Coding4Fun Drone 🚁 posts
- Introduction to DJI Tello
- Analyzing Python samples code from the official SDK
- Drone Hello World ! Takeoff and land
- Tips to connect to Drone WiFi in Windows 10
- Reading data from the Drone, Get battery level
- Sample for real time data read, Get Accelerometer data
- How the drone camera video feed works, using FFMPEG to display the feed
- Open the drone camera video feed using OpenCV
- Performance and OpenCV, measuring FPS
- Detect faces using the drone camera
- Detect a banana and land!
- Flip when a face is detected!
- How to connect to Internet and to the drone at the same time
- Video with real time demo using the drone, Python and Visual Studio Code
- Using custom vision to analyze drone camera images
- Drawing frames for detected objects in real-time in the drone camera feed
- Save detected objects to local files, images and JSON results
- Save the Drone camera feed into a local video file
- Overlay images into the Drone camera feed using OpenCV
- Instance Segmentation from the Drone Camera using OpenCV, TensorFlow and PixelLib
- Create a 3×3 grid on the camera frame to detect objects and calculate positions in the grid
- Create an Azure IoT Central Device Template to work with drone information
- Create a Drone Device for Azure IoT Central
- Send drone information to Azure IoT Central
Back to some drone posts! I was kind of busy during the last weeks and now I can get back to write about the drone.
OK, in the last posts I described how to connect and work with the drone camera feed using OpenCV. Now with 2 extra lines of code we can also detect faces. Let’s take a look at the final sample.
In the previous image we can see 2 camera feeds. My computer webcam, where you can see how I hold the drone with the drone camera pointing to my face. And the drone camera feed, presented using OpenCV and drawing a frame over each detected face.
Let’s share some code insights:
- As usual, I resize the camera feed to 320 x 240
- The average processing time is between 40 and 70 FPS
- I use a haar cascade classifier to detect the faces in each frame
Note: I need to write about Haar Cascades as part of my face detection post series.
In my next posts, I’ll add some drone specific behaviors for each face detected.
More posts in my blog ElBruno.com.
- Anaconda, My steps to install a virtual environment with TensorFlow, Keras, OpenCV and more
- Let’s do some Face Recognition with 20 lines in Python
- OpenCV – Show Image – imshow()
Face Recognition and Face Detection series in Python
- Detecting Faces with 20 lines in Python
- Face Recognition with 20 lines in Python
- Detecting Facial Features with 20 lines in Python
- Facial Features and Face Recognition with 20 lines in Python
- Performance improvements with code
- Resize the camera input with OpenCV
- Working with Haar Cascades and OpenCV
- Detect and blur faces 😁 using haar cascades
- Detect and blur faces 😁 using DNN