B0270 Arducam High Quality IR-CUT Camera Raspberry Pi 12.3MP 1/2.3" 477P HQ
This Arducam module uses the same 12MP image sensor as the Raspberry Pi High-Quality Camera, but offers a mechanical IR cut-off filter switched automatically based on light conditions. The official RPi HQ camera is not sensitive to infrared, and there won’t be a NoIR version. On the contrary, this Arducam camera module not only offers sensitivity to infrared but also keeps the natural feeling during daylight. It’s fully compatible with all Raspberry Pi models with a camera connector.
Applications
- DSLR Camera Control
- Remote Viewing Camera
- Time-lapse Machine
- Security System
- Smart Video Doorbell
- Face Recognition
- Instant (Polaroid-Style) Camera, etc.
Specifications
Lens
| Focus Type |
Manual Focus |
| Focal Length |
6mm |
| F.NO |
F1.2 |
| Field of View(FOV) |
65°(H) |
| Lens Mount |
CS-Mount |
| MOD |
0.2m |
| Back Focal Length |
7.53mm |
| Lens Dimension |
Φ30×31mm |
Electrical & Mechanical
| Camera Board Size |
38 × 38mm |
| Hole Pitch |
Compatible with 29mm, 30mm, 34mm |
| Peaking Current |
300mA |
Package Including
- 1 x 12.3MP IR-CUT camera module
- 1 x 6mm focal length CS-mount camera lens
- 1 x 300mm/11.8inch 22pin FPC cable for Pi Zero&W
- 1 x 300mm/11.8inch 15pin to 22pin FPC cable for Pi A&B series
Note
- The Raspberry Pi board is not included in the package
- Our camera module support 4-lane in hardware, but the 4-lane camera driver requires extra customization. Here is why:
-
Standard Raspberry Pi and Jetson Nano/Xavier NX can’t physically support a 4-lane connection (both of them only have 2-lane CSI connectors). Only the Raspberry Pi Compute Module and some 3rd party Jetson Carrier Boards come with 4-lane hardware support. Therefore, it’s not a general need.
-
Extra work, specifically camera drivers, are required for a 4-lane connection other than the 4-lane physical connector. And the drivers are limited by the performances of the platform itself. For example, 4-lane can’t unlock 4k video on Raspberry Pi because the VideoCore does not currently support it. Jetson Nano is also to some extent limited because of the encoding capabilities. You need to make sure you really need it.
Documentation
