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| Categories | Face Recognition Camera Module | 
|---|---|
| Brand Name: | Shi Zun | 
| Model Number: | JP-1126 | 
| Place of Origin: | China | 
| MOQ: | Negotiable | 
| Price: | Negotiable | 
| 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 | 
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% | 












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