DAHUA IVS-GS8000-GU2-HW Dahua Comprehensive Analysis Intelligent Server
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IVS-GS8000-GU2-HW
Dahua Comprehensive Analysis Intelligent Server
> Adopts advanced face deep learning algorithms and gives full play to GPU parallel computing. With its algorithms, the device has enhanced recognition capabilities and performs exceptionally well, raising the bar in the industry.
> Tesla T4 intelligence analysis card with strong computing power.
> Performs intelligent analysis and compares tens of millions of pieces of massive data from faces, vehicles and structured services.
> Arms the blocklist database which has millions of pieces of face data.
> A type of rack mount server with multiple built-in slots and modular replacement that assist with changing the hardware.
> The system has cluster deployment and supports enhancing the performance of clusters when servers are added based on the video cloud distributed architecture.
> Supports algorithm storehouse.
Product Data
System |
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Main Processor |
Two 16 C/32 T X86 processors, 2.1 GHz |
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GPU |
Supports Four NVIDIA TESLA T4 GPUs (the GPU card is optional, and the following functions are available with the GPU card and relevant software permission). |
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Operating System |
CentOS Linux release 7.4.1708 (Core) |
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Memory |
Eight 16 GB DDR4 memory modules with up to 24 slots |
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Disk |
Five 3.5"4 TB HDD which can be expanded to maximum 32 TB (each HDD is 4T) with up to 8 slots. |
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Face Analytics |
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Face Detection |
Detects and analyzes face image streams by gender, age, expression, glasses, mustache, face mask, opened and closed eyes, and opened and closed mouths. |
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Face Modeling |
Supports extracting attributes from face images. |
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Face Arm |
Compares the face snapshot against a designated face database to get information on the first person that exceeds the arming threshold. |
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History Alarm Records Query |
Quickly search for history records on arming alarms to review information on alarms that were previously triggered. |
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Management of Registered Database |
Manage and use multiple types of databases such as the blocklist database, allowlist database, and static database. You can add, delete and modify these databases and their members. |
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Search in Registered Database |
Quickly search for registered database members by name, gender, date of birth and ID card number. |
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Search by Image in Registered Database |
Images can be used to search for information. The results are compared with data on humans in the registered database, and the matches are displayed based on their similarity level. |
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Search in Snapshot Database |
Conveniently search for history records of passing persons in the snapshot database. |
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Search by Image in Snapshot Database |
Images can be used to search for information, and the search results can be filtered by time and channel. The results are compared with data on humans in the snapshot database, and the matches are displayed based on their similarity level. |
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1V1 |
Supports 1V1 face comparison, and returns similarity result.;One T4 card supports up to 75 times/s (only in the case of working with video cloud platform, and exclusive use of hardware resources of single server) |
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Cluster |
Supports clusters (when it is set to work with the video cloud platform) |
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Image Stream Analysis Capability |
One T4 card supports up to 200 face images/s. |
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Blocklist/Allowlist Database Arm |
When a single server perform arming with CPU hardware, it supports blocklist/allowlist database with 2 million data and can real-time alarm of 100 face features/s |
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Search by Image |
Up to 100 million face data (30 million in registered database and 70 million in snapshot database by default) |
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Vehicle Analytics |
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Vehicle Recognition Mode |
Recognizes the front and back of vehicles (supports recognition of license plates from Brazil, and configuring license plate recognition for other countries). |
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License Plate Color Recognition |
White, black, yellow, blue, and green |
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Vehicle Color Recognition |
Recognizes a variety of colors such as white, orange, pink, black, red, yellow, gray, blue, green, silver, brown and purple |
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Vehicle Type Recognition |
Supports large bus, heavy truck, medium truck, sedan, van, truck, medium bus, SUV, MPV and pickup |
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Vehicle Attributes Recognition |
Recognizes vehicle attributes such as tissue boxes, sunshields, pendants, perfume, cards and permits. |
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Safe Driving Behavior Detection |
For drivers, it detects when they are not wearing their seatbelt, calling while driving and smoking. |
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Target Detection |
Supports vehicle recognition of incomplete snapshot |
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Image Stream Analysis Capability |
One T4 card supports up to 3 million image/day (pixel from 2 MP to 9 MP) |
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Vehicle Brand/Logo Recognition |
147 kinds |
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License Plate Recognition |
License plate recognition with a minimum of 50 x 13 pixels is supported. |
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License Plate Recognition Rate |
With normal light in the day and normal fill light at night, resolution ≥120 × 120, clear, distinguishable license plate. |
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Vehicle Type Recognition Rate |
With normal light in the day and normal fill light at night, resolution ≥240 × 240, clear, distinguishable vehicles. |
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Vehicle Color Recognition Rate |
With normal light in the day and normal fill light at night, resolution ≥240 × 240, clear, distinguishable vehicles. |
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Safety Belts Recognition Rate |
≥85% (vehicle glass is clear) |
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Recognition Rate of Driver and Passenger Phone Calling |
≥80% (vehicle glass is clear) |
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Search by Vehicle Picture |
Images can be used to search for information, and the search results can be filtered by time and channel. The results are compared with data on motor vehicles in the database, and the matches are displayed based on their similarity level. |
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Search by Vehicle Picture Performance |
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Vehicle Search |
One server supports up to 40 million data in snapshot database, searching by image and responding in seconds(only in the case of working with video cloud platform, and exclusive use of hardware resources of single server) |
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Metadata Analytics |
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Target Classification |
Classify targets including face, body, motor vehicles and non-motor vehicles. Generate intelligent structured analysis on the live video, history video (when using with the platform), and the video files that were uploaded offline, and then extract structured information on the moving targets. (for face, only image can be viewed without structured analysis). |
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Motor Vehicle Detection |
Detects motor vehicles by a wide range of attributes such as type, color, brand and plate number(supports recognition of license plates from Brazil, and configuring license plate recognition for other countries). |
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Non-motor Vehicle Detection |
Detects pedestrians by a wide range of attributes such as gender, age, hair style, their top and bottom clothes and color, non-motor vehicle type and color wearing a hat, hat color, umbrella (canopy), umbrella (canopy) color, bag, bag color, shoe type and color, vest, mask color, raincoat, rearview mirror, truck, basket and direction. |
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Pedestrian Detection |
Detects pedestrians by a wide range of attributes such as gender, age, hair style, their top and bottom clothes and color, wearing a hat, hat color, umbrella, umbrella color, bag, bag color, shoe type and color, vest, mask color, raincoat, cart, whether they are riding, and direction. |
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Real-time Display |
Displays the analysis results in real time, and display humans, motor vehicles and non-motor vehicles in real time with tracking boxes. |
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Search by Attribute |
Intelligent search of human, motor vehicles and non-motor vehicles by their attributes. |
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Search by Image |
Images can be used to search for information, and the search results can be filtered by time and channel. The results are compared with data on humans, motor vehicles and non-motor vehicles in the database, and the matches are displayed based on their similarity level. |
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Video Recording Task |
Generate intelligent structured analysis on history videos (when using with the platform), extract structured information on moving targets, and the video recording task can be accelerated automatically. |
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Local Task |
Generate a structured analysis of your uploaded local video files, and extract information on moving targets, and the local task can be accelerated automatically. |
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Display Tracks on the Map |
Yes (when using with the platform) |
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Computing Node Cluster |
Supports clusters (when it is set to work with the video cloud platform) |
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Metadata Analytics Performance |
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Intelligent Video Stream |
Supports real-time display of structured intelligent video streaming, including target attributes, and displays up to 5 items at the same time. Pedestrians (age, gender, top clothes and color, hat, umbrella and bag), vehicle (model, brand, license plate and color) |
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Metadata Analytics Performance |
One T4 card supports up to 32-channel real-time 1080p video analysis of moving target or 100 images/s (1080p) metadata analysis of target or 3 million images/day (1080p) structured analysis. |
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Search by Image Performance |
One server supports up to 40 million data in snapshot database, searching by image and responding in seconds(only in the case of working with video cloud platform, and exclusive use of hardware resources of single server) |
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Detection Rate of Moving Target |
With normal light in the day and normal fill light at night, resolution ≥40 × 80, clear, distinguishable pedestrians and non-motor vehicles: |
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Pedestrian Recognition Accuracy |
With normal light in the day and normal fill light at night, resolution ≥80×160, clear and distinguishable pedestrians: |
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Recognition Accuracy of Non-motor Vehicle |
With normal light in the day and normal fill light at night, resolution ≥80×160, clear and distinguishable non-motor vehicles: |
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Vehicle Recognition Accuracy |
With normal light in the day and normal fill light at night, resolution ≥240×240, clear, distinguishable motor vehicles: |
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Port |
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Network Port |
2 × 10000/1000 MB self-adaptive network ports |
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USB |
2 × front USB3.0 ports and 3 × rear USB3.0 ports |
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VGA |
2 × VGA ports |
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Others |
1 × RJ-45 management network port |
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General |
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Power Supply |
100–127 V/200–240 V, 50/60 Hz, 10 A/5 A |
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Power Redundancy |
Dual |
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Power Consumption |
≤ 800 W |
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Operating Temperature |
10°C to 35°C (50°F to 95°F ) |
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Operating Humidity |
35%–80% (RH), maximum relative humidity is 90%(RH) (40°C ). |
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Storage Temperature |
–40°C to 60°C (–40°F to 140°F) |
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Storage Humidity |
20%–93% (RH) |
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Gross Weight |
35 kg (77.16 lb) |
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Net Weight |
27.5 kg (60.63 lb) |
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Product Dimensions |
87.1 mm × 447.6 mm × 735.0 mm (3.43" × 17.62" × 28.94") (H × W × D) |
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Packaging Dimensions |
273.0 mm × 754.0 mm × 1069.0 mm (10.74" × 29.68" × 42.09") (H × W × D) |
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Installation |
Standard 19'' rack installation with guide rail |
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BTU |
≤2729.7 Btu/h |
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Optional |
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Product Type |
Hardware |