Shenzhen Jupin Technology Co., Ltd.
| Supply Ability | 100+pcs+day |
| Delivery Time | 10 working days |
| Packaging Details | 84.0mm × 22.45mm × 19.35mm |
| Payment Terms | T/T |
| 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 3840 x 2160@30fps + 720p@30fps encoding |
| Video Decoding | 4KH.264/H.26530fps 3840 x 2160@30encoding + 3840 x 2160@30fps decoding |
| System Support | Linux |
| Power | 5V/1A |
| Operating Temperature | -10℃～60℃ |
| Operating Humidity | 10%～90% |
| Binocular Camera | Camera（IR）/ Camera（RGB） |
| Image Sensors | GC2053 / GC2093 |
| Sensor Size | 1 / 2.9 |
| Resolution | Center 800 Edge 600 |
| Pixel Size | 2.8 μm |
| Output Format | RAW |
| Interface | MIPI |
| Focusing Distance | 80 cm |
| Lens | 4P |
| Optical Filter | 850 nm |
| Field of View | D70°H62°V38° |
| Optical Distortion | ≤0.5% |
| Focal Length | F2.0/4.3mm |
| Maximum Database | 100,000 |
| Recommended Database | 10,000 |
| 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% |
| Face Detection | Face Detection Time: ~23 ms / Face Tracking Time: ~7 ms |
| Liveness Detection | Monocular Liveness Detection Time: ~45 ms / Binocular Liveness Detection Time: ~15 ms |
| Face Comparison | Feature Extraction Time: ~25 ms / Single Comparison Time: ~0.0115 ms |
| Recommended Image | 720P |
| Minimum Face Size for Recognition | Without Liveness Detection: 50 x 50 pixels / With Liveness Detection: 90 x 90 pixels） |
| Recommended Face Recognition Angles | Yaw: ≤ ±30° Pitch: ≤ ±30° Roll: ≤ ±30° |
| Module Size | 84.0mm × 22.45mm × 19.35mm |
| Enclosure Design | Aluminum alloy material with serrated heat sink back cover for efficient cooling |
| 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 |
| Brand Name | Shi Zun |
| Model Number | JP-1126 |
| Place of Origin | China |
View Detail Information
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Product Specification
| Supply Ability | 100+pcs+day | Delivery Time | 10 working days |
| Packaging Details | 84.0mm × 22.45mm × 19.35mm | Payment Terms | T/T |
| 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 3840 x 2160@30fps + 720p@30fps encoding | Video Decoding | 4KH.264/H.26530fps 3840 x 2160@30encoding + 3840 x 2160@30fps decoding |
| System Support | Linux | Power | 5V/1A |
| Operating Temperature | -10℃～60℃ | Operating Humidity | 10%～90% |
| Binocular Camera | Camera（IR）/ Camera（RGB） | Image Sensors | GC2053 / GC2093 |
| Sensor Size | 1 / 2.9 | Resolution | Center 800 Edge 600 |
| Pixel Size | 2.8 μm | Output Format | RAW |
| Interface | MIPI | Focusing Distance | 80 cm |
| Lens | 4P | Optical Filter | 850 nm |
| Field of View | D70°H62°V38° | Optical Distortion | ≤0.5% |
| Focal Length | F2.0/4.3mm | Maximum Database | 100,000 |
| Recommended Database | 10,000 | 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% |
| Face Detection | Face Detection Time: ~23 ms / Face Tracking Time: ~7 ms | Liveness Detection | Monocular Liveness Detection Time: ~45 ms / Binocular Liveness Detection Time: ~15 ms |
| Face Comparison | Feature Extraction Time: ~25 ms / Single Comparison Time: ~0.0115 ms | Recommended Image | 720P |
| Minimum Face Size for Recognition | Without Liveness Detection: 50 x 50 pixels / With Liveness Detection: 90 x 90 pixels） | Recommended Face Recognition Angles | Yaw: ≤ ±30° Pitch: ≤ ±30° Roll: ≤ ±30° |
| Module Size | 84.0mm × 22.45mm × 19.35mm | Enclosure Design | Aluminum alloy material with serrated heat sink back cover for efficient cooling |
| 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 | Brand Name | Shi Zun |
| Model Number | JP-1126 | 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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