https://docs.vcloud.ai/api.php?action=feedcontributions&user=Danifo&feedformat=atomvCloud.ai Documentation - User contributions [en]2024-03-29T09:07:47ZUser contributionsMediaWiki 1.37.2https://docs.vcloud.ai/index.php?title=VCloud.ai_License_Plate_Recognition_VCA&diff=653VCloud.ai License Plate Recognition VCA2022-05-31T11:56:32Z<p>Danifo: </p>
<hr />
<div>'''Vehicle License Plates Recognition Module'''<br />
<br />
== '''Main functionality''' ==<br />
* License plates recognition accuracy up to 99%.<br />
* ''ANPR'' system can read ''license plates'' of ''vehicles'' traveling at ''speed up to 250'' km/h.<br />
* Recognition of vehicle brands, models, and colors with accuracy 95%.<br />
* More than 60 countries supported.<br />
* Support for one- and two-line, regular, reverse, and special types of license plates.<br />
* Real-time notifications based on alarms from recognized license plates.<br />
* Notifications in Telegram, by SMS or email.<br />
* Restricted access to notifications for a pre-defined group of users.<br />
* Unified database of registered vehicles.<br />
* Ability to build reports on an hourly, daily, weekly, or monthly basis.<br />
* Support for import (CSV) and export of vehicle databases (EXCEL, PDF, CSV, JSON).<br />
<br />
== '''Camera Installation Guidelines''' ==<br />
The detection rate and accuracy of an ALPR system strongly depend on the quality of the images captured by the camera. Main condition is that the camera should capture images of license plates with close to perfect sharpness and contrast, day and night and in different weather conditions. This manual describes the key requirements for license plate recognition including hardware, installation, and configuration.<br />
<br />
It is recommended to minimize the angle between the camera and the travel direction of the car, as shown in Picture 1. Ideally, you should place the camera right above the vehicles, or not too high. It is, however, a good idea to place the camera higher than the car headlights, to avoid blinding the camera with strong light.<br />
<br />
'''Picture 1'''<br />
<br />
[[File:Pic_1.png|frameless]]<br />
<br />
The total angle between the camera and the travel direction of the car can be estimated from Tables 1 and 2. We recommend keeping the total angle below 30°.<br />
<br />
'''Table 1.'''<br />
[[File:Image 2.png|thumb|none]]<br />
<br />
'''Table 2.'''<br />
[[File:Table2.png|thumb|none]]<br />
<br />
<br />
'''Camera alignment'''<br />
<br />
The camera should be pointed at the road so that the relevant lanes are centered in the image. It should be zoomed in to cover the required number of lanes. The roll angle of the camera should be adjusted so that the license plate is parallel to the edges of the image, see Picture 2.<br />
'''Picture 2.'''<br />
[[File:Pic2.png|none|thumb]]<br />
The distance between the camera and the road part that it captures is called the capture distance, shown in Picture 1. The capture distance should be chosen carefully since it will influence, in several ways, the possibility to detect license plates. We will show different parameters that affect the choice of capture distance.<br />
<br />
The camera needs to be well focused so the captured license plates would be well readable. The image is, however, sharp not only at one specific distance but in a range of distances around the focal plane, as illustrated in Picture 3. The size of this range is called the depth of field (DOF). The DOF is normally larger for a longer capture distance. The DOF can be increased by reducing the size of the iris aperture. This is only necessary for short capture distances, below 10 m when the DOF is small. Reducing the iris aperture should be done carefully since it limits the low-light performance of the camera.<br />
<br />
'''Picture 3.'''<br />
[[File:Pic3.png|none|thumb]]<br />
<br />
<br />
'''Detectable range'''<br />
<br />
The detectable range is the range of distances along the road where the license plate is visible and readable in the image, see Picture 4. Ideally, the detectable range is the full field of view of the camera, but this is not always the case. The detectable range can be limited by the depth of field of the camera, and vehicles that are far away are sometimes too small for processing by the image sensor.<br />
<br />
'''Picture 4.'''<br />
[[File:Pic4.png|none|thumb]]<br />
Weather conditions such as snow, rain, and fog can severely limit the visibility at long capture distances and hence limit the detectable range.<br />
<br />
In the daytime and in good weather conditions, the detectable range increases with longer capture distance. For vehicles moving at high speed, it is necessary to use a long capture distance, to have enough time to read the license plate before the car exits the field of view.<br />
<br />
<br />
'''Recommended capture distance'''<br />
<br />
Table 3 shows the recommended minimum capture distance depending on the speed of the vehicles. The numbers are based on an estimated detection time of 0.2 s, which means that the ALPR analytics software can analyze five frames per second. Note that the number of analyzed frames per second can vary in different processors, and also depends on the resolution of the images. The table is just an example.<br />
<br />
'''Table 3.'''<br />
[[File:T3.png|none|thumb]]<br />
At night, the maximum possible capture distance is often limited by IR reach. The IR reach can be improved by using more powerful external IR sources.<br />
<br />
'''IR light'''<br />
<br />
Capturing license plates at night requires artificial lighting. Normally, infrared (IR) light is used since it is invisible to the eye and will not blind the drivers. Most license plates are IR reflective, and IR light will increase the visibility and contrast of the plate in darkness or cloudy weather. The IR light can come from LEDs built into the camera, or from IR sources that are external to the camera.<br />
<br />
The intensity of light decreases with the distance, squared, to the light source. For a reflective object, such as a license plate, this leads to the fact that each doubling of the distance between the light source and the object will require a fourfold increase in IR power, in order for the object to keep the same visibility.<br />
<br />
If the IR reach is not enough with the built-in LEDs, or if a camera does not have built-in IR LEDs, external IR can be used. The light cone of the IR source should match the field of view of the camera, at the relevant zoom level. License plates are made from retro-reflecting material, which means that they reflect light straight back where it came from, no matter at which angle the light hits the plate. When using an external IR source, the reflected IR light will come back towards the source, as illustrated in Picture 5.<br />
<br />
'''Picture 5.'''<br />
[[File:Pic5.png|none|thumb]]<br />
External IR sources need to be placed close to the camera so the reflected light hits the camera. Picture 5 shows the relative contrast of a license plate 10 m away, as a function of the distance between the camera and the external IR source.<br />
<br />
The IR source should be aligned parallel to the camera, ensuring that the light shines on the part of the road that is in the camera’s field of view.<br />
<br />
'''Camera settings'''<br />
<br />
Specialized license plate cameras are built with suitable default settings and require a minimum of tuning. For other cameras, the following settings might need to be applied.<br />
<br />
'''Max shutter speed'''<br />
<br />
Vehicles that are moving fast may cause motion blur, as shown in the Picture 6 if the shutter speed of the camera is too high. The maximum shutter speed depends on the alignment of the camera as well as the speed of the vehicles.<br />
<br />
'''Picture 6.'''<br />
[[File:Picture6.png|none|thumb]]<br />
Car that is approaching the camera will get larger as it approaches. But once there is an angle between the camera and the direction of movement, the car will move laterally in the image at a speed that depends on the angle. Lateral movement will result in motion blur at a normal shutter speed of about 1/30 sec., so the max shutter speed needs to be limited. Table 4 shows the recommended maximum shutter speed depending on the angle between the camera and the direction of travel of the vehicle, as well as the speed of the vehicles. The camera angle can be estimated from tables 1 and 2.<br />
<br />
Table 4.<br />
[[File:T4.png|none|thumb]]<br />
<br />
<br />
'''1 ms = 1/1000s'''<br />
<br />
Note that the camera will collect more light at a faster shutter speed, which increases the IR range. For example, by setting the camera at a 5 ° angle instead of a 20 ° angle, the shutter speed can be increased four times, which will double the IR range.<br />
<br />
'''Max gain'''<br />
<br />
Since the license plate is made of reflective material, it will glow brightly when exposed to intense infrared light. Objects around will be much darker as they reflect much less light. As a result, license plate gets overexposed and impossible to read.<br />
<br />
The simplest way to avoid overexposing the license plate is to limit the max gain of the camera, as shown in Picture 7.<br />
<br />
<br />
'''Picture 7.'''<br />
[[File:Picture7.png|none|thumb]] <br />
<br />
Maximum gain set up depends on the available IR intensity, distance to vehicles and camera sensitivity. Anywhere between 9dB and 21dB gives reasonable results when using built-in IR.<br />
<br />
<br />
'''WDR'''<br />
<br />
Wide dynamic range (WDR) includes various methods for increasing the dynamic range of an image. WDR is very useful for highlighting details that might otherwise be hidden in shadows, or for preventing strong light from “blinding” the camera.<br />
<br />
But WDR can cause motion artifacts in images of moving vehicles, depending on how WDR is implemented in a particular camera. We recommend to switch WDR off for license plate capture.<br />
<br />
== '''Product Description''' ==<br />
ANPR module is designed to collect and store data about vehicles as well as automatic recognition of license plates in the traffic conditions and parking.<br />
<br />
Basic data used by module:<br />
<br />
* Date and time of vehicle presence at certain section;<br />
* Frame with the vehicle as evidence (photo fixation);<br />
* Recognition of the model and color of the vehicle;<br />
* Direction of vehicle movement and route determination.<br />
<br />
All information about vehicle is stored in the database: date and time, frame with the car, license plate and vehicle model, color, the direction of movement, route.<br />
<br />
ANPR module can be used for:<br />
<br />
* Searching in the database of wanted vehicles;<br />
* Automatic detection of vehicles belonging to employees of the company;<br />
* Gate automation scenario;<br />
* As part of traffic rule violation detection system.<br />
<br />
System requirements<br />
<br />
Below are minimum system requirements for license plate recognition based on GPU for 1 video stream.<br />
<br />
{| class="wikitable"<br />
|Parameter<br />
|Recommended value<br />
|-<br />
|CPU<br />
|Intel Core i5-5575 or higher<br />
|-<br />
|RAM<br />
|2 GB RAM (+1GB make and model recognition)<br />
|-<br />
|GPU<br />
|NVIDIA 1050<br />
|-<br />
|Places for archive<br />
|up to 5 GB per day<br />
|-<br />
|Operating system<br />
|Ubuntu 18.04<br />
|}<br />
<br />
== '''Analytics''' ==<br />
To get started with ANPR analytics, click LPR in the left menu and then click analytics.<br />
[[File:Picture8.png|none|thumb]]<br />
<br />
<br />
'''Adding analytics'''<br />
<br />
The page displays a list of cameras with the status and the ability to edit, add, or delete analytics. In order to add a new license plate analytics, press '''Add Analytics''' in the upper-right corner of the screen.<br />
[[File:Pictur9.png|none|thumb]]<br />
When you click on the "Add analytics" button, the form for adding analytics opens.<br />
[[File:Picture10.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field name<br />
|Description<br />
|-<br />
|Video<br />
|Select the camera name from a drop-down list. Video stream will be used to create analytics.<br />
|-<br />
|Detection zone<br />
|License plates will be recognized in the red zone. You can reduce enlarge or move recognition zone<br />
|-<br />
|Frames to detect<br />
|The minimum number of frames for license plate recognition. Possible range from 1 to 100<br />
|-<br />
|Min plate width<br />
|The minimum license plate width for recognition is 60 pixels<br />
|-<br />
|Min plate height<br />
|The minimum license plate height for recognition is 15 pixels<br />
|}<br />
[[File:Picture11.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field name<br />
|Description<br />
|-<br />
|Hardware<br />
|For hardware acceleration, select CPU or GPU<br />
|-<br />
|Decoding<br />
|Select the hardware decoder from the drop-down list - CPU, Intel, Nvidia<br />
|-<br />
|Optimization<br />
|For hardware acceleration, select one of the technologies.<br />
|-<br />
|Frames to detect<br />
|The minimum number of frames for license plate recognition. Possible range from 1 to 100<br />
|}<br />
[[File:Picture12.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field name<br />
|Description<br />
|-<br />
|Send events to event manager<br />
|Fill in the checkbox "Send events to event manager " to create your own event for notifications sending. If necessary, it is possible to add additional parameters for further use when event is being created. Fill in the parameter fields. To add parameters, press the "+" button<br />
|-<br />
|Vehicle without number<br />
|Send notification upon detection of vehicle without license plate<br />
|-<br />
|Blur plate number in preview mode<br />
|Send notification to preview image if plate number blurred<br />
|}<br />
Camera search<br />
<br />
Search field is located at the top of the '''Analytics''' page. To find the required camera enter the name or/and status of camera.<br />
[[File:Pictiure13.png|none|thumb]]<br />
<br />
<br />
Starting and stopping analytics<br />
<br />
To start analytics, press '''Start''' button on the right side with the analytics name field. To stop analytics, press '''Stop'''.<br />
[[File:Picture15.png|none|thumb]]<br />
<br />
<br />
Editing analytics<br />
<br />
To open the license plate analytics editing window, press the '''Editor''' button on the right side of the license plate analytics page.<br />
[[File:Picture16.png|none|thumb]]<br />
By clicking the '''Editor''' icon, the page for license plate analytics editing will load.<br />
<br />
If analytics is already running before editing it is required to stop the analytics.<br />
[[File:Picture19.png|none|thumb]]<br />
<br />
<br />
Viewing analytics<br />
<br />
To view analytics, press the view icon on the right side.<br />
[[File:Picture20.png|none|thumb]]<br />
It is possible to view only active video streams. In the opened window you can view the video from the camera in real-time mode.<br />
[[File:Pict21.png|none|thumb]]<br />
There are records of recognized vehicles in the lower part of the window, which include license plate, model, and date of event.<br />
[[File:Pict22.png|none|thumb]]<br />
Click on the vehicle number in the table to view information about that vehicle.<br />
[[File:Pict23.png|none|thumb]]<br />
To view a different record, click '''Previous post''' or '''Next post.'''<br />
<br />
To download an image of a recognized vehicle, press '''Save image.'''<br />
<br />
<br />
'''Deleting analytics'''<br />
<br />
To delete one of the cameras, click on the delete icon on the right side of the analytics field.<br />
[[File:Pict24.png|none|thumb]]<br />
<br />
== '''Search''' ==<br />
Search Parameters<br />
<br />
In order to perform a vehicle search, select '''LPR''' in the left menu and click on '''Search'''.<br />
[[File:Pict25.png|none|thumb]]<br />
There are recognized vehicle search parameters available at the top of the screen.<br />
[[File:Pict26.png|none|thumb]] <br />
<br />
<br />
{| class="wikitable"<br />
|Search field<br />
|Parameters<br />
|-<br />
|License plate number<br />
|Enter vehicle license plate number in the field to search for detected license plates<br />
|-<br />
|Time frame<br />
|Select time period you want to search for<br />
|-<br />
|Camera<br />
|Select the cameras you want to search for, or check the Select by radius box. In the window that opens, set the area. The search will be performed by cameras in the selected area.<br />
|-<br />
|Color<br />
|Select the desired vehicle color in the field<br />
|-<br />
|Make<br />
|Select the vehicle brand<br />
|-<br />
|Model<br />
|Select the vehicle model<br />
|-<br />
|Country<br />
|Select the country of recognized license plate number<br />
|-<br />
|Direction<br />
|Select the direction of movement of the car<br />
|}<br />
Click on '''Search''' to display search results. Click on '''Reset''' to clear the input fields.<br />
<br />
Search Results<br />
<br />
Search results are shown in the picture below. The list consists of the following fields: number, list, make, CCD (country, color, direction), date, camera.<br />
[[File:Pict27.png|none|thumb]]<br />
<br />
<br />
List<br />
<br />
In the list field, when you click on Add to the list, small window opens up where you can add recognized license plate to the one of existing lists.<br />
[[File:Pict28.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field Name<br />
|Description<br />
|-<br />
|Notes<br />
|Enter the text of notification that will be sent when the vehicle is detected<br />
|-<br />
|List<br />
|Select specific list where you want to add the number<br />
|}<br />
<br />
<br />
Camera<br />
<br />
When you click on '''Route icon''', a window will open up with the statistics of vehicle movement. When you click on the '''Map icon''', a window will open up showing the camera location. <br />
[[File:Pict29.png|none|thumb]]<br />
<br />
<br />
Photo of the car with recognized license plate <br />
<br />
On a right side of your screen, you can see picture of the car captured by camera along with the recognized license plate.<br />
[[File:Picture30.png|none|thumb]]<br />
<br />
<br />
When you click on Enlarge icon window will open up.<br />
[[File:Pict31.png|none|thumb]]<br />
In this enlarged window you will find option to export this captured image in PDF or JPG formats. <br />
<br />
Export Results<br />
<br />
Records can be exported in JSON or Excel format. To perform export, click on JSON or Excel.<br />
[[File:Pict32.png|none|thumb]]<br />
<br />
== '''Lists''' ==<br />
To create a database of license plate numbers to be recognized, select LPR in the menu on the left and click on '''Lists'''.<br />
[[File:Pict33.png|none|thumb]]By clicking on the list name, page with the license plates added to this list opens up.<br />
<br />
Lists Search<br />
<br />
There is a search field at the top of the screen. To find required list, enter the name or part of it in the '''Name''' field.<br />
[[File:Pict34.png|none|thumb]]<br />
Click on '''Search''' to display the search results. Click on '''Reset''' to clear the input fields. Search by number opens up list of all license plate numbers in the system and allows to perform search by license plate number.<br />
<br />
Adding List<br />
<br />
In order to add a new list, click on '''Add List''' in the upper-right corner of the screen.<br />
[[File:Pict35.png|none|thumb]]<br />
Fill in the fields in the opened window:<br />
[[File:Pict36.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field name<br />
|Description<br />
|-<br />
|Name<br />
|List name<br />
|-<br />
|Note<br />
|Description of the purpose for the record to be created<br />
|-<br />
|Camera<br />
|Select the camera from a drop-down list. The selected cameras will be used to search for the vehicle with the specified number<br />
|-<br />
|Send notifications if a recognized plate number is in the list<br />
|Send notifications on recognized license plates to external sources (Telegram, Email, etc.), check the box in the selected field.<br />
|-<br />
|Events<br />
|From the drop-down list, select the event for which notifications will be sent.<br />
|-<br />
|Additional parameters<br />
|If necessary, it is possible to add additional parameters for further use when event being created. Fill in the parameter fields. To add parameters, press the "+" button. To remove parameters, press " -".<br />
|}<br />
Editing list<br />
<br />
To edit list, click on edit icon in the right side.<br />
[[File:Pict37.png|none|thumb]]<br />
<br />
<br />
Deleting list<br />
<br />
To delete the list, click trash bin icon on the right side of the screen.<br />
[[File:Pict38.png|none|thumb]]<br />
Viewing list<br />
<br />
To view the list content, click on eye icon.<br />
[[File:Pict39.png|none|thumb]]<br />
Click '''Import CSV''' to upload a CSV file with a list of license plate numbers.<br />
[[File:Pic40.png|none|thumb]]<br />
Adding license late to the list manually<br />
<br />
In order to add a new record, click on '''Add License Plate''' in the upper-right corner of the screen.<br />
[[File:Pic41.png|none|thumb]]<br />
<br />
<br />
As a result, small window will be opened.<br />
[[File:Pict43.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field Name<br />
|Description<br />
|-<br />
|Number<br />
|Enter the license plate number of the vehicle you want to find in the field. Search will be performed by the cameras that were selected when creating the list.<br />
<br />
In addition to the full format number, you can enter the number using additional characters:<br />
<br />
% - 0 or more characters omitted<br />
<br />
$ - 1 character omitted<br />
<br />
@ - 1 letter omitted<br />
<br />
_ - 1 symbol omitted<br />
|-<br />
|Message<br />
|Enter the text of the notification that will be sent when the vehicle is detected.<br />
|}<br />
Viewing license plate number<br />
<br />
To view information about license plate number, click on its name or on the view icon.<br />
[[File:Pict44.png|none|thumb]]<br />
Once you click on it window opens up with the information about this particular record.<br />
[[File:Pic45.png|none|thumb]]<br />
Deleting license plate number from the list<br />
[[File:Pict46.png|none|thumb]]<br />
Clicking the '''Delete''' button opens a form with a suggestion to delete the license plate number from the list s. To confirm this operation, press '''Yes,''' and to cancel press '''No.'''<br />
<br />
== '''Events''' ==<br />
To view information about received events, select LPR in the menu on the left and click on '''Events'''.<br />
[[File:Pict49.png|none|thumb]]<br />
After the camera set up for LPR detection and events start<br />
<br />
After set up for LPR detections is done and camera stared to capture license plates, information about such events will be displayed in the Events section.<br />
[[File:Pict50.png|none|thumb]]<br />
Event search<br />
<br />
There is a search field at the top of the screen.<br />
[[File:Pict52.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field name<br />
|Description<br />
|-<br />
|Number<br />
|Enter the vehicle number in the field<br />
<br />
In addition to the full format number, you can enter the number using additional characters:<br />
<br />
% - 0 or more characters omitted<br />
<br />
$ - 1 character omitted<br />
<br />
@ - 1 letter omitted<br />
<br />
_ - 1 symbol omitted<br />
|-<br />
|Period<br />
|Click on the field and select the desired time period.<br />
|-<br />
|List<br />
|Click on the field and select the necessary list.<br />
|-<br />
|Accepted<br />
|Click on the field and select the user who received notifications.<br />
|}<br />
<br />
<br />
<br />
Click on '''Search''' to display the search results. Click on '''Reset''' to clear the input fields.<br />
<br />
<br />
Viewing vehicle license plate number<br />
<br />
Click on the list name in the Events page to view information about records related to this specific list.<br />
[[File:Pict56.png|none|thumb]]<br />
Click Edit to change the data.<br />
[[File:Pict53.png|none|thumb]]<br />
In the opened window you can change the following fields:<br />
[[File:Pict57.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field name<br />
|Description<br />
|-<br />
|Number<br />
|Enter the vehicle number in the field<br />
|-<br />
|Message<br />
|Enter a message in the field. The message should contain information about the vehicle<br />
|-<br />
|List<br />
|Press on the field and select the list with the number<br />
|}<br />
<br />
<br />
Clicking the Delete button opens a form with a suggestion to delete the number from the list of vehicles. To confirm the deletion, press Yes, and to cancel press No.<br />
[[File:Pict59.png|none|thumb]]<br />
If you press Yes, the number will be removed from the list of vehicles.<br />
<br />
Vehicle Number Export<br />
<br />
To export the card of this vehicle number in PDF format, click Export PDF.<br />
<br />
Frame<br />
<br />
To view a frame from a record, click the frame icon on the right side of the record.<br />
[[File:Pict60.png|none|thumb]]<br />
When you press on the frame icon, a window is opened with the image of the found vehicle.<br />
<br />
Camera<br />
<br />
To view the camera location, press the camera location icon.<br />
[[File:Pict61.png|none|thumb]]<br />
Accept Notification<br />
<br />
To accept a notification for yourself, press Accept in the right part of the record.<br />
[[File:Pict63.png|none|thumb]]<br />
After clicking, a confirmation window will appear. Press Yes to accept the notification, press No to cancel accepting.<br />
<br />
== '''Recognition Statistics''' ==<br />
To view vehicle recognition statistics, select LPR and go to the Recognition Statistics section.<br />
[[File:Pict64.png|none|thumb]]<br />
Vehicle recognition statistics are used for reports viewing and creating for specific periods.<br />
<br />
Recognition Statistics Filter<br />
<br />
In order to filter out the statistics for vehicles detection it is necessary to do the following:<br />
<br />
Select the time period for which statistics will be generated.<br />
[[File:Pict65.png|none|thumb]]<br />
To select a period, enter one of the following values: today, yesterday, last 7 days, last 30 days, this month, previous month, manually selected period (using calendar specify a range of days and times).<br />
<br />
Select the camera from which the video stream is being played. It is possible to select All cameras or a specific camera.<br />
<br />
Press Filter.<br />
[[File:67.png|none|thumb]]<br />
Reports Export<br />
<br />
To upload the reports, it is necessary to use the option of report downloading.<br />
[[File:68.png|none|thumb]]<br />
Statistics Viewing<br />
<br />
To view camera statistics by hours, days, weeks, and months, select the appropriate tab.<br />
[[File:69.png|none|thumb]]<br />
Camera<br />
<br />
In the Camera tab, you can see quantitative indicators of vehicle recognition by a camera.<br />
[[File:70.png|none|thumb]]<br />
<br />
Hours<br />
<br />
In the tab By the hours, you can see quantitative recognition indicators relative to the days of the week with hourly detail.<br />
[[File:Pict72.png|none|thumb]]<br />
Days<br />
<br />
In the tab Days there is the possibility to detail the vehicle recognition schedule. To do this, it is possible to use side scrolls to reduce the display width of the main chart on the upper indicator chart. It is possible to move along the main chart by moving the truncated zone horizontally.<br />
[[File:Picture2.jpg|none|thumb]]<br />
<br />
<br />
[[File:Pictur790.png|none|thumb]]<br />
To normalize the display, press the button to disable zoom.<br />
<br />
Weeks<br />
<br />
In the tab Weeks, it is possible to see quantitative recognition indicators for weeks in the selected range.<br />
[[File:Ppict80.png|none|thumb]]<br />
<br />
== '''Lists Statistics''' ==<br />
Statistics for vehicles that are in the corresponding lists are intended for reports viewing and creating for certain periods.<br />
[[File:Pict810.png|none|thumb]]<br />
Lists Statistics Filter<br />
<br />
In order to filter statistics it is necessary to perform the following actions:<br />
<br />
Select the time period for which statistics will be generated.<br />
[[File:Pict84-0.png|none|thumb]]<br />
To select a period, enter one of the following values: today, yesterday, last 7 days, last 30 days, this month, previous month, manually selected period (using calendar specify a range of days and times).<br />
<br />
Select the camera from which the video stream is being played. It is possible to select All cameras or a specific camera.<br />
<br />
Press Filter<br />
[[File:Pict85-0.png|none|thumb]]<br />
Report Export<br />
<br />
To upload the reports, it is necessary to use the option of report downloading.<br />
[[File:Pict86-0.png|none|thumb]]<br />
<br />
<br />
Statistics Viewing<br />
<br />
To view camera statistics by hours, days, weeks, and months, select the appropriate tab.<br />
<br />
[[File:Pict88-00.png|none|thumb]]<br />
<br />
== '''Camera Installation Requirements''' ==<br />
· Camera installation height requirements: recommended - 3 m or 5 m (Minimum - 1.5 m; Maximum - 10 m)<br />
<br />
· License plate image of moving vehicle should have no high-speed "blurring" effect visible to the eye<br />
<br />
· Symbols of license plate number must be applied in font and size in full accordance with the standard adopted in the country that issued this number<br />
<br />
· License plate numbers must meet the requirements for cleanliness and legibility: all symbols must be clearly visible and not obstructed by anything<br />
<br />
· License plate images should be of sufficient contrast; the difference in contrast between characters of the number and background must be visible by eye<br />
<br />
· The size of a single-line number on the image must be at least 100 * 20 (width * height) pixels on FullHD<br />
<br />
Sensor Resolution Requirements for Cameras<br />
<br />
1 lane (~ 4 m) - 1 MP (HD, 720p)<br />
<br />
2 lanes (~ 8 m) - 2 MP (Full HD, 1080p)<br />
<br />
3 lanes (~ 12 m) - 5MP</div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture2.jpg&diff=652File:Picture2.jpg2022-05-31T11:54:48Z<p>Danifo: </p>
<hr />
<div>Picture2</div>Danifohttps://docs.vcloud.ai/index.php?title=VCloud.ai_License_Plate_Recognition_VCA&diff=651VCloud.ai License Plate Recognition VCA2022-05-31T11:52:34Z<p>Danifo: </p>
<hr />
<div>'''Vehicle License Plates Recognition Module'''<br />
<br />
== '''Main functionality''' ==<br />
* License plates recognition accuracy up to 99%.<br />
* ''ANPR'' system can read ''license plates'' of ''vehicles'' traveling at ''speed up to 250'' km/h.<br />
* Recognition of vehicle brands, models, and colors with accuracy 95%.<br />
* More than 60 countries supported.<br />
* Support for one- and two-line, regular, reverse, and special types of license plates.<br />
* Real-time notifications based on alarms from recognized license plates.<br />
* Notifications in Telegram, by SMS or email.<br />
* Restricted access to notifications for a pre-defined group of users.<br />
* Unified database of registered vehicles.<br />
* Ability to build reports on an hourly, daily, weekly, or monthly basis.<br />
* Support for import (CSV) and export of vehicle databases (EXCEL, PDF, CSV, JSON).<br />
<br />
== '''Camera Installation Guidelines''' ==<br />
The detection rate and accuracy of an ALPR system strongly depend on the quality of the images captured by the camera. Main condition is that the camera should capture images of license plates with close to perfect sharpness and contrast, day and night and in different weather conditions. This manual describes the key requirements for license plate recognition including hardware, installation, and configuration.<br />
<br />
It is recommended to minimize the angle between the camera and the travel direction of the car, as shown in Picture 1. Ideally, you should place the camera right above the vehicles, or not too high. It is, however, a good idea to place the camera higher than the car headlights, to avoid blinding the camera with strong light.<br />
<br />
'''Picture 1'''<br />
<br />
[[File:Pic_1.png|frameless]]<br />
<br />
The total angle between the camera and the travel direction of the car can be estimated from Tables 1 and 2. We recommend keeping the total angle below 30°.<br />
<br />
'''Table 1.'''<br />
[[File:Image 2.png|thumb|none]]<br />
<br />
'''Table 2.'''<br />
[[File:Table2.png|thumb|none]]<br />
<br />
<br />
'''Camera alignment'''<br />
<br />
The camera should be pointed at the road so that the relevant lanes are centered in the image. It should be zoomed in to cover the required number of lanes. The roll angle of the camera should be adjusted so that the license plate is parallel to the edges of the image, see Picture 2.<br />
'''Picture 2.'''<br />
[[File:Pic2.png|none|thumb]]<br />
The distance between the camera and the road part that it captures is called the capture distance, shown in Picture 1. The capture distance should be chosen carefully since it will influence, in several ways, the possibility to detect license plates. We will show different parameters that affect the choice of capture distance.<br />
<br />
The camera needs to be well focused so the captured license plates would be well readable. The image is, however, sharp not only at one specific distance but in a range of distances around the focal plane, as illustrated in Picture 3. The size of this range is called the depth of field (DOF). The DOF is normally larger for a longer capture distance. The DOF can be increased by reducing the size of the iris aperture. This is only necessary for short capture distances, below 10 m when the DOF is small. Reducing the iris aperture should be done carefully since it limits the low-light performance of the camera.<br />
<br />
'''Picture 3.'''<br />
[[File:Pic3.png|none|thumb]]<br />
<br />
<br />
'''Detectable range'''<br />
<br />
The detectable range is the range of distances along the road where the license plate is visible and readable in the image, see Picture 4. Ideally, the detectable range is the full field of view of the camera, but this is not always the case. The detectable range can be limited by the depth of field of the camera, and vehicles that are far away are sometimes too small for processing by the image sensor.<br />
<br />
'''Picture 4.'''<br />
[[File:Pic4.png|none|thumb]]<br />
Weather conditions such as snow, rain, and fog can severely limit the visibility at long capture distances and hence limit the detectable range.<br />
<br />
In the daytime and in good weather conditions, the detectable range increases with longer capture distance. For vehicles moving at high speed, it is necessary to use a long capture distance, to have enough time to read the license plate before the car exits the field of view.<br />
<br />
<br />
'''Recommended capture distance'''<br />
<br />
Table 3 shows the recommended minimum capture distance depending on the speed of the vehicles. The numbers are based on an estimated detection time of 0.2 s, which means that the ALPR analytics software can analyze five frames per second. Note that the number of analyzed frames per second can vary in different processors, and also depends on the resolution of the images. The table is just an example.<br />
<br />
'''Table 3.'''<br />
[[File:T3.png|none|thumb]]<br />
At night, the maximum possible capture distance is often limited by IR reach. The IR reach can be improved by using more powerful external IR sources.<br />
<br />
'''IR light'''<br />
<br />
Capturing license plates at night requires artificial lighting. Normally, infrared (IR) light is used since it is invisible to the eye and will not blind the drivers. Most license plates are IR reflective, and IR light will increase the visibility and contrast of the plate in darkness or cloudy weather. The IR light can come from LEDs built into the camera, or from IR sources that are external to the camera.<br />
<br />
The intensity of light decreases with the distance, squared, to the light source. For a reflective object, such as a license plate, this leads to the fact that each doubling of the distance between the light source and the object will require a fourfold increase in IR power, in order for the object to keep the same visibility.<br />
<br />
If the IR reach is not enough with the built-in LEDs, or if a camera does not have built-in IR LEDs, external IR can be used. The light cone of the IR source should match the field of view of the camera, at the relevant zoom level. License plates are made from retro-reflecting material, which means that they reflect light straight back where it came from, no matter at which angle the light hits the plate. When using an external IR source, the reflected IR light will come back towards the source, as illustrated in Picture 5.<br />
<br />
'''Picture 5.'''<br />
[[File:Pic5.png|none|thumb]]<br />
External IR sources need to be placed close to the camera so the reflected light hits the camera. Picture 5 shows the relative contrast of a license plate 10 m away, as a function of the distance between the camera and the external IR source.<br />
<br />
The IR source should be aligned parallel to the camera, ensuring that the light shines on the part of the road that is in the camera’s field of view.<br />
<br />
'''Camera settings'''<br />
<br />
Specialized license plate cameras are built with suitable default settings and require a minimum of tuning. For other cameras, the following settings might need to be applied.<br />
<br />
'''Max shutter speed'''<br />
<br />
Vehicles that are moving fast may cause motion blur, as shown in the Picture 6 if the shutter speed of the camera is too high. The maximum shutter speed depends on the alignment of the camera as well as the speed of the vehicles.<br />
<br />
'''Picture 6.'''<br />
[[File:Picture6.png|none|thumb]]<br />
Car that is approaching the camera will get larger as it approaches. But once there is an angle between the camera and the direction of movement, the car will move laterally in the image at a speed that depends on the angle. Lateral movement will result in motion blur at a normal shutter speed of about 1/30 sec., so the max shutter speed needs to be limited. Table 4 shows the recommended maximum shutter speed depending on the angle between the camera and the direction of travel of the vehicle, as well as the speed of the vehicles. The camera angle can be estimated from tables 1 and 2.<br />
<br />
Table 4.<br />
[[File:T4.png|none|thumb]]<br />
<br />
<br />
'''1 ms = 1/1000s'''<br />
<br />
Note that the camera will collect more light at a faster shutter speed, which increases the IR range. For example, by setting the camera at a 5 ° angle instead of a 20 ° angle, the shutter speed can be increased four times, which will double the IR range.<br />
<br />
'''Max gain'''<br />
<br />
Since the license plate is made of reflective material, it will glow brightly when exposed to intense infrared light. Objects around will be much darker as they reflect much less light. As a result, license plate gets overexposed and impossible to read.<br />
<br />
The simplest way to avoid overexposing the license plate is to limit the max gain of the camera, as shown in Picture 7.<br />
<br />
<br />
'''Picture 7.'''<br />
[[File:Picture7.png|none|thumb]] <br />
<br />
Maximum gain set up depends on the available IR intensity, distance to vehicles and camera sensitivity. Anywhere between 9dB and 21dB gives reasonable results when using built-in IR.<br />
<br />
<br />
'''WDR'''<br />
<br />
Wide dynamic range (WDR) includes various methods for increasing the dynamic range of an image. WDR is very useful for highlighting details that might otherwise be hidden in shadows, or for preventing strong light from “blinding” the camera.<br />
<br />
But WDR can cause motion artifacts in images of moving vehicles, depending on how WDR is implemented in a particular camera. We recommend to switch WDR off for license plate capture.<br />
<br />
== '''Product Description''' ==<br />
ANPR module is designed to collect and store data about vehicles as well as automatic recognition of license plates in the traffic conditions and parking.<br />
<br />
Basic data used by module:<br />
<br />
* Date and time of vehicle presence at certain section;<br />
* Frame with the vehicle as evidence (photo fixation);<br />
* Recognition of the model and color of the vehicle;<br />
* Direction of vehicle movement and route determination.<br />
<br />
All information about vehicle is stored in the database: date and time, frame with the car, license plate and vehicle model, color, the direction of movement, route.<br />
<br />
ANPR module can be used for:<br />
<br />
* Searching in the database of wanted vehicles;<br />
* Automatic detection of vehicles belonging to employees of the company;<br />
* Gate automation scenario;<br />
* As part of traffic rule violation detection system.<br />
<br />
System requirements<br />
<br />
Below are minimum system requirements for license plate recognition based on GPU for 1 video stream.<br />
<br />
{| class="wikitable"<br />
|Parameter<br />
|Recommended value<br />
|-<br />
|CPU<br />
|Intel Core i5-5575 or higher<br />
|-<br />
|RAM<br />
|2 GB RAM (+1GB make and model recognition)<br />
|-<br />
|GPU<br />
|NVIDIA 1050<br />
|-<br />
|Places for archive<br />
|up to 5 GB per day<br />
|-<br />
|Operating system<br />
|Ubuntu 18.04<br />
|}<br />
<br />
== '''Analytics''' ==<br />
To get started with ANPR analytics, click LPR in the left menu and then click analytics.<br />
[[File:Picture8.png|none|thumb]]<br />
<br />
<br />
'''Adding analytics'''<br />
<br />
The page displays a list of cameras with the status and the ability to edit, add, or delete analytics. In order to add a new license plate analytics, press '''Add Analytics''' in the upper-right corner of the screen.<br />
[[File:Pictur9.png|none|thumb]]<br />
When you click on the "Add analytics" button, the form for adding analytics opens.<br />
[[File:Picture10.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field name<br />
|Description<br />
|-<br />
|Video<br />
|Select the camera name from a drop-down list. Video stream will be used to create analytics.<br />
|-<br />
|Detection zone<br />
|License plates will be recognized in the red zone. You can reduce enlarge or move recognition zone<br />
|-<br />
|Frames to detect<br />
|The minimum number of frames for license plate recognition. Possible range from 1 to 100<br />
|-<br />
|Min plate width<br />
|The minimum license plate width for recognition is 60 pixels<br />
|-<br />
|Min plate height<br />
|The minimum license plate height for recognition is 15 pixels<br />
|}<br />
[[File:Picture11.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field name<br />
|Description<br />
|-<br />
|Hardware<br />
|For hardware acceleration, select CPU or GPU<br />
|-<br />
|Decoding<br />
|Select the hardware decoder from the drop-down list - CPU, Intel, Nvidia<br />
|-<br />
|Optimization<br />
|For hardware acceleration, select one of the technologies.<br />
|-<br />
|Frames to detect<br />
|The minimum number of frames for license plate recognition. Possible range from 1 to 100<br />
|}<br />
[[File:Picture12.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field name<br />
|Description<br />
|-<br />
|Send events to event manager<br />
|Fill in the checkbox "Send events to event manager " to create your own event for notifications sending. If necessary, it is possible to add additional parameters for further use when event is being created. Fill in the parameter fields. To add parameters, press the "+" button<br />
|-<br />
|Vehicle without number<br />
|Send notification upon detection of vehicle without license plate<br />
|-<br />
|Blur plate number in preview mode<br />
|Send notification to preview image if plate number blurred<br />
|}<br />
Camera search<br />
<br />
Search field is located at the top of the '''Analytics''' page. To find the required camera enter the name or/and status of camera.<br />
[[File:Pictiure13.png|none|thumb]]<br />
<br />
<br />
Starting and stopping analytics<br />
<br />
To start analytics, press '''Start''' button on the right side with the analytics name field. To stop analytics, press '''Stop'''.<br />
[[File:Picture15.png|none|thumb]]<br />
<br />
<br />
Editing analytics<br />
<br />
To open the license plate analytics editing window, press the '''Editor''' button on the right side of the license plate analytics page.<br />
[[File:Picture16.png|none|thumb]]<br />
By clicking the '''Editor''' icon, the page for license plate analytics editing will load.<br />
<br />
If analytics is already running before editing it is required to stop the analytics.<br />
[[File:Picture19.png|none|thumb]]<br />
<br />
<br />
Viewing analytics<br />
<br />
To view analytics, press the view icon on the right side.<br />
[[File:Picture20.png|none|thumb]]<br />
It is possible to view only active video streams. In the opened window you can view the video from the camera in real-time mode.<br />
[[File:Pict21.png|none|thumb]]<br />
There are records of recognized vehicles in the lower part of the window, which include license plate, model, and date of event.<br />
[[File:Pict22.png|none|thumb]]<br />
Click on the vehicle number in the table to view information about that vehicle.<br />
[[File:Pict23.png|none|thumb]]<br />
To view a different record, click '''Previous post''' or '''Next post.'''<br />
<br />
To download an image of a recognized vehicle, press '''Save image.'''<br />
<br />
<br />
'''Deleting analytics'''<br />
<br />
To delete one of the cameras, click on the delete icon on the right side of the analytics field.<br />
[[File:Pict24.png|none|thumb]]<br />
<br />
== '''Search''' ==<br />
Search Parameters<br />
<br />
In order to perform a vehicle search, select '''LPR''' in the left menu and click on '''Search'''.<br />
[[File:Pict25.png|none|thumb]]<br />
There are recognized vehicle search parameters available at the top of the screen.<br />
[[File:Pict26.png|none|thumb]] <br />
<br />
<br />
{| class="wikitable"<br />
|Search field<br />
|Parameters<br />
|-<br />
|License plate number<br />
|Enter vehicle license plate number in the field to search for detected license plates<br />
|-<br />
|Time frame<br />
|Select time period you want to search for<br />
|-<br />
|Camera<br />
|Select the cameras you want to search for, or check the Select by radius box. In the window that opens, set the area. The search will be performed by cameras in the selected area.<br />
|-<br />
|Color<br />
|Select the desired vehicle color in the field<br />
|-<br />
|Make<br />
|Select the vehicle brand<br />
|-<br />
|Model<br />
|Select the vehicle model<br />
|-<br />
|Country<br />
|Select the country of recognized license plate number<br />
|-<br />
|Direction<br />
|Select the direction of movement of the car<br />
|}<br />
Click on '''Search''' to display search results. Click on '''Reset''' to clear the input fields.<br />
<br />
Search Results<br />
<br />
Search results are shown in the picture below. The list consists of the following fields: number, list, make, CCD (country, color, direction), date, camera.<br />
[[File:Pict27.png|none|thumb]]<br />
<br />
<br />
List<br />
<br />
In the list field, when you click on Add to the list, small window opens up where you can add recognized license plate to the one of existing lists.<br />
[[File:Pict28.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field Name<br />
|Description<br />
|-<br />
|Notes<br />
|Enter the text of notification that will be sent when the vehicle is detected<br />
|-<br />
|List<br />
|Select specific list where you want to add the number<br />
|}<br />
<br />
<br />
Camera<br />
<br />
When you click on '''Route icon''', a window will open up with the statistics of vehicle movement. When you click on the '''Map icon''', a window will open up showing the camera location. <br />
[[File:Pict29.png|none|thumb]]<br />
<br />
<br />
Photo of the car with recognized license plate <br />
<br />
On a right side of your screen, you can see picture of the car captured by camera along with the recognized license plate.<br />
[[File:Picture30.png|none|thumb]]<br />
<br />
<br />
When you click on Enlarge icon window will open up.<br />
[[File:Pict31.png|none|thumb]]<br />
In this enlarged window you will find option to export this captured image in PDF or JPG formats. <br />
<br />
Export Results<br />
<br />
Records can be exported in JSON or Excel format. To perform export, click on JSON or Excel.<br />
[[File:Pict32.png|none|thumb]]<br />
<br />
== '''Lists''' ==<br />
To create a database of license plate numbers to be recognized, select LPR in the menu on the left and click on '''Lists'''.<br />
[[File:Pict33.png|none|thumb]]By clicking on the list name, page with the license plates added to this list opens up.<br />
<br />
Lists Search<br />
<br />
There is a search field at the top of the screen. To find required list, enter the name or part of it in the '''Name''' field.<br />
[[File:Pict34.png|none|thumb]]<br />
Click on '''Search''' to display the search results. Click on '''Reset''' to clear the input fields. Search by number opens up list of all license plate numbers in the system and allows to perform search by license plate number.<br />
<br />
Adding List<br />
<br />
In order to add a new list, click on '''Add List''' in the upper-right corner of the screen.<br />
[[File:Pict35.png|none|thumb]]<br />
Fill in the fields in the opened window:<br />
[[File:Pict36.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field name<br />
|Description<br />
|-<br />
|Name<br />
|List name<br />
|-<br />
|Note<br />
|Description of the purpose for the record to be created<br />
|-<br />
|Camera<br />
|Select the camera from a drop-down list. The selected cameras will be used to search for the vehicle with the specified number<br />
|-<br />
|Send notifications if a recognized plate number is in the list<br />
|Send notifications on recognized license plates to external sources (Telegram, Email, etc.), check the box in the selected field.<br />
|-<br />
|Events<br />
|From the drop-down list, select the event for which notifications will be sent.<br />
|-<br />
|Additional parameters<br />
|If necessary, it is possible to add additional parameters for further use when event being created. Fill in the parameter fields. To add parameters, press the "+" button. To remove parameters, press " -".<br />
|}<br />
Editing list<br />
<br />
To edit list, click on edit icon in the right side.<br />
[[File:Pict37.png|none|thumb]]<br />
<br />
<br />
Deleting list<br />
<br />
To delete the list, click trash bin icon on the right side of the screen.<br />
[[File:Pict38.png|none|thumb]]<br />
Viewing list<br />
<br />
To view the list content, click on eye icon.<br />
[[File:Pict39.png|none|thumb]]<br />
Click '''Import CSV''' to upload a CSV file with a list of license plate numbers.<br />
[[File:Pic40.png|none|thumb]]<br />
Adding license late to the list manually<br />
<br />
In order to add a new record, click on '''Add License Plate''' in the upper-right corner of the screen.<br />
[[File:Pic41.png|none|thumb]]<br />
<br />
<br />
As a result, small window will be opened.<br />
[[File:Pict43.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field Name<br />
|Description<br />
|-<br />
|Number<br />
|Enter the license plate number of the vehicle you want to find in the field. Search will be performed by the cameras that were selected when creating the list.<br />
<br />
In addition to the full format number, you can enter the number using additional characters:<br />
<br />
% - 0 or more characters omitted<br />
<br />
$ - 1 character omitted<br />
<br />
@ - 1 letter omitted<br />
<br />
_ - 1 symbol omitted<br />
|-<br />
|Message<br />
|Enter the text of the notification that will be sent when the vehicle is detected.<br />
|}<br />
Viewing license plate number<br />
<br />
To view information about license plate number, click on its name or on the view icon.<br />
[[File:Pict44.png|none|thumb]]<br />
Once you click on it window opens up with the information about this particular record.<br />
[[File:Pic45.png|none|thumb]]<br />
Deleting license plate number from the list<br />
[[File:Pict46.png|none|thumb]]<br />
Clicking the '''Delete''' button opens a form with a suggestion to delete the license plate number from the list s. To confirm this operation, press '''Yes,''' and to cancel press '''No.'''<br />
<br />
== '''Events''' ==<br />
To view information about received events, select LPR in the menu on the left and click on '''Events'''.<br />
[[File:Pict49.png|none|thumb]]<br />
After the camera set up for LPR detection and events start<br />
<br />
After set up for LPR detections is done and camera stared to capture license plates, information about such events will be displayed in the Events section.<br />
[[File:Pict50.png|none|thumb]]<br />
Event search<br />
<br />
There is a search field at the top of the screen.<br />
[[File:Pict52.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field name<br />
|Description<br />
|-<br />
|Number<br />
|Enter the vehicle number in the field<br />
<br />
In addition to the full format number, you can enter the number using additional characters:<br />
<br />
% - 0 or more characters omitted<br />
<br />
$ - 1 character omitted<br />
<br />
@ - 1 letter omitted<br />
<br />
_ - 1 symbol omitted<br />
|-<br />
|Period<br />
|Click on the field and select the desired time period.<br />
|-<br />
|List<br />
|Click on the field and select the necessary list.<br />
|-<br />
|Accepted<br />
|Click on the field and select the user who received notifications.<br />
|}<br />
<br />
<br />
<br />
Click on '''Search''' to display the search results. Click on '''Reset''' to clear the input fields.<br />
<br />
<br />
Viewing vehicle license plate number<br />
<br />
Click on the list name in the Events page to view information about records related to this specific list.<br />
[[File:Pict56.png|none|thumb]]<br />
Click Edit to change the data.<br />
[[File:Pict53.png|none|thumb]]<br />
In the opened window you can change the following fields:<br />
[[File:Pict57.png|none|thumb]]<br />
{| class="wikitable"<br />
|Field name<br />
|Description<br />
|-<br />
|Number<br />
|Enter the vehicle number in the field<br />
|-<br />
|Message<br />
|Enter a message in the field. The message should contain information about the vehicle<br />
|-<br />
|List<br />
|Press on the field and select the list with the number<br />
|}<br />
<br />
<br />
Clicking the Delete button opens a form with a suggestion to delete the number from the list of vehicles. To confirm the deletion, press Yes, and to cancel press No.<br />
[[File:Pict59.png|none|thumb]]<br />
If you press Yes, the number will be removed from the list of vehicles.<br />
<br />
Vehicle Number Export<br />
<br />
To export the card of this vehicle number in PDF format, click Export PDF.<br />
<br />
Frame<br />
<br />
To view a frame from a record, click the frame icon on the right side of the record.<br />
[[File:Pict60.png|none|thumb]]<br />
When you press on the frame icon, a window is opened with the image of the found vehicle.<br />
<br />
Camera<br />
<br />
To view the camera location, press the camera location icon.<br />
[[File:Pict61.png|none|thumb]]<br />
Accept Notification<br />
<br />
To accept a notification for yourself, press Accept in the right part of the record.<br />
[[File:Pict63.png|none|thumb]]<br />
After clicking, a confirmation window will appear. Press Yes to accept the notification, press No to cancel accepting.<br />
<br />
== '''Recognition Statistics''' ==<br />
To view vehicle recognition statistics, select LPR and go to the Recognition Statistics section.<br />
[[File:Pict64.png|none|thumb]]<br />
Vehicle recognition statistics are used for reports viewing and creating for specific periods.<br />
<br />
Recognition Statistics Filter<br />
<br />
In order to filter out the statistics for vehicles detection it is necessary to do the following:<br />
<br />
Select the time period for which statistics will be generated.<br />
[[File:Pict65.png|none|thumb]]<br />
To select a period, enter one of the following values: today, yesterday, last 7 days, last 30 days, this month, previous month, manually selected period (using calendar specify a range of days and times).<br />
<br />
Select the camera from which the video stream is being played. It is possible to select All cameras or a specific camera.<br />
<br />
Press Filter.<br />
[[File:67.png|none|thumb]]<br />
Reports Export<br />
<br />
To upload the reports, it is necessary to use the option of report downloading.<br />
[[File:68.png|none|thumb]]<br />
Statistics Viewing<br />
<br />
To view camera statistics by hours, days, weeks, and months, select the appropriate tab.<br />
[[File:69.png|none|thumb]]<br />
Camera<br />
<br />
In the Camera tab, you can see quantitative indicators of vehicle recognition by a camera.<br />
[[File:70.png|none|thumb]]<br />
<br />
Hours<br />
<br />
In the tab By the hours, you can see quantitative recognition indicators relative to the days of the week with hourly detail.<br />
[[File:Pict72.png|none|thumb]]<br />
Days<br />
<br />
In the tab Days there is the possibility to detail the vehicle recognition schedule. To do this, it is possible to use side scrolls to reduce the display width of the main chart on the upper indicator chart. It is possible to move along the main chart by moving the truncated zone horizontally.<br />
<br />
<br />
<br />
[[File:Pictur790.png|none|thumb]]<br />
To normalize the display, press the button to disable zoom.<br />
<br />
Weeks<br />
<br />
In the tab Weeks, it is possible to see quantitative recognition indicators for weeks in the selected range.<br />
[[File:Ppict80.png|none|thumb]]<br />
<br />
== '''Lists Statistics''' ==<br />
Statistics for vehicles that are in the corresponding lists are intended for reports viewing and creating for certain periods.<br />
[[File:Pict810.png|none|thumb]]<br />
Lists Statistics Filter<br />
<br />
In order to filter statistics it is necessary to perform the following actions:<br />
<br />
Select the time period for which statistics will be generated.<br />
[[File:Pict84-0.png|none|thumb]]<br />
To select a period, enter one of the following values: today, yesterday, last 7 days, last 30 days, this month, previous month, manually selected period (using calendar specify a range of days and times).<br />
<br />
Select the camera from which the video stream is being played. It is possible to select All cameras or a specific camera.<br />
<br />
Press Filter<br />
[[File:Pict85-0.png|none|thumb]]<br />
Report Export<br />
<br />
To upload the reports, it is necessary to use the option of report downloading.<br />
[[File:Pict86-0.png|none|thumb]]<br />
<br />
<br />
Statistics Viewing<br />
<br />
To view camera statistics by hours, days, weeks, and months, select the appropriate tab.<br />
<br />
[[File:Pict88-00.png|none|thumb]]<br />
<br />
== '''Camera Installation Requirements''' ==<br />
· Camera installation height requirements: recommended - 3 m or 5 m (Minimum - 1.5 m; Maximum - 10 m)<br />
<br />
· License plate image of moving vehicle should have no high-speed "blurring" effect visible to the eye<br />
<br />
· Symbols of license plate number must be applied in font and size in full accordance with the standard adopted in the country that issued this number<br />
<br />
· License plate numbers must meet the requirements for cleanliness and legibility: all symbols must be clearly visible and not obstructed by anything<br />
<br />
· License plate images should be of sufficient contrast; the difference in contrast between characters of the number and background must be visible by eye<br />
<br />
· The size of a single-line number on the image must be at least 100 * 20 (width * height) pixels on FullHD<br />
<br />
Sensor Resolution Requirements for Cameras<br />
<br />
1 lane (~ 4 m) - 1 MP (HD, 720p)<br />
<br />
2 lanes (~ 8 m) - 2 MP (Full HD, 1080p)<br />
<br />
3 lanes (~ 12 m) - 5MP</div>Danifohttps://docs.vcloud.ai/index.php?title=File:VCloud.ai_BRASIL.pdf&diff=540File:VCloud.ai BRASIL.pdf2022-05-17T16:15:03Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:VCLOUDAI_EN-Q4_2021.pdf&diff=539File:VCLOUDAI EN-Q4 2021.pdf2022-05-17T16:14:30Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=VCloud.ai_VSaaS_user_manual_1.1_Italian&diff=538VCloud.ai VSaaS user manual 1.1 Italian2022-05-17T15:58:45Z<p>Danifo: Created page with "<big>'''Contents'''</big> == Esecuzione dell’App Client <br> == Trova l'app vCloud.ai nelle app installate ed eseguila, oppure apri il web browser e usa il link: https://app.vcloud.ai == Accesso al Sistema<br> == Accedi con le credenziali del tuo account vCloud:<br> none Fai Click sul pulsante '''Add provider''' oppure vai a '''Settings->Services->VSaaS''' e accedi al sistema VSaaS. In caso tu stia usando il servizio Basic di vCloud.ai, sei pregat..."</p>
<hr />
<div><big>'''Contents'''</big><br />
<br />
== Esecuzione dell’App Client <br> ==<br />
Trova l'app vCloud.ai nelle app installate ed eseguila, oppure apri il web browser e usa il link: https://app.vcloud.ai<br />
== Accesso al Sistema<br> ==<br />
Accedi con le credenziali del tuo account vCloud:<br><br />
[[File:1.png|thumb|none]]<br />
Fai Click sul pulsante '''Add provider''' oppure vai a '''Settings->Services->VSaaS''' e accedi al sistema VSaaS. In caso tu stia usando il servizio Basic di vCloud.ai, sei pregato di accedere all’account vCloud con le tue credenziali:<br><br />
[[File:2.png|thumb|none]]<br />
Le tue telecamere appariranno nell’elenco '''All devices''' nella sezione '''Devices Settings:''' <br><br />
[[File:03.png|thumb|none]]<br />
Puoi selezionare una delle telecamere per assicurarti che il client sia connesso a VSaaS e funzioni correttamente.<br><br />
[[File:04.png|thumb|none]]<br />
<br />
==Creazione e modifica dei Layout<br> ==<br />
Fai Click su '''New Layout''' nel menu principale.<br><br />
[[File:18.png|thumb|none]]<br />
La pagina di modifica del '''Layout''' si aprirà.<br><br />
[[File:06.png|thumb|none]]<br />
Fornisci al tuo nuovo Layout un '''Nome''', scegli il '''Layout Template''' e trascina le singole telecamere ovvero gruppi di esse alla griglia di Layout sul lato destro. <br><br />
[[File:07.png|thumb|none]]<br />
Fai Click su '''Save''' per salvare il tuo Layout.<br />
Per editare un Layout esistente fai Click sull’icona '''Pencil''' nel tab menu del Layout sulla parte superiore dello schermo:<br><br />
[[File:21.png|thumb|none]]<br />
<br />
==Visualizzazione dei video Live <br> ==<br />
Dopo aver creato e salvato un layout, le telecamere dovrebbero essere visualizzate sullo schermo in modalità live. Puoi vedere lo stato del nell'angolo in basso a sinistra. '''Rec''' significa che la telecamera è connessa a VSaaS e la registrazione su cloud è in corso. '''Live''' significa che la telecamera è disponibile solo per la visualizzazione live. <br><br />
[[File:09.png|thumb|none]]<br />
Utilizza i pulsanti Ingrandisci e Riduci a icona nell'angolo in alto a destra per ridimensionare le singole finestre video. In alternativa, puoi fare Click sul video con il tasto sinistro del mouse. <br><br />
[[File:010.png|thumb|none]]<br />
<br />
==Selezione dei flussi Live<br> ==<br />
Fare Click sul pulsante Impostazioni streaming video per selezionare lo streaming e attivare/disattivare la selezione automatica dello streaming.<br><br />
[[File:011.png|thumb|none]]<br />
La selezione automatica del flusso mantiene basso il traffico di rete poiché mostra il flusso a bassa risoluzione quando la finestra video è ridotta a icona e mostra il flusso ad alta risoluzione quando la finestra è ingrandita o a schermo intero.<br />
<br />
==Operare con l’audio<br> ==<br />
Nel caso in cui la telecamera trasmetta video con audio, è possibile riattivare il sonoro delle singole telecamere e regolare il volume.<br> <br />
[[File:012.png|thumb|none]]<br />
<br />
==Operare con le mappe<br> ==<br />
Fare Click sul pulsante della mappa nell'angolo in basso a destra della finestra del video per aprire la mappa.<br><br />
[[File:013.png|thumb|none]]<br />
Puoi regolare la posizione della telecamera sulla mappa nelle impostazioni: Settings->Devices->All cameras->[Camera name][Camera name]<br />
<br />
==Ripetizione rapida<br> ==<br />
Per visualizzare l'archivio degli ultimi 15 secondi di registrazione cliccare sul pulsante '''15 (quick replay)'''. Ciò commuterà istantaneamente la finestra del video in '''Archive Mode'''.<br><br />
[[File:014.png|thumb|none]]<br />
<br />
==Archivio di riproduzione<br> ==<br />
Fai Click sul pulsante di switch '''Live/Archive''' quando la finestra video è di medie dimensioni per passare ad '''Archive Mode'''<br><br />
[[File:015.png|thumb|none]]<br />
Apparirà la cronologia. Puoi ingrandire/rimpicciolire e trascinare la timeline per passare a un'ora specifica nell'archivio.<br><br />
[[File:016.png|thumb|none]]<br />
Fai Click sul '''Time Counter''' per inserire l’ora e la data manualmente.<br />
<br />
Fai Click sul pulsante '''Settings''' per selezionare la velocità di playback.<br />
<br><br />
[[File:017.png|thumb|none]]<br />
<br />
==Esportazione di filmati<br> ==<br />
Fai doppio Click sulla '''Timeline''' per selezionare i time frame da esportare. <br><br />
[[File:018.png|thumb|none]]<br />
Quindi fai Click sul pulsante di esportazione e specifica il parametro richiesto. Fai clic su Download per prepararti a scaricare il filmato. ''Tieni presente che l'archivio è immagazzinato in forma di piccoli clip video, quindi potrebbe essere necessario del tempo per preparare il video per il download sul lato server.'' <br><br />
[[File:019.png|thumb|none]]<br />
<br />
==Operare con le PTZ<br> ==<br />
Se nel sistema è presente una telecamera PTZ, è possibile fare clic sul pulsante PTZ e utilizzare i controlli pan/tilt/zoom su schermo per ruotare e ingrandire/rimpicciolire l’immagine.<br><br />
[[File:020.png|thumb|none]]<br />
<br />
==Zoom digitale<br> ==<br />
È possibile ingrandire/ridurre i flussi video e archiviare la riproduzione con lo zoom digitale con la rotellina del mouse mentre si passa con il mouse sulla finestra del video.<br><br />
==Suggerimenti<br> ==<br />
Fai Click sul pulsante [[File:021.png|thumb|none]] per abilitare e disabilitare I suggerimenti. I suggerimenti appariranno quando passi con il mouse sugli elementi attivi dell'interfaccia utente.<br><br />
[[File:022.png|thumb|none]][[File:023.png|thumb|none]]</div>Danifohttps://docs.vcloud.ai/index.php?title=VCloud.ai_VSaaS_Administrator_manual_1.1_Italian&diff=537VCloud.ai VSaaS Administrator manual 1.1 Italian2022-05-17T15:58:09Z<p>Danifo: Created page with "<big>'''Contenuti'''</big><br> == Scopo del sistema <br> == vCloud.ai Videosorveglianza come servizio (VSaaS) è un servizio online che collega le telecamere al sistema in Cloud in grado di ricevere, registrare, trasmettere, trasmettere in multicast ed elaborare più flussi video verso applicazioni (o client) Web/Mobile/Desktop. = Struttura del sistema VSaaS <br>= Le telecamere si connettono al Cloud tramite un agente abilitato a TLS che funziona su telecamere, DVR e..."</p>
<hr />
<div><big>'''Contenuti'''</big><br><br />
<br />
== Scopo del sistema <br> ==<br />
vCloud.ai Videosorveglianza come servizio (VSaaS) è un servizio online che collega le telecamere al sistema in Cloud in grado di ricevere, registrare, trasmettere, trasmettere in multicast ed elaborare più flussi video verso applicazioni (o client) Web/Mobile/Desktop.<br />
<br />
= Struttura del sistema VSaaS <br>=<br />
Le telecamere si connettono al Cloud tramite un agente abilitato a TLS che funziona su telecamere, DVR e bridge (richiedere o verificare con il produttore della telecamera il firmware supportato da vCloud).<br />
Streaming live e filmati possono essere scaricati dal Cloud tramite applicazioni (o client) Web/Mobile/Desktop. Gli utenti possono individualmente connettere al cloud un numero illimitato di telecamere e impostare piani di registrazione specifici su ciascuna di esse.<br />
[[File:VSaaS system structure.png|thumb|none]]<br />
<br />
= Requisiti Hardware<br>=<br />
<strong>Telecamera<br></strong><br />
<br />
Per potersi connettere a vCloud.ai la telecamera deve essere una telecamera IP dotata di interfaccia di rete e deve essere in grado di trasmettere video in formato H.264.<br />
<br />
La connettività dalla telecamera al Cloud è organizzata con uno dei seguenti metodi:<br><br />
3.1.1. Firmware della telecamera che supporta il servizio VSaaS di vCloud.ai. I file del firmware sono disponibili su https://vcloud.ai/downloads <br><br />
3.1.2. Bridge di vCloud.ai o NVR supportato (vedi elenco dispositivi integrati)<br><br />
3.1.3. Collegamento RTSP con un indirizzo IP pubblico<br><br />
3.1.4. Collegamento RTSP con un indirizzo DNS dinamico<br><br />
<br />
<strong>Client<br></strong><br />
3.2.1. Il client desktop richiede un PC o un computer Mac con CPU Intel/AMD a 32 oa 64 bit, Apple Silicon o altra CPU ARM, con almeno 2 core da 1,5 GHz<br><br />
3.2.2. Il client mobile richiede il sistema operativo Android o iOS, con una CPU costituita da almeno un chip quad-core e 4 GB di RAM<br><br />
3.2.3. Browser supportati: Google Chrome v.92+, Mozilla Firefox v.90+, Safari v.14+<br><br />
<br />
= Compatibilità<br>=<br />
4.1. Codec: il sistema VSaaS vCloud.ai è adatto a funzionare con qualsiasi flusso video con compressione H.264 con risoluzione fino a 8Mp. La compressione H.265 è supportata con funzionalità limitate.<br><br />
4.2. La maggior parte delle telecamere IP e analogiche sono rese compatibili dall’utilizzo di vCloud.ai Bridge.<br><br />
4.3. La connessione diretta da telecamera a Cloud funziona solo con alcuni modelli di telecamera integrati per i quali è disponibile un firmware specifico con modulo software vCloud TLS.<br><br />
<br />
= Installazione dell’App Client<br>=<br />
L’ applicazione Web client è disponibile istantaneamente al seguente link: https://app.vcloud.ai tuttavia è necessario installare un'applicazione client sul desktop che è disponibile per il download al link: https://vcloud.ai/downloads <br><br />
:<strong>a. Installazione dell’App Linux<br></strong><br />
:Una volta scaricato il file vCloud_ai_VSaaS_Linux_x_x.deb puoi installarlo dall'interfaccia utente facendo doppio Click e seguendo le istruzioni sullo schermo oppure puoi farlo con la seguente riga di comando:<br />
sudo apt install vCloud_ai_VSaaS_Linux_x_x.deb <br><br />
<br />
:<strong>b. Installazione dell’App Windows<br></strong><br />
:Una volta scaricato il file vCloud_ai_VSaaS_WIN_x_x.exe, puoi installarlo dall'interfaccia utente facendo doppio Click e seguendo le istruzioni sullo schermo.<br><br />
<br />
:<strong>c. Installazione dell’App MacOS<br></strong><br />
:Una volta scaricato il file vCloud_ai_VSaaS_WIN_x_x.dmg, puoi installarlo dall'interfaccia utente facendo doppio Click e seguendo le istruzioni sullo schermo.<br><br />
<br />
= Accesso al Sistema<br>=<br />
Dopo aver eseguito l'applicazione per la prima volta dovresti vedere la schermata di accesso.<br />
[[File:3.png|thumb|none]] Inserisci le tue credenziali valide o fai Click sul link della '''pagina di registrazione''' sottostante per una nuova registrazione. Fare Click su accedi per accedere al client.<br />
Il passaggio successivo consiste nell'aggiungere il fornitore di servizi.<br><br />
Vai su Settings->Services->VSaaS->[Provider]<br> Scegli il provider di servizi richiesto (per impostazione predefinita è vCloud.ai Basic) e inserisci le tue credenziali.<br> Si prega di notare che le credenziali del fornitore di servizi devono essere ricevute dal fornitore di servizi. In caso di domande al riguardo, inviare un'e-mail a support@vcloud.ai <br> <br />
[[File:4.png|thumb|none]]<br />
<br />
= Aggiunta di telecamere<br>=<br />
7.1. Aggiunta di una telecamera già integrata sul cloud: Camera-to-Cloud<br> <br />
::Vai su Settings->Cameras->Add camera <br><br />
::Assegna un nome alla telecamera, inserisci l'indirizzo MAC (delle telecamere integrate Camera-to-Cloud), inserisci Login e Password con le credenziali della telecamera, seleziona il fuso orario, quindi fai Click su '''Add'''. <br><br />
[[File:5.png|thumb|none]]<br />
::La telecamera dovrebbe quindi apparire nella sezione '''All cameras/Devices.'''<br><br />
[[File:6.png|thumb|none]]<br />
::vCloud.ai supporta anche la connessione in streaming RTSP da qualsiasi fonte. Ecco i passaggi da seguire per aggiungere flussi RTSP. <br><br />
<br />
<br />
7.2. Aggiunta di un flusso RTSP:<br />
::7.2.1. Vai sul link seguente per utilizzare il pannello Web legacy di <br> http://basic.vcloud.ai <br><br />
::7.2.2. Esegui l’accesso (Log in) usando le tue credenziali vCloud.ai <br> <br />
[[File:7.png|thumb|none]]<br />
::7.2.3. Fai Click sul pulsante '''Add''' <br> <br />
[[File:8.png|thumb|none]]<br />
::7.2.4. Fai Click sul pulsante '''Add Device'''<br> <br />
[[File:9.png|thumb|none]]<br />
::7.2.5. Fai Click sul pulsante '''Camera of Another Brand'''<br> <br />
[[File:10.png|thumb|none]]<br />
::7.2.6. Compila i seguenti campi: <br> <br />
[[File:11.png|thumb|none]]<br />
::7.2.7. Hai aggiunto una telecamera con un link RTSP.<br />
<br />
<br />
7.3. Aggiungere Bridge e NVR integrati<br> <br />
::7.3.1. Vai sul link seguente per utilizzare il pannello Web legacy di vCloud.ai: http://basic.vcloud.ai <br> <br />
::7.3.2. esegui l’accesso (Log in) usando le tue credenziali vCloud.ai <br><br />
[[File:7.png|thumb|none]]<br />
::7.3.3. Fai Click sul pulsante '''Add''' <br> <br />
[[File:8.png|thumb|none]]<br />
::7.3.4. Fai Click sul pulsante '''Add Device'''<br><br />
[[File:9.png|thumb|none]]<br />
::7.3.5. Fai Click sul pulsante '''Video Recorder'''<br><br />
[[File:15.png|thumb|none]]<br />
::7.3.6. Compila i seguenti campi usando le tue credenziali e fai Click sul pulsante '''Add'''<br> <br />
[[File:16.png|thumb|none]]<br />
<br />
= Setup della Mappa<br>=<br />
Per poter localizzare la telecamera sulla mappa puoi aggiungere le coordinate o semplicemente trascinare la telecamera sulla mappa e poi fare Click sul pulsante '''Save'''.<br><br />
[[File:17.png|thumb|none]]<br />
<br />
= Setup dei Layout<br>=<br />
Fai Click su New Layout nel menu principale. <br><br />
[[File:18.png|thumb|none]]<br />
La pagina di modifica del '''Layout''' si aprirà.<br><br />
[[File:19.png|thumb|none]]<br />
Fornisci al tuo nuovo Layout un '''Nome''', scegli il '''Layout Template''' e trascina le singole telecamere ovvero gruppi di esse alla griglia di Layout sul lato destro. <br> <br />
[[File:20.png|thumb|none]]<br />
Fai Click su '''Save''' per salvare il tuo Layout. <br> <br />
Per editare un Layout esistente fai Click sull’icona '''Pencil''' nel tab menu del Layout sulla parte superiore dello schermo: <br> <br />
[[File:21.png|thumb|none]]<br />
<br />
= Gruppi di telecamere<br>=<br />
Vai a Settings->Cameras->Add group e compila il campo '''Group Name'''. e poi cliccare su '''Save'''. Poi fare Click sul pulsante '''Add'''. <br><br />
[[File:22.png|thumb|none]]<br />
Per editare un gruppo esistente fai Click sull’icona '''Pencil''' alla destra del gruppo. <br> <br />
[[File:23.png|thumb|none]]<br />
Ora puoi modificare o cancellare il gruppo. <br><br />
[[File:24.png|thumb|none]]<br />
Per aggiungere una telecamera a un gruppo esistente, vai alle impostazioni della telecamera e seleziona il gruppo richiesto. <br><br />
[[File:25.png|thumb|none]]<br />
<br />
= Supporto tecnico<br>=<br />
Il supporto tecnico di vCloud.ai è operativo 24 ore su 24, 7 giorni su 7. Il tempo di risposta medio è di circa 3 ore.<br><br />
Il supporto tecnico può essere richiesto a vCloud.ai via e-mail al seguente indirizzo: [mailto:support@vcloud.ai support@vcloud.ai]</div>Danifohttps://docs.vcloud.ai/index.php?title=Italian_manuals&diff=536Italian manuals2022-05-17T15:57:59Z<p>Danifo: Created page with "* vCloud.ai VSaaS Administrator manual 1.1_ Italian * vCloud.ai VSaaS user manual 1.1_ Italian"</p>
<hr />
<div>* [[vCloud.ai VSaaS Administrator manual 1.1_ Italian]]<br />
* [[vCloud.ai VSaaS user manual 1.1_ Italian]]</div>Danifohttps://docs.vcloud.ai/index.php?title=File:Vcloudai_colours.png&diff=535File:Vcloudai colours.png2022-05-17T15:56:31Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:VCloud.ai_brandbook.png&diff=534File:VCloud.ai brandbook.png2022-05-17T15:56:04Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=Brand_Book&diff=533Brand Book2022-05-17T15:55:34Z<p>Danifo: Created page with "left left"</p>
<hr />
<div>[[File:VCloud.ai brandbook.png|1200px|frameless|left]]<br />
[[File:Vcloudai colours.png|1200px|frameless|left]]</div>Danifohttps://docs.vcloud.ai/index.php?title=Marketing_Presentations_and_Brochures&diff=532Marketing Presentations and Brochures2022-05-17T15:53:06Z<p>Danifo: Created page with "none<br> none<br>"</p>
<hr />
<div>[[File:VCLOUDAI EN-Q4 2021.pdf|thumb|none]]<br><br />
[[File:VCloud.ai BRASIL.pdf|thumb|none]]<br></div>Danifohttps://docs.vcloud.ai/index.php?title=Cluebase_VMS_Technical_Specifications&diff=531Cluebase VMS Technical Specifications2022-05-17T15:51:48Z<p>Danifo: Created page with "== Product overview <br> == vCloud.ai is new-generation Video Management Software that works on all smartphones and computers: Android, iPhone, iPad, MacBook, Windows, Linux and even Web browser of literally any device. vCloud.ai Cluebase VMS is made for reliability, performance, and convenience. Flexibility and limitlessness by design allows creating advanced computer vision systems in a very short time. The vCloud.ai API allows integrating third-party hardware and so..."</p>
<hr />
<div>== Product overview <br> ==<br />
vCloud.ai is new-generation Video Management Software that works on all smartphones and computers: Android, iPhone, iPad, MacBook, Windows, Linux and even Web browser of literally any device. vCloud.ai Cluebase VMS is made for reliability, performance, and convenience. Flexibility and limitlessness by design allows creating advanced computer vision systems in a very short time. The vCloud.ai API allows integrating third-party hardware and software to extend your video system's functionality even further. The advanced ergonomic interface makes all functions intuitively easy to use.<br><br />
<br />
== Features <br> ==<br />
<br />
• Highly scalable professional software solution for video surveillance: complete video surveillance solution from one to thousands of cameras<br><br />
• Unlimited number of cameras, servers and remote clients<br><br />
• AI video analytics<br><br />
• Supports high resolution IP cameras (up to 24 megapixel)<br><br />
• ONVIF and RTSP camera support<br><br />
• Cross-platform client application (Web/Linux/Windows/MacOS)<br><br />
• Runs on ARM and Intel/AMD CPUs<br><br />
• Container-based cross-platform server application<br><br />
• Cloud-ready video and audio recording design<br><br />
• Flexible user right management<br><br />
• Video surveillance in three modes: Live View, Archive View, Tutorial mode. <br><br />
• Google maps <br><br />
• RTSP server <br><br />
• Configuration of all components. Visual access to the functionality provided by the Server<br><br />
• All video streams from IP cameras can be recorded simultaneously in real time.<br><br />
• GPU integration that provides hardware acceleration for video encoding/decoding<br><br />
• Works with two or more independent streams from camera and is able to automatically and manually switch between them within the layout depending on the video frame size<br><br />
• Requires no proprietary recording hardware. The server application runs on ARM and Intel/AMD processors<br><br />
• True open platform design that allows integration of 3rd party hardware and software<br><br />
• Supports all brands of IP cameras through ONVIF<br><br />
• The Server and Client run on the following operating systems: Windows, MacOS and Linux. 32-bit and 64-bit versions are supported.<br><br />
• Full-featured Web application <br><br />
• Mobile apps for Android and iOS<br><br />
• Server application natively runs in Docker container<br><br />
• Archive depth can be set in days<br><br />
• Unlimited storage capacity configured per server<br><br />
• Live video is streamed in WebRTC (Web Real-Time Communication) format<br><br />
• Archive is played via HLS (HTTP Live Streaming) protocol<br><br />
• Authenticating users and giving access to the functions based on predefined user access rights<br><br />
• The Client application allows users to connect to multiple Servers. Their access rights could be determined on a per server basis or per servers’ role basis<br><br />
• Automatically records video and audio<br><br />
• Tools for archive configuration and management<br><br />
• Works with multiple storage devices mapped in the operating system<br><br />
• Tools for configuring streams for multi stream-supporting cameras - selecting a stream for live view, configuring the stream for recording<br><br />
• Allows creating cameras groups<br><br />
• Configuring layouts: creating new layouts, adding cameras to layouts, adding camera groups to layouts <br><br />
• Configuring Google maps: placing the camera icon onto a location and selecting the camera’s field of view<br><br />
• PTZ device control: pan, tilt and zoom camera control functionality <br><br />
<br />
== AI video analytics <br> ==<br />
vCloud.ai Cluebase Video Management Software incorporates a powerful system for analysis of video images based on neural networks. It includes the following video analytics: <br><br />
• Object Detection - identifies people, cars, busses, trucks, motorcycles and animals in a defined area/zone.<br><br />
• Face recognition – an algorithm for human identification and verification, based on the facial recognition as well as the age and gender estimation. The algorithm creates a database of all faces captured by video cameras and lets you search the database for similar faces.<br><br />
• License plate recognition - an algorithm for license plate recognition. Video streams can be processed to search for and recognize license plate numbers in the frame. These license plate numbers are saved to a database and associated with the relevant recorded video. The database is searchable. License plate numbers can be compared to lists in real time, with actions performed (or not performed) depending on whether or not a license plate is found in the list.<br><br />
• Traffic Analytics - intended for the calculation of intensity and determination of traffic structure classify the types of vehicles (car, bus, truck, bike, motorbike). <br><br />
• Crowd Detection - estimates the number of people within a given area in real time and triggers an alarm when a specified number of people (capacity) or a specified percentage of people (occupancy) is reached.<br><br />
• Hard Hat Detection - detects people not wearing helmets, records video and sends alarms to security service.<br><br />
• Heat Map - colour visual representation of data. analysis of customer activity presented by colour visual representation of data (warm and cold zones). <br><br />
• Age & Gender Detection - determines the gender of customers and their approximate age by detecting and analyzing the faces of visitors.<br><br />
• Motion Detection - captures any movement in the scene. The following rules can be applied: line crossing, loitering, intrusion, abandoned object, disappearance of an object.<br><br />
• Smoke & Fire Detection - recognizes smoke and fire in the image<br><br />
• Smoking Detection – recognizes person while smoking<br><br />
• Smart Tracking System - search by attributes (color of clothes, bag, hair, hat, gender, and age).<br><br />
• Body Movement Detection - identifies a person in different positions: sitting, standing, walking, falling, getting up.<br><br />
• Wagon Identification - detection and recognition of wagon UIC numbers.<br><br />
• Smart Parking - management of parking lot, detection of license plates of entering vehicles, recognition of model, direction of movement, and payment status of the car.<br></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_24.png&diff=530File:Picture 24.png2022-05-17T15:51:00Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=Cluebase_VMS_Installation_Manual&diff=529Cluebase VMS Installation Manual2022-05-17T15:50:35Z<p>Danifo: Created page with "<strong>Installation manual Contents</strong> == Automatic installation <br> == Docker container framework and Docker-compose extension are required for Cluebase VMS installation and operation.<br> 1.1. Linux<br> To install Cluebase VMS on a clean Linux OS automatically please run install.sh script.<br> To run the script please enter the folder that contains install.sh and run the following command: <br> $ sudo sh install.sh <br> 1.2. Windows<br> To install Clueb..."</p>
<hr />
<div><strong>Installation manual Contents</strong><br />
<br />
== Automatic installation <br> ==<br />
Docker container framework and Docker-compose extension are required for Cluebase VMS installation and operation.<br><br />
<br />
1.1. Linux<br><br />
<br />
To install Cluebase VMS on a clean Linux OS automatically please run install.sh script.<br><br />
<br />
To run the script please enter the folder that contains install.sh and run the following command: <br><br />
<br />
$ sudo sh install.sh <br><br />
<br />
1.2. Windows<br><br />
<br />
To install Cluebase VMS on Windows OS please run the WINDOWS_install.bat batch file. <br><br />
<br />
== Manual installation <br> ==<br />
<strong> 2.1. Installing Docker </strong><br><br />
<br />
Docker container framework and Docker-compose extension are required for Cluebase VMS installation and operation. <br><br />
<br />
2.1.1.Installing Docker on Linux<br><br />
<br />
Official Docker installation manual: https://docs.docker.com/engine/install/ubuntu/<br><br />
<br />
Run the following command:<br><br />
<br />
$ sudo apt-get update && apt-get install docker-ce docker-ce-cli containerd.io <br><br />
<br />
2.1.2. Installing docker-compose on Linux<br><br />
<br />
Run the following command:<br><br />
<br />
$ sudo curl -L "https://github.com/docker/compose/releases/download/1.29.2/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose <br><br />
<br />
Grant required access rights by running the following command:<br><br />
<br />
$ sudo chmod +x /usr/local/bin/docker-compose <br><br />
<br />
2.1.3. Installing Docker on Windows <br><br />
<br />
Download the latest version of Docker Desktop from the official website: https://www.docker.com/products/docker-desktop <br><br />
<br />
Docker Desktop installer contains Docker engine and Docker compose.<br><br />
<br />
<strong> 2.2. Preparing for VMS installation </strong> <br><br />
<br />
2.2.1. Download Cluebase.zip. Create a VMS folder and unzip the zip file contents to it. <br><br />
<br />
To install the VMS successfully you will need to edit the .env file which is the environment variable file.<br><br />
<br />
Please note that this file is hidden in the folder by default. <br><br />
<br />
2,2.2. Open the .env file and specify the server’s IP address in the following fields: <br><br />
<br />
APP_HOST=0.0.0.0 (public IP address of the server)<br />
MACHINE_HOST=0.0.0.0 (local IP address of the server) <br><br />
<br />
Both IP addresses will be the same if the VMS is supposed to be used only in the local network. <br><br />
<br />
2.2.3. Installing an running the VMS <br><br />
Get into the VMS folder and run the following command: <br><br />
<br />
$ sudo docker-compose up -d <br><br />
<br />
This command will automatically download, install and run the VMS. <br><br />
<br />
== Signing in<br> ==<br />
Open a web-browser (Google Chrome, Mozilla Firefox and Safari are recommended), input the IP address of the server and press Enter. <br><br />
[[File:Picture 24.png|thumb|none]]<br><br />
By default the login and password are: admin/admin.<br><br />
<br />
== Stopping the VMS <br> ==<br />
To stop the VMS server run the following command from the VMS folder:<br><br />
<br />
$ sudo docker-compose down <br><br />
<br />
== Updating the VMS <br> ==<br />
To update the VMS version:<br> <br />
1. Stop the VMS <br> <br />
2. Run the following command from the VMS folder:<br> <br />
$ sudo docker-compose pull <br> <br />
3. Run the VMS again:<br> <br />
$ sudo docker-compose up -d<br></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_23.png&diff=528File:Picture 23.png2022-05-17T15:50:02Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_22.png&diff=527File:Picture 22.png2022-05-17T15:49:39Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_21.png&diff=526File:Picture 21.png2022-05-17T15:49:19Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_20.png&diff=525File:Picture 20.png2022-05-17T15:49:01Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_19.png&diff=524File:Picture 19.png2022-05-17T15:48:39Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_18.png&diff=523File:Picture 18.png2022-05-17T15:48:15Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_17.png&diff=522File:Picture 17.png2022-05-17T15:47:56Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_16.png&diff=521File:Picture 16.png2022-05-17T15:47:35Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_15.png&diff=520File:Picture 15.png2022-05-17T15:47:16Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_14.png&diff=519File:Picture 14.png2022-05-17T15:46:56Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_13.png&diff=518File:Picture 13.png2022-05-17T15:46:29Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_12.png&diff=517File:Picture 12.png2022-05-17T15:45:48Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_11.png&diff=516File:Picture 11.png2022-05-17T15:45:30Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_10.png&diff=515File:Picture 10.png2022-05-17T15:45:08Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_9.png&diff=514File:Picture 9.png2022-05-17T15:44:45Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_8.png&diff=513File:Picture 8.png2022-05-17T15:44:29Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_7.png&diff=512File:Picture 7.png2022-05-17T15:44:08Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_6.png&diff=511File:Picture 6.png2022-05-17T15:43:50Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_5.png&diff=510File:Picture 5.png2022-05-17T15:43:30Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_4.png&diff=509File:Picture 4.png2022-05-17T15:43:14Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_3.png&diff=508File:Picture 3.png2022-05-17T15:42:56Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_2.png&diff=507File:Picture 2.png2022-05-17T15:42:22Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Picture_1.png&diff=506File:Picture 1.png2022-05-17T15:42:00Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=Cluebase_VMS_User_Manual&diff=505Cluebase VMS User Manual2022-05-17T15:41:21Z<p>Danifo: Created page with "<strong>Cluebase VMS by vCloud.ai User manual</strong> == Purpose of the VMS <br> == Cluebase VMS (video management system) is a software product that allows connecting video cameras to the server for further recording, live view and multiple additional functions. <br> Cluebase VMS is distributed as an open-platform commercial product under End User License Agreement. <br> == System description <br> == Cluebase VMS consists of the following parts: <br> 2.1. Front-end..."</p>
<hr />
<div><strong>Cluebase VMS by vCloud.ai User manual</strong><br />
<br />
== Purpose of the VMS <br> ==<br />
Cluebase VMS (video management system) is a software product that allows connecting video cameras to the server for further recording, live view and multiple additional functions. <br><br />
Cluebase VMS is distributed as an open-platform commercial product under End User License Agreement. <br><br />
<br />
== System description <br> ==<br />
Cluebase VMS consists of the following parts: <br><br />
2.1. Front-end (Web/Lunix/MacOs/Windows)<br><br />
2.2. Back-end: server-side application that runs in the background<br><br />
Cameras connect to Cluebase VMS via ONVIF and RTSP protocols. <br><br />
Users can connect to the cloud unlimited number of cameras individually and set individual recording plans on them.<br><br />
<br />
== Hardware requirements<br> ==<br />
Minimal server requirements: Dual-core ARM or Intel/AMD (32 or 64 bit), 2GB RAM, 2GB HDD/SSD.<br />
Desktop client requires a PC or Mac computer with Intel/AMD 32 or 64 bit, Apple Silicon or other ARM CPU with at least 2 cores of 1.5 GHz each. <br />
Supported browsers: Google Chrome v.92+, Mozilla Firefox v.90+, Safari v.14+<br><br />
<br />
== Compatibility<br> ==<br />
4.1. Codecs: Cluebase VMS is ready to work with any h.264 video stream though h.265 is supported with limited functionality.<br><br />
4.2. All IP cameras and DVR/NVR are compliant.<br><br />
<br />
== Client app installation<br> ==<br />
Please note that Web client application is available instantly by accessing the server’s IP address via a web-browser. However is you need to install a client application on you desktop they available for downloading at https://vcloud.ai/downloads<br><br />
<br />
a. Installing Linux app<br><br />
Once you’ve downloaded file Cluebase_VMS_Linux_x_x.deb you can install it from the UI by double-clicking and following the screen instructions or you can do it from the command line:<br><br />
sudo apt install Cluebase_ VMS_Linux_x_x.deb<br><br />
<br />
b. Installing Windows app<br><br />
Once you’ve downloaded file Cluebase_VMS_WIN_x_x.exe you can install it from the UI by double-clicking and following the screen instructions.<br><br />
<br />
c. Installing MacOS app<br><br />
Once you’ve downloaded file Cluebase_VMS_MacOS_x_x.dmg you can install it from the UI by double-clicking and following the screen instructions.<br><br />
<br />
== Signing in<br> ==<br />
After running the application for the first time you should see the Sign in screen. <br><br />
[[File:Picture 1.png|thumb|none]]<br><br />
<br />
Please enter your valid login and password and click Sign in. After installation you can use the default credentials: admin/admin.<br><br />
<br />
== License activation<br> ==<br />
Go to Settings->Services->VMS->vCloud.ai VMS->VMS License Request, fill the customer e-mail and name fields, specify the required licenses and click Send License Request. Your request will be delivered to vCloud.ai sales team so, in return, you should receive the License activation key file to your email. <br><br />
[[File:Picture 2.png|thumb|none]]<br><br />
<br />
Once received, you can Upload the license file at the screen bottom and click Activate.<br><br />
[[File:Picture 3.png|thumb|none]]<br><br />
Your license activation page should look as on the picture below:<br><br />
[[File:Picture 4.png|thumb|none]]<br><br />
<br />
== Adding cameras<br> ==<br />
8.1. Camera search tool<br><br />
Camera search tool is created to simplify and speed up cameras discovery and connection processes.<br><br />
<br />
Go to Settings->Cameras->Search<br><br />
<br />
[[File:Picture 5.png|thumb|none]]<br><br />
<br />
All supported cameras in the local network will be found automatically (normally within 5-10 seconds). <br><br />
<br />
After specifying cameras’ credentials (name/login/password) you can add them one by one using the ‘+’ button on the left<br><br />
[[File:Picture 6.png|thumb|none]]<br><br />
Or you can click Add all devices to add all cameras with the specified credentials.<br><br />
<br />
Click Refresh search to search the network again.<br><br />
<br />
You can specify the search range manually. <br><br />
[[File:Picture 7.png|thumb|none]]<br><br />
By default the system will search in the current subnet.<br><br />
<br />
8.2. Add cameras manually<br><br />
<br />
Go to Settings->Cameras->Add camera<br><br />
Name the camera, select connection type (ONVIF or RTSP) fill the IP address and port for ONVIF or the URL for the RTSP, fill Login and Password with camera’s credentials, select the time zone then click Add.<br><br />
<br />
[[File:Picture 8.png|thumb|none]]<br><br />
Your camera should then appear in All cameras/Devices section<br><br />
[[File:Picture 9.png|thumb|none]]<br><br />
<br />
== Storage settings<br> ==<br />
By default the VMS should identify all mounted drives from the system. <br><br />
[[File:Picture 10.png|thumb|none]]<br><br />
To enable a storage volume for recording please select the storage volume and switch it on:<br><br />
[[File:Picture 11.png|thumb|none]]<br />
Then select the cameras that are required to be recorded, set archive depth, select quality and click Save. The storage will be activated for recording immediately.<br />
<br />
== User access management<br> ==<br />
10.1. Managing roles<br><br />
Go to Settings->Users->Add role<br><br />
[[File:Picture 12.png|thumb|none]]<br><br />
Name the role and grant access to specific cameras and functions. Click save.<br><br />
Please note that all users with this role will then have access to the specified cameras and functions.<br><br />
10.2. Managing users<br><br />
Go to Settings->Users->Add new user<br><br />
[[File:Picture 13.png|thumb|none]]<br><br />
<br />
Specify the new user credentials: Username, Password and the required Role. Access granted to the selected Role is be indicated below but is not available for editing. To edit the permissions you need to edit the Role by clicking the pencil button <br><br />
[[File:Picture 14.png|thumb|none]]<br><br />
<br />
== Map setup<br> ==<br />
To be able to locate the camera on the map you can add the coordinates or simply drag the camera across the map and then click Save.<br />
[[File:Picture 15.png|thumb|none]]<br />
<br />
== Layout setup<br> ==<br />
Click '''New layout''' in the main menu<br />
[[File:Picture 16.png|thumb|none]]<br />
The '''Layout''' editing page will open<br />
[[File:Picture 17.png|thumb|none]]<br />
Give your new layout a '''Name''', choose '''Layout template''' and drag’n’drop cameras or whole groups to the layout grid on the right-hand side.<br />
[[File:Picture 18.png|thumb|none]]<br />
Click Save to save your layout.<br />
<br />
To edit existing layouts, click the Pencil button in the layout tab menu at the top of the screen:<br />
[[File:Picture 19.png|thumb|none]]<br />
<br />
== Camera groups<br> ==<br />
Go to Settings->Cameras->Add group and fill the group name field. Then click “Add”<br />
[[File:Picture 20.png|thumb|none]]<br />
To edit a group click the ‘pencil’ icon on the right side of the group.<br />
[[File:Picture 21.png|thumb|none]]<br />
Now you can edit or delete the group.<br />
[[File:Picture 22.png|thumb|none]]<br />
To add a camera to a particular group go to camera settings and select the required group.<br />
[[File:Picture 23.png|thumb|none]]<br />
<br />
== Technical support<br> ==<br />
vCloud.ai technical support is operating 24/7, the average reply time is 3 hours.<br />
Technical support can be requested via email: [mailto:support@vcloud.ai support@vcloud.ai]</div>Danifohttps://docs.vcloud.ai/index.php?title=EN&diff=504EN2022-05-17T15:16:04Z<p>Danifo: Created page with "* Cluebase VMS User Manual * Cluebase VMS Installation Manual * Cluebase VMS Technical Specifications"</p>
<hr />
<div>* [[Cluebase VMS User Manual]]<br />
* [[Cluebase VMS Installation Manual]]<br />
* [[Cluebase VMS Technical Specifications]]</div>Danifohttps://docs.vcloud.ai/index.php?title=Cluebase_VMS_Manuals&diff=503Cluebase VMS Manuals2022-05-17T15:15:51Z<p>Danifo: Created page with "* EN"</p>
<hr />
<div>* [[EN]]</div>Danifohttps://docs.vcloud.ai/index.php?title=File:Pose2.jpg&diff=502File:Pose2.jpg2022-05-17T15:14:42Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:P41.png&diff=501File:P41.png2022-05-17T15:13:32Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:Pose1.png&diff=500File:Pose1.png2022-05-17T15:13:08Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:P42.png&diff=499File:P42.png2022-05-17T15:12:44Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:P40.png&diff=498File:P40.png2022-05-17T15:12:26Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:P39.png&diff=497File:P39.png2022-05-17T15:12:05Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:P38.png&diff=496File:P38.png2022-05-17T15:11:43Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:P37.png&diff=495File:P37.png2022-05-17T15:11:24Z<p>Danifo: </p>
<hr />
<div></div>Danifohttps://docs.vcloud.ai/index.php?title=File:P36.png&diff=494File:P36.png2022-05-17T15:11:06Z<p>Danifo: </p>
<hr />
<div></div>Danifo