Wildlife photography can be incredibly rewarding. Especially if we use it as an excuse to dabble into Machine Learning using a Raspberry Pi. For this video, I set up an Intel D435 RealSense camera to capture video near a bird feeder. Then, I connected it to a Raspberry Pi, and used Python, OpenCV, and Tensorflow to process the video data and detect when a bird was in the field of view. I also connected a DSLR over USB to the Pi, which I triggered using Python and gPhoto2, whenever a bird was detected. I took some great photos, so here's an overview of the build.
Supplemental Content:
- Episode 448: DIY Raspberry Pi 4 Boxing Game
- Getting Started | Raspberry Pi 4 + Intel's RealSense D435 Depth Camera Step-By-Step Installation
- Tensor Flow Guide
- Project Code
Bill of Material:
| Product Name | Manufacturer | Quantity | Buy Kit |
|---|---|---|---|
| Raspberry Pi 4 Model B | RASPBERRY-PI | 1 | Buy Now |
| Dev Board, RealSense Robotic Camera | INTEL | 1 | Buy Now |
Additional Parts:
| Product Name |
|---|
| Coral USB Accelerator |
| Nikon D7000 DSLR |
Raspberry Pi Bird Watching Camera
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