Equipped with high-performance quad-core AI intelligent vision processor with computing power up to 2.0Tops, the module supports 4K video coding and decoding, various AI frameworks and human detection with high recognition accuracy — it is suitable for face recognition, gate access control, gesture recognition, expression recognition, face attribute analysis, etc. Abundant resources facilitate secondary development and help the project to be implemented quickly.
AI vision processor RV1126, with quad-core 32-bit ARM Cortex-A7 architecture and frequency up to 1.5GHz, integrates NEON and FPU to accelerate — has extraordinary processing performance.
NPU neural network processor are integrated, with computing power up to 2.0 Tops. RKNN toolkit is provided for model conversion, which can realize the model conversion and algorithm support of commonly used AI frameworks like caffe/darknet/mxnet/onnx/pytorch/tensorflow/tflite.
2MP RGB+IR dual-lens camera supports human detection, which can effectively prevent the deception of photos, videos, and wax figures, and ensure the face recognition effect in various complex and extreme light environments.
It supports face database up to 100,000 capacity; it has efficient recognition speed, and identifies the target quickly — the recognition accuracy rate is 99.7%.
Integrated video coding & decoding processor, supports ffmpeg, Gstreamer framework, and supports multi-channel H.264/H.265 4K@30FPS video coding and decoding.
It can be used as a USB device to output visual processing data and images to the computer or can be connected to a MIPI 1080P display to form a face recognition/AI vision terminal.
Equipped with all-aluminum alloy shell, the space-saving module has efficient heat dissipation and can be flexibly embedded in various AI products.
Complete SDK, including cross compiler toolchain, BSP source code, application development environment, development documents and examples are provided to be used for system peripheral expansion, application development and algorithm porting, etc.
t is widely used in face recognition, gesture recognition, gate access control, self-service terminals, smart finance, smart construction, smart travel and other industries.
CAM-C1109S2U | CAM-C1126S2U | |
SoC |
RV1109 |
RV1126 |
CPU |
Dual-core ARM Cortex-A7 32-bit , frequency 1.5GHz, integrate NEON and FPU Each core has a 32KB I-cache, 32KB D-cache and 512KB shared second-level cache Based on RISC-V MCU |
Quad-core ARM Cortex-A7 32-bit, frequency 1.5GHz, integrate NEON and FPU Each core has a 32KB I-cache, 32KB D-cache and 512KB shared second-level cache Based on RISC-V MCU |
NPU |
1.2Tops, support INT8/ INT16, It has strong network model compatibility and provides RKNN tool, which can realize the conversion of commonly used AI framework models Eg: (caffe, darknet, mxnet, onnx, pytorch, tensorflow, tflite) and algorithm support |
Computing power up to 2.0Tops, supports INT8/ INT16, It has strong network model compatibility and provides RKNN tool, which can realize the conversion of commonly used AI framework models Eg: (caffe, darknet, mxnet, onnx, pytorch, tensorflow, tflite) and algorithm support |
RAM |
1GB / 2GB DDR3 |
1GB / 2GB DDR4 |
存储 |
8GB / 16GB eMMC |
8GB / 16GB eMMC |
Video Encoding |
H.264/H.265 encoding capability: 2688 x 1520@30 fps+1280 x 720@30 fps 3072 x 1728@30 fps+1280 x 720@30 fps 2688 x 1944@30 fps+1280 x 720@30fps |
4K H.264/H.265 30fps video encoding: 3840 x 2160@30 fps+720p@30 fps encoding |
Video Decoding |
5M H.264/H.265 decoding |
4K H.264/H.265 30fps video decoding 3840 x 2160@30 + 3840 x 2160@30 fps decoding |
OS |
Linux |
Linux |
Power |
5V |
5V |
Operating Temperature |
-10℃~60℃ |
-10℃~60℃ |
Operating Humidity |
10%~90 % |
10%~90 % |
Dual-Lens Camera | ||
Camera (IR) | Camera (RGB) | |
Dual-Lens Camera |
GC2053 |
GC2093 |
Sensor Size |
1 / 2.9 |
1 / 2.9 |
Resolution |
1920*1080 |
1920*1080 |
Pixel Size |
2.8 μm |
2.8 μm |
Output Format |
RAW |
RAW |
Interface |
MIPI |
MIPI |
Focus Distance |
80 cm |
80 cm |
Lens |
4P |
4P |
Filter |
850 nm |
650 nm |
Field Angle |
D70°H62°V38° |
D70°H62°V38° |
Distortion |
≤0.5% |
≤0.5% |
Aperture/ Focal Length |
F2.0/4.3mm |
F2.0/4.3mm |
Resolving Power |
Center: 800 Around: 600 |
Center: 800 Around: 600 |
Face Recognition & Detection | ||
Max Database |
100,000 |
|
Recommended Database |
10,000 |
|
Accuracy |
Under standard test environment, 10,000 database No Mask: Accuracy 99% With mask: Accuracy 95% |
|
Face Detection |
Face detection time: ~23ms Face tracking time: ~7ms |
|
Human Detection |
Single-lens detection time: ~45ms Dual-lens detection time: ~15ms |
|
Face Recognition |
Feature extraction time: ~25ms Single recognition time: ~0.0115ms |
|
Recommended Image Input Size |
720P |
|
Min Face Recognition Size |
50*50 pixel (Non-human) 90*90 pixel (Human) |
|
Recommended Face Recognition Angle |
Yaw ≤ ±30° Pitch ≤ ±30° Roll≤ ±30° |
|
Appearance | ||
Dimension |
84.0mm × 22.45mm × 19.35mm |
|
Shell |
All aluminum alloy design, efficient heat dissipation |