
video_push_interval How often video is pushed to Sieve (in seconds) 10
video_feed_path The location of your video stream as taken in by OpenCV. If you have a webcam plugged in, this is some number depending on how many cameras you have plugged in. You can also specify a filepath to the location of a local video file (e.g. /home/my/path/my_video.mp4) 0

Sieve Dashboard

Sieve Dashboard

Watch the video above to learn more about how to use our dashboard. This repo has already taken care of the uploading videos section of it. To access your Sieve dashboard, all you need to do is visit the following link:

Export Dataset

  1. Type your query into the dashboard
    Sieve Sample Query
  2. Click export and choose a name for your export
    Sieve Sample Export
  3. Go over to the “Project Info and Exports” tab to view progress of export. If your query is less than 100k samples, it should be done within a few minutes.
    Sieve Export Progress
  4. Click download and get the exact curl command for you to download the set of data anywhere.


View Github