Messages

1

General / Filter Dense Cloud Option (Actually Resample)

« on: December 12, 2021, 02:04:42 PM »

Hi

There is an option in Agisoft MetaShape Ver 1.7.3 named "Filter Dense Cloud...".
Although its name isn't quite match with what it does and "Resampling dense cloud" could be better for that, my point is another thing.

As you may tested, it resamples dense cloud on arbitrary space between points (from maximum to low resolution). When I export filtered dense cloud in ASCII or other formats, All coordinates rounded in 0.1 precision.

Is it right or I forget to set any parameters in setting?

2

General / Re: Problem with undulation of the geoid

« on: July 25, 2020, 10:23:38 PM »

Hi
If we measure altitudes based on ellipsoid and want to convert them according to Geoid, Is it possible to define custom coordinate system based on usual geoid models like EGM96 in Metashape?

3

General / Re: Best collection method for 3D building

« on: May 08, 2020, 09:25:10 PM »

All your mentioned techniques like oblique images, cross flying, different flight heights with different angles are good enough to make a perfect 3D model but Aside from all benefits of Metashape, I think making 3D model of building can be done better with other image processing softwares like ContextCapture or Reality Capture.

4

General / Re: What is an exactly a Checkpoint ?

« on: May 08, 2020, 09:14:29 PM »

Hi

If I want to explain it in a simple way, Check points don't take part in calculating parameters. Therefore you can estimate final coordinates of that point with computed parameters and make a judgment about error.

5

General / Re: P4 RTK with GCP

« on: October 28, 2019, 09:53:09 PM »

All you have to do is checking images with high quality coordinates and unchecking others with poor coordinates.

At final step you can import some GCPs for optimizing and exterior orientation.

regards,

6

General / Re: Project with 220K images for processing

« on: October 06, 2019, 12:46:17 PM »

Thank you very much SAV, I reached out your suggestion after searching and completely agree with you. I decided to use more than one Graphic card and select a CPU with higher clock and usual number of cores instead of Xeon series.

regards,

7

General / Re: Project with 220K images for processing

« on: September 23, 2019, 10:11:33 PM »

220k？ 22w? In China, this is a normal project.

And the way we do it is very simple,break up the whole into parts，If the geometric strength and precision of each control point are sufficient, the quality of the whole project is very good.

If possible, you can entrust us 

We are gonna do it in Iran and aside from whatever processing unit, I have to break project into smaller parts.

8

General / Re: Project with 220K images for processing

« on: September 17, 2019, 09:31:00 AM »

Hi jivago,

That's a huge area.
I highly recommend to increase your AGL to be able to cover a larger area with a single battery. Depending on your local drone legislation, you can apply for an exemption for the AGL limit. For example, increasing AGL to 300m would still give you a GSD of 8.2cm. I have recently done a larger scale survey over an area of 18km2 at AGL 300 with 80% forward and 75% sideward image overlap. I was able to safely cover 0.75 - 0.80 km2 per battery. I wish the Phantom 4 Pro/RTK would ascend and descend a little quicker. It takes quite a long time to get up to and down from AGL 300m. However, AGL 300 comes with the advantage that it allows you to fly much faster (I was doing 13m/s) without getting into motion blur issues in your imagery. Blurry pictures need to be avoided because the lead to higher error/lower accuracy.

And as suggested by Alexey, you'll probably need to split your project into a few smaller chunks for processing.

Regarding hardware, this might be some useful information for you:
https://www.pugetsystems.com/recommended/Recommended-Systems-for-Agisoft-Metashape-145/Hardware-Recommendations


All the best. And it would be great if you could share how you finally did this massive survey.

Regards,
SAV

Hi SAV

thank your for your advises, but I have to say my map scale is 1:500 and need image resolution below 5 cm based on local instruction.

There for I have to fly at maximum height about 120 meter and for avoiding image motion blur issue restrict drone speed at 9 or 10 m/s.

And for hardware configuration I think below specification is enough for my project and splitting project into smaller parts is inevitable.

Cpu : 2x Xeon E5 2688 V4
40 Core 80 Thread 100 MB Cache

MB : Asus Z10PE-D16

Ram : 64GB ECC DDR4 2400

SSD : SAMSUNG 970 EVO M.2 2280 1TB
Hard : WD 4TB Red

VGA : AORUS GeForce GTX 1080 Ti Waterforce Xtreme Edition 11G Rev 1.0/1.1

Case : Mastertech T500
Power : Green 1050 OCPT
2xWaterCooler Green 120 Evo

regards,

9

General / Re: Project with 220K images for processing

« on: September 11, 2019, 06:59:04 AM »

My map scale is 1:500 therefore I think very rare fixed wing can fly for that purpose.

I convinced myself to fly about one month and have no problem with that but I don't know which pc with what configuration can processing more than 20,000 images in each chunk!

My record till now is 20,000 images. Does anybody have suggestions? What's is your opinion about HP Z840 workstation?

10

General / Re: Project with 220K images for processing

« on: September 10, 2019, 06:04:24 AM »

I'm agree with you but I don't have a fixed wing. If I shall handle battety management, is there any advice for doing processing in ideal situation?

11

General / Project with 220K images for processing

« on: September 09, 2019, 08:40:27 PM »

Hi
I have a huge project about 170 Sq. Km and wanna fly with Phantom 4 RTK.

Base on my calculation I will have about 220K images from 100 m height above ground with overlapping 75% in both in both directions.

Does anybody know anything about best practice for processing such a numerous amount of images?

sincerely,

12

General / Re: Classify Ground Points - not enought memory

« on: July 22, 2019, 12:31:11 PM »

Is it possible to classify dense cloud part by part?

I mean instead of running classification on whole points, split it to smaller point group and work on it.