Shenzhen Jupin Technology Co., Ltd.
| Storage | 8GB/16GB eMMC |
| Power | 5V/1A |
| Output Format | Camera（IR）: RAW Camera（RGB）: RAW |
| Recommended Database | 10,000 |
| Module Size | 84.0mm × 22.45mm × 19.35mm |
| Processor | Quad-core ARM Cortex-A7 32-bit, 1.5GHz, with integrated NEON and FPU Each core has a 32KB I-cache and 32KB D-cache, plus 512KB shared L2 cache Based on RISC-V MCU |
| Interface | Camera（IR）: MIPI Camera（RGB）: MIPI |
| Maximum Database | 100,000 |
| Recommended Face Recognition Angles | Yaw: ≤ ±30° Pitch: ≤ ±30° Roll: ≤ ±30° |
| Face Comparison | Feature Extraction Time: ~25 ms Single Comparison Time: ~0.0115 ms |
| Video decoding | 4KH.264/H.26530fps 3840x2160@30encoding+3840x2160@30fpsdecoding |
| Image Sensors | Camera（IR）: GC2053 Camera（RGB）: GC2093 |
| Pixel Size | Camera（IR）: 2.8 μm Camera（RGB）: 2.8 μm |
| Recommended Image | 720P |
| Video encoding | 4KH.264/H.26530fps 3840x2160@30fps+720p@30fpsencoding |
| Sensor Size | Camera（IR）: 1 / 2.9 Camera（RGB）: 1 / 2.9 |
| System support | Linux |
| Operating humidity | 10%～90% |
| Resolution | Camera（IR）: Center 800 Edge 600 Camera（RGB）: Center 800 Edge 600 |
| Face Recognition Accuracy | Standard Testing Environment, 10,000-person Database: Without Mask: False Acceptance Rate: 0.01%; Recognition Accuracy: 99% With Mask: False Acceptance Rate: 0.01%; Recognition Accuracy: 95% |
| Enclosure Design | Aluminum alloy material with serrated heat sink back cover for efficient cooling |
| Lens | Camera（IR）: 4P Camera（RGB）: 4P |
| Liveness Detection | Monocular Liveness Detection Time: ~45 ms Binocular Liveness Detection Time: ~15 ms |
| NPU | Up to 2.0 Tops performance, supports INT8/INT16, strong network model compatibility, RKNN model conversion tool available for converting common AI framework models (e.g., Caffe, Darknet, MXNet, ONNX, PyTorch, TensorFlow, TFLite) and algorithm support |
| Face Detection | Face Detection Time: ~23 ms Face Tracking Time: ~7 ms |
| Memory | 1GB/2GBDDR4 |
| Filter Wavelength | Camera（IR）: 850 nm Camera（RGB）: 650 nm |
| Payment Terms | T/T |
| Optical Distortion | Camera（IR）: ≤0.5% Camera（RGB）: ≤0.5% |
| Focal Length | Camera（IR）: F2.0/4.3mm Camera（RGB）: F2.0/4.3mm |
| Host computer chip | RV1126 |
| Focusing Distance | Camera（IR）: 80 cm Camera（RGB）: 80 cm |
| Supply Ability | 200+/day |
| Delivery Time | 5-8 work days |
| Packaging Details | |
| Operating temperature | -10℃～60℃ |
| Power Consumption | Typical Power Consumption: 2.8W (5V, 560mA) Maximum Power Consumption: 4.3W (5V, 860mA) Minimum Power Consumption: 0.71W (5V, 142mA) Power Supply Recommendation: 5V/1.2A or higher |
| Field of View | Camera（IR）: D70°H62°V38° Camera（RGB）: D70°H62°V38° |
| Minimum Face Size for Recognition | Without Liveness Detection: 50 x 50 pixels With Liveness Detection: 90 x 90 pixels） |
| Brand Name | |
| Model Number | JP1126 |
| Place of Origin | China |
View Detail Information
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Product Specification
| Storage | 8GB/16GB eMMC | Power | 5V/1A |
| Output Format | Camera（IR）: RAW Camera（RGB）: RAW | Recommended Database | 10,000 |
| Module Size | 84.0mm × 22.45mm × 19.35mm | Processor | Quad-core ARM Cortex-A7 32-bit, 1.5GHz, with integrated NEON and FPU Each core has a 32KB I-cache and 32KB D-cache, plus 512KB shared L2 cache Based on RISC-V MCU |
| Interface | Camera（IR）: MIPI Camera（RGB）: MIPI | Maximum Database | 100,000 |
| Recommended Face Recognition Angles | Yaw: ≤ ±30° Pitch: ≤ ±30° Roll: ≤ ±30° | Face Comparison | Feature Extraction Time: ~25 ms Single Comparison Time: ~0.0115 ms |
| Video decoding | 4KH.264/H.26530fps 3840x2160@30encoding+3840x2160@30fpsdecoding | Image Sensors | Camera（IR）: GC2053 Camera（RGB）: GC2093 |
| Pixel Size | Camera（IR）: 2.8 μm Camera（RGB）: 2.8 μm | Recommended Image | 720P |
| Video encoding | 4KH.264/H.26530fps 3840x2160@30fps+720p@30fpsencoding | Sensor Size | Camera（IR）: 1 / 2.9 Camera（RGB）: 1 / 2.9 |
| System support | Linux | Operating humidity | 10%～90% |
| Resolution | Camera（IR）: Center 800 Edge 600 Camera（RGB）: Center 800 Edge 600 | Face Recognition Accuracy | Standard Testing Environment, 10,000-person Database: Without Mask: False Acceptance Rate: 0.01%; Recognition Accuracy: 99% With Mask: False Acceptance Rate: 0.01%; Recognition Accuracy: 95% |
| Enclosure Design | Aluminum alloy material with serrated heat sink back cover for efficient cooling | Lens | Camera（IR）: 4P Camera（RGB）: 4P |
| Liveness Detection | Monocular Liveness Detection Time: ~45 ms Binocular Liveness Detection Time: ~15 ms | NPU | Up to 2.0 Tops performance, supports INT8/INT16, strong network model compatibility, RKNN model conversion tool available for converting common AI framework models (e.g., Caffe, Darknet, MXNet, ONNX, PyTorch, TensorFlow, TFLite) and algorithm support |
| Face Detection | Face Detection Time: ~23 ms Face Tracking Time: ~7 ms | Memory | 1GB/2GBDDR4 |
| Filter Wavelength | Camera（IR）: 850 nm Camera（RGB）: 650 nm | Payment Terms | T/T |
| Optical Distortion | Camera（IR）: ≤0.5% Camera（RGB）: ≤0.5% | Focal Length | Camera（IR）: F2.0/4.3mm Camera（RGB）: F2.0/4.3mm |
| Host computer chip | RV1126 | Focusing Distance | Camera（IR）: 80 cm Camera（RGB）: 80 cm |
| Supply Ability | 200+/day | Delivery Time | 5-8 work days |
| Packaging Details | Operating temperature | -10℃～60℃ | |
| Power Consumption | Typical Power Consumption: 2.8W (5V, 560mA) Maximum Power Consumption: 4.3W (5V, 860mA) Minimum Power Consumption: 0.71W (5V, 142mA) Power Supply Recommendation: 5V/1.2A or higher | Field of View | Camera（IR）: D70°H62°V38° Camera（RGB）: D70°H62°V38° |
| Minimum Face Size for Recognition | Without Liveness Detection: 50 x 50 pixels With Liveness Detection: 90 x 90 pixels） | Brand Name | |
| Model Number | JP1126 | Place of Origin | China |
| High Light | HD Face Recognition Module ，Face Recognition Module DC5V ，1920x1080 face detection module | ||
JP1126 Intelligent Dual-Lens Camera Module Up to 2.0 Tops performance, supports INT8/INT16 5V/1A
JP1126 Intelligent Dual-Lens Camera Module Features:
JP1126 Intelligent Dual-Lens Camera Module Parameter:
|
Processor:
|
Quad-core ARM Cortex-A7 32-bit, 1.5GHz, with integrated NEON and FPU
Each core has a 32KB I-cache and 32KB D-cache, plus 512KB shared L2 cache
Based on RISC-V MCU
|
|
NPU:
|
Up to 2.0 Tops performance, supports INT8/INT16, strong network model compatibility,
RKNN model conversion tool available for converting common AI framework models (e.g.,
Caffe, Darknet, MXNet, ONNX, PyTorch, TensorFlow, TFLite) and algorithm support
|
|
Memory:
|
1GB/2GBDDR4
|
|
Storage:
|
8GB/16GB eMMC
|
|
Video encoding:
|
4KH.264/H.26530fps
3840x2160@30fps+720p@30fpsencoding
|
|
Video Decoding:
|
4KH.264/H.26530fps
3840x2160@30encoding+3840x2160@30fpsdecoding
|
|
System support:
|
Linux
|
|
Power:
|
5V/1A
|
|
Image Sensors:
|
GC2053
GC2093
|
| Module Board Dimensions: | 80* 16* 17.6mm (L* W* H) |
|
Resolution:
|
1920*1080
|
|
Pixel Size:
|
2.8 μm
|
|
Interface:
|
MIPI
|
|
Focal Length:
|
F2.0/4.3mm
|
| Maximum Database: |
100,000
|
|
Face Recognition
Accuracy:
|
Standard Testing Environment, 10,000-person Database:
Without Mask:
False Acceptance Rate: 0.01%; Recognition Accuracy: 99%
With Mask:
False Acceptance Rate: 0.01%; Recognition Accuracy: 95%
|
Company Details
Business Type:
Manufacturer
Year Established:
2016
Total Annual:
1000000-1500000
Employee Number:
>100
Ecer Certification：
Site Member
Shenzhen Jupin Technology Co., Ltd. ("Jupin" for short) is a domestic high-tech enterprise focusing on the development, production and sales of iris recognition and face recognition technology products. Main products: iris recognition access control, iris recognition attendance machine, fa... Shenzhen Jupin Technology Co., Ltd. ("Jupin" for short) is a domestic high-tech enterprise focusing on the development, production and sales of iris recognition and face recognition technology products. Main products: iris recognition access control, iris recognition attendance machine, fa...
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