Practical overview
When it fits
Use it when a development project needs computer vision connected to DJI Tello drone video, especially for object detection, instance segmentation or tracking experiments.
Who it is for
- Python developers working with DJI Tello drones
- Computer-vision practitioners exploring YOLOv8 or Detectron2
- Researchers and hobbyists prototyping aerial-robotics applications
Documented uses
- Detect objects in live DJI Tello drone footage
- Generate instance-segmentation results for aerial video
- Prototype autonomous object tracking
- Compare or combine YOLOv8 and Detectron2 in a drone-vision workflow
Requirements & limits
The repository is public and listed under the Apache-2.0 license. The available project information does not document setup instructions, dependencies or a completed execution workflow.
- It targets DJI Tello rather than a general-purpose video source.
- Its stated model stack includes both YOLOv8 and Detectron2.
- Instance segmentation and autonomous tracking are explicit project goals.
- The repository description identifies a modular design but does not provide detailed implementation guidance.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Install Tello Vision with YOLOv8
Set up the project environment and install its YOLOv8 option.
Before you start
- Python 3.10, as indicated by the project’s environment setup.
- A shell with Git and pip available.
Steps
Clone the repository: the command below.
git clone https://github.com/dronefreak/dji-tello-object-detection-segmentationEnter the project directory:
cd dji-tello-object-detection-segmentation.Create and activate a virtual environment with the command below and
source venv/bin/activate(Windows:venv\Scripts\activate).python3.10 -m venv venvInstall the YOLOv8 option with the command below.
pip install -e ".[yolo]
Expected outcome
The project is installed in the active virtual environment with its YOLOv8 option.
Guide limitations
- This recipe covers installation only; it does not verify that installation succeeded.
- The documentation labels YOLOv8 as recommended for real-time use but supplies no performance guarantees.
Start the Tello Vision application with a DJI Tello
Launch the application after connecting a Tello drone to its Wi-Fi.
Before you start
- A DJI Tello drone.
- The project installed in a Python environment, using the documented setup process.
Steps
Power on the Tello and connect your computer to its Wi-Fi.
From the project environment, launch the application with the command below.
python -m tello_vision.appUse the documented keyboard controls as needed; for example, Tab takes off, Backspace lands, and Esc is the emergency stop.
Expected outcome
The project application is launched for use with the connected Tello; the documentation lists keyboard controls for flight and application actions.
Guide limitations
- The documentation does not specify a tested computer or operating-system configuration for this launch sequence.
- The source provides no safety assessment or guarantee of autonomous tracking behavior.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 4 October 2026
- Original website title
- dronefreak/dji-tello-object-detection-segmentation · Official homepage title · retained in its source language