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🚨🚨🚨 REPO DEPRECATED 🚨🚨🚨

Roboflow Video Inference

Example script to do inference on a video file with Roboflow Infer

Example Output

An example video (gif) generated with this utility script from a Roboflow model with the following command:

ROBOFLOW_KEY=xxxxxxxx ./infer.sh rf-aquarium-merged/3 IMG_3203.mov fish.gif --fps_in 3 --fps_out 12 --scale 4

Getting Started

Colab Tutorial Here:

Open In Colab

Installation

The shell script you need is infer.sh in this repo.

To use it

  • copy that file to your local machine,
  • add execute permissions chmod +x infer.sh,
  • install the requirements (see below)
  • and then use it:
# Simple usage with ROBOFLOW_KEY env var set inline
ROBOFLOW_KEY=xxxxx ./infer.sh [YOUR_DATASET]/[YOUR_VERSION] video_in.mp4 video_out.mov

To obtain your ROBOFLOW_KEY, go to your account settings page and copy your API Key (not your Publishable Key). Treat this API Key like a password; it gives access to your Roboflow account and is meant to remain a secret.

The model ID ([YOUR_DATASET]/[YOUR_VERSION] in the command above) is obtained from the Roboflow UI after training. Click "Example Web App" in the "Use Your Trained Model" section and copy it from the pre-filled text field at the top of the page.

Requirements

The script's main requirements are ffmpeg, base64, and curl. On most modern Unix-like operating systems, you will only need to install ffmpeg because the other requirements are preinstalled.

macOS

Already includes base64 and curl.

Use homebrew to install ffmpeg: brew install ffmpeg

Ubuntu

Already includes base64 and curl.

Use apt to install ffmpeg: sudo apt install ffmpeg

Windows

Download ffmpeg from their website and install git for Windows which conveniently includes base64 and curl.

Options

A ROBOFLOW_KEY environment variable with your Roboflow API Key is required.

The infer.sh script accepts the following parameters:

Parameter Example Description
--host --host "http://localhost:9001" The Roboflow Infer host; set for On-Device Inference (default: https://infer.roboflow.com).
--confidence --confidence 50 The minimum threshold for the model to output box predictions (default: 50).
--overlap --overlap 50 The maximum amount two predicted boxes of the same class can intersect before being combined (default: 50).
--stroke --stroke 5 The thickness of the predicted bounding boxes (default: 5).
--labels --labels Enable printing the class names (implicit default: off)
--classes --classes car A comma separated (no whitespace) list of classes to predict (default: show all).
--fps_in --fps_in 6 The sample rate from the input video in frames per second (default: 6).
--fps_out --fps_out 24 The render speed; setting higher than fps_in gives a timelapse effect (default: 24).
--scale --scale 2 The amount to shrink the video; eg 2 to make video_out width and height 2x smaller than video_in (default: 1).
--tmp --tmp . The tmp directory; must be writable (default: /tmp).
--retries --retries 3 The number of times to retry a failed inference (default: 3).
--parallel --parallel 8 The number of concurrent frames to send to the model (default: 8).
model xx-mymodel--1 The Roboflow model to use for inference (required).
video_in video_in.mp4 The input video file (required).
video_out video_out.mp4 The output video file (required). Can be of any format supported by ffmpeg's encoder (eg .mov, .mp4, .gif).

Building

The infer script is built with argbash (a code generator that adds smart parameter parsing for bash scripts) from source.m4.

To build, clone this repo, install argbash, then run the following in the repo's top-level directory:

argbash source.m4 -o infer.sh

You can then use your newly generated infer.sh as described above.

License

This example repo is released under an MIT License. You will need to train a model with Roboflow Train which is goverened by the Roboflow Terms of Service.

**Note: Update from November 2023 - Roboflow now provides a new video inference API, please visit this link to learn more. This repository is archived. **