Messages

1

Feature Requests / Re: CHECK/UNCHECK API

« on: March 16, 2024, 09:02:05 PM »

Solved!!

Code: [Select]

for camera in chunk.cameras:
    camera.reference.enabled = False
for camera in chunk.cameras:
    if camera.reference.location_accuracy and max(camera.reference.location_accuracy) < 5:
        camera.reference.enabled = True


2

Feature Requests / CHECK/UNCHECK API (SOLVED)

« on: March 16, 2024, 03:04:27 PM »

Hi,

I'm reaching out to suggest a potential addition to the Metashape API that I believe could benefit many users. While the current API offers great flexibility, including enabling/disabling cameras (enabled) and selecting/deselecting them (selected), it seems there's no direct way to programmatically "uncheck" images for processing based on specific criteria (e.g., location accuracy).

Many of us automate workflows where pre-selecting images based on metadata or quality metrics is crucial before proceeding to resource-intensive processing steps. For instance, being able to automatically uncheck images with location accuracy below a certain threshold could save significant time and enhance the quality of project outputs.

Could we consider adding a method to the API to control the "check" state of images in the Reference Panel or before processing? This feature would provide even greater control over automated workflows and potentially improve processing efficiency and outcomes.

Code: [Select]

import Metashape
doc = Metashape.app.document
chunk = doc.chunks[0]
for camera in chunk.cameras:
    # Checks if the camera has a defined reference and location accuracy
    if camera.reference and camera.reference.location_accuracy:
        accuracy = max(camera.reference.location_accuracy.x, camera.reference.location_accuracy.y,camera.reference.location_accuracy.z)
        print(f"Camera {camera.label}: Accuracy = {accuracy}") # Prints the accuracy
        if accuracy > 9:
            camera.selected = False
            print(f"Camera {camera.label} unselected due to high accuracy.") # Print the action

Best,

3

General / Re: scan the same object in parts and merge it

« on: January 28, 2024, 08:15:03 AM »

Hi,

Try this

https://agisoft.freshdesk.com/support/solutions/articles/31000168474-terrestrial-laser-scans-processing-in-metashape-2-1

4

General / Re: Linear scan using video frames and RTK images instead of GCP's

« on: January 28, 2024, 03:38:01 AM »

Hi,

Video usually has greater density with the extraction of frames, but it has a smaller format than a single photograph, you have to take this into consideration.

If you respect these parameters here,
https://agisoft.freshdesk.com/support/solutions/articles/31000149338-aerial-survey-tips,

Then you need to perform the alignment as here,
https://agisoft.freshdesk.com/support/solutions/articles/31000153696-aerial-data-processing-with-gcps-orthomosaic-dem-generation

If necessary, try to create random arbitrary manual control points to help the program identify the location correctly, selecting the images and alignment manually.

5

General / Re: Imported (known) ground control point elevation changes when editing position

« on: January 28, 2024, 03:19:27 AM »

Hi rivermapper,

Try this

https://agisoft.freshdesk.com/support/solutions/articles/31000153696-aerial-data-processing-with-gcps-orthomosaic-dem-generation

and

https://agisoft.freshdesk.com/support/solutions/articles/31000154132-control-and-check-points-for-aerial-surveys

and

Add Photos
Use "Add Photos..." from the Workflow menu to load the images.

Align Photos and Import GCPs:
Select "Align Photos..." from the Workflow menu to estimate camera positions and orientations.
Click on "Import" in the Reference tab to load the GCPs.

Unmark Images without Accurate Coordinates:
Go to the Photos tab.
Utilize "View Matches..." to visualize correspondences.
Unmark the images that lack accurate navigation coordinates.

Edit GCP Markers:
Enter the marker editing mode.
Adjust the position of GCP markers in the images as necessary.

Optimize Parameters:
Execute the optimization of alignment parameters.

Build Point Cloud and DEM:
Choose "Build Point Cloud..." to initiate the point cloud construction. Proceed with the process.

Generate Orthomosaic:
After building the point cloud, proceed to generate the orthomosaic.

6

Bug Reports / Re: Can't Select Tile Size - Dual GPU V2.1.0.17526

« on: January 26, 2024, 09:23:21 PM »

Hello Alexey,

Yes, the error is presented when both are active and CUDA is enabled, regardless of the filter.

Yes, it presents errors in the depth maps when CUDA is active in the same configuration.

In time, I did a test with the alignment and activated max_workgroup_size=20 with CUDA, which caused processing to take longer and some errors, but no overflow occurred.

Another test was to align everything at downscale=(2) and the error did not occur either. But the depth map was successful limiting BuildDepthMaps/max_neighbors=10 and BuildPointCloud/max_neighbors=12, in both aspects I managed to reach 15, at most, and the error appeared again.

main/gpu_enable_cuda=false everything everything ran without errors but with high processing time and some isolated cases of errors in the depth map.

7

Bug Reports / Re: Infinite values in transform V.2.1.0.17526

« on: January 26, 2024, 09:05:24 PM »

Hello Alexey,

As I said initially, I checked the coordinate values and they are correct. So much so that I can align the images by manually selecting groups.

The alignment error, in v.2.0 onwards, has for some time been generating wrong alignments, generating bizarre and stratospheric values with tens of thousands of kilometers of error from the correct position.

The solution was to generate the alignment, of more than 5k images, then reset the glaring errors, 200 images, and align manually. But in v.2.1 it doesn't even do the initial alignment, having to do the work of aligning manually and then optimizing to get the correct values.

The highest frequency occurs with oblique images.

8

Bug Reports / Infinite values in transform V.2.1.0.17526

« on: January 25, 2024, 07:06:29 PM »

Code: [Select]

2024-01-25 12:57:59 1 blocks: 4593
2024-01-25 12:58:05 block: 3 sensors, 4593 cameras, 4506674 points, 14742630 projections
2024-01-25 12:58:05 block_sensors: 0.00254059 MB (0.00254059 MB allocated)
2024-01-25 12:58:05 block_cameras: 1.78713 MB (1.78713 MB allocated)
2024-01-25 12:58:05 block_points: 206.299 MB (219.429 MB allocated)
2024-01-25 12:58:05 block_tracks: 17.1916 MB (17.1916 MB allocated)
2024-01-25 12:58:05 block_obs: 674.864 MB (674.864 MB allocated)
2024-01-25 12:58:05 block_ofs: 34.3832 MB (34.3832 MB allocated)
2024-01-25 12:58:05 block_fre: 0 MB (0 MB allocated)
2024-01-25 12:58:05 final block size: 4593
2024-01-25 12:58:06 adding 3996297 points, 0 far, 789281 inaccurate, 10436 invisible, 916 weak
2024-01-25 12:58:06 (3 px, 2 3d) sigma filtering...
2024-01-25 12:58:08 adjusting: - nan -> nan
2024-01-25 12:58:19 point variance: 1.69192 px, threshold: 5.07577 px
2024-01-25 12:58:21 adding 767565 points, 133804 far (5.07577 px threshold), 758903 inaccurate, 8020 invisible, 1168 weak
2024-01-25 12:58:22 adjusting: - nan -> nan
2024-01-25 12:58:32 point variance: 1.05102 px, threshold: 3.15307 px
2024-01-25 12:58:33 adding 736792 points, 123068 far (3.15307 px threshold), 729916 inaccurate, 6026 invisible, 1065 weak
2024-01-25 12:58:35 adjusting: - nan -> nan
2024-01-25 12:58:44 point variance: 0.788759 px, threshold: 2.36628 px
2024-01-25 12:58:45 adding 715358 points, 96357 far (2.36628 px threshold), 709650 inaccurate, 4868 invisible, 1301 weak
2024-01-25 12:58:46 adjusting: - nan -> nan
2024-01-25 12:58:54 point variance: 0.677631 px, threshold: 2.03289 px
2024-01-25 12:58:56 adding 702639 points, 65034 far (2.03289 px threshold), 697230 inaccurate, 4266 invisible, 1423 weak
2024-01-25 12:58:57 adjusting: - nan -> nan
2024-01-25 12:59:05 point variance: 0.623643 px, threshold: 1.87093 px
2024-01-25 12:59:06 adding 695379 points, 40811 far (1.87093 px threshold), 690054 inaccurate, 3981 invisible, 1525 weak
2024-01-25 12:59:06 optimized in 59.735 seconds
2024-01-25 12:59:13 Error: Infinite values in transform are not allowed
2024-01-25 12:59:13 processing failed in 75.271 sec
Hi Alexey,

I've never seen this before. I checked the coordinates, none were out of range. What I only noticed is that after version 2.0 some images are aligning with astronomical displacements, something that didn't happen before in previous versions.

9

Bug Reports / Re: Can't Select Tile Size - Dual GPU V2.1.0.17526

« on: January 24, 2024, 09:23:22 PM »

Hello Alexey,


Nvidia published new driver 551.23, try with CUDA on and the issues continues.

10

General / Re: Inconsistent elevation error between point cloud and GCPs

« on: January 21, 2024, 03:54:48 AM »

Hello rivermapper,

Try this,

https://agisoft.freshdesk.com/support/solutions/articles/31000153696-aerial-data-processing-with-gcps-orthomosaic-dem-generation

And,

Review Z-Value Correction:
Reevaluate the need for the approximate z-value correction during image alignment. It might be causing the inconsistency, and alternative methods could be explored.

Tie Point Filtering:
Adjust the tie point filtering process. The current removal percentage might be affecting the accuracy of the DEM. Experiment with different percentages to find the optimal balance between point density and accuracy.

GCP Integration:
Confirm that GCPs are being effectively integrated into the processing. Check if there are any issues during the optimization and realignment steps that may be causing discrepancies.

DEM Post-Processing:
After generating the DEM, consider post-processing steps to correct artifacts. Some software tools offer options for filtering out anomalies and refining the output.

11

Feature Requests / Re: Add Tools/Tie Points/Build Tie Points to batch dialog

« on: January 20, 2024, 05:09:43 AM »

+1

12

Feature Requests / Re: Add "Build Tie Points" to batch processing

« on: January 20, 2024, 05:09:09 AM »

+1 perfect placement. And don't forget your other post on the topic https://www.agisoft.com/forum/index.php?topic=15700

13

Bug Reports / Re: Can't Select Tile Size - Dual GPU V2.1.0.17526

« on: January 18, 2024, 08:46:17 PM »

Hi Alexey,

With Cuda setup off, all GPU works fine, without issues.

The reprojection error 0.67 and projection accuracy 121.

14

Bug Reports / Re: Can't Select Tile Size - Dual GPU V2.1.0.17526

« on: January 18, 2024, 08:42:55 AM »

Hello Alexey,

The new nvidia drive is available, try it on local and network with dual GPU, and the process stops with zero memory GPU.

 But if the local process and the dual GPU are turned on, the same thing happens, to solve it you need to turn off one GPU.

Another solution, alignment with medium accuracy, now the error occurs, takes more time, but can finish online, still a better option anyway, as it is faster than local.

Another point, when the error occurs on a GPU without memory, the gradual selection for projection accuracy is between 224-260 and reprojection over 1.15. The same dataset without errors with single GPU the value is now between 110-127 and error reprojection 0.6-0.8

15

Bug Reports / Re: Can't Select Tile Size - Dual GPU V2.1.0.17526

« on: January 16, 2024, 01:36:41 AM »

Hi Alexey,

Dual GPU RTX2080, Drive NVidia 546.33, Windows 10 Pro 22H2 19045.3930

Code: [Select]

2024-01-15 19:29:30 processing finished in 1.588 sec
2024-01-15 19:29:33 MatchPhotos.detect (1/100): downscale = 1, subtask = detect, generic_preselection = on, reference_preselection = on, filter_mask = on, mask_tiepoints = off, filter_stationary_points = off, keypoint_limit = 40000, keypoint_limit_per_mpx = 5000, tiepoint_limit = 4000, guided_matching = off, reset_matches = on, data_folder = F:/3762_01.files/1/0/point_cloud.1
2024-01-15 19:29:34 loaded keypoint partition in 0 sec
2024-01-15 19:29:34 loaded matching data in 0 sec
2024-01-15 19:29:34 Detecting points...
2024-01-15 19:29:34 Found 2 GPUs in 0.076 sec (CUDA: 0.043 sec, OpenCL: 0.033 sec)
2024-01-15 19:29:35 Using device: NVIDIA GeForce RTX 2080 SUPER, 48 compute units, free memory: 7110/8191 MB, compute capability 7.5
2024-01-15 19:29:35   driver/runtime CUDA: 12030/10010
2024-01-15 19:29:35   max work group size 1024
2024-01-15 19:29:35   max work item sizes [1024, 1024, 64]
2024-01-15 19:29:35 Using device: NVIDIA GeForce RTX 2080 SUPER, 48 compute units, free memory: 7110/8191 MB, compute capability 7.5
2024-01-15 19:29:35   driver/runtime CUDA: 12030/10010
2024-01-15 19:29:35   max work group size 1024
2024-01-15 19:29:35   max work item sizes [1024, 1024, 64]