Topics

1

Python and Java API / Regarding Decimating 3D Models in Agisoft Metashape

« on: March 08, 2024, 10:34:32 AM »

Hello everyone,

I hope you're all doing well. I'm currently working on a project using Agisoft Metashape and have run into an issue with the size of the 3D models generated. To reduce the file size, I'm exploring the use of the decimateModel option in Agisoft Metashape's Python API version 1.8.5.

I've used the high option for building depth and a dense model to achieve the desired accuracy in the DTM image. However, the resulting 3D model (in ModelFormatOBJ) is too large. I believe that utilizing the decimateModel function could help reduce its size, but I'm unsure about the correct way to implement this.

I would greatly appreciate any guidance or advice on how to effectively use the decimateModel function to reduce the size of 3D models generated in Agisoft Metashape.

Thank you all in advance for your help.

Best regards,
Dhanraj

2

Python and Java API / Processing Parrot Sequoia Camera Multispectral Data: Ortho Band Info issue

« on: December 11, 2023, 05:05:17 PM »

I'm working with multispectral data from the Parrot Sequoia camera, encompassing five bands: RGB, GREEN, RED, NIR, and REDEDGE. Employing the Agisoft Metashape 1.8.5 Python API workflow code from GitHub for data processing, I encountered a challenge when generating an orthomosaic image.

Upon inspecting the band information within the orthomosaic, I observed six bands listed as ('gray', 'undefined', 'undefined', 'undefined', 'undefined', 'alpha'). I aim to accurately identify the specific band names instead of encountering 'undefined' values.

Could you advise on how to retrieve the band names instead of encountering 'undefined' in the orthomosaic image generated through the Agisoft Metashape 1.8.5 Python API workflow code?"

3

Python and Java API / Improving Orthomosaic Quality for Road Survey

« on: September 21, 2023, 02:03:39 PM »

I'm currently processing images from a road survey to generate orthomosaic and elevation TIF images, and the process is completed successfully without any errors. However, since these images are all along a single line, reflecting the nature of a road survey, I've noticed that in some parts of the orthomosaic, there are disturbances.

I'm using Agisoft Metashape Python 1.8.5 for this task, and I'm wondering if there is a special method or technique within this software that can help me address this issue and improve the quality of the orthomosaic along the road survey path. Any insights or suggestions would be greatly appreciated.

4

Python and Java API / Generating DTM Images Alongside Orthomosaic, DEM, and 3D Models

« on: September 20, 2023, 02:38:40 PM »

Hello, Agisoft Metashape community,

I am currently using Agisoft Metashape Python API version 1.8.5 to generate orthomosaic, DEM, dense cloud, and 3D models. I've been following the code example provided at https://github.com/agisoft-llc/metashape-scripts/blob/1.8/src/samples/general_workflow.py to accomplish this.

Now, I am looking to expand my workflow and also generate Digital Terrain Model (DTM) images from the same dataset. However, I couldn't find specific information or examples in the documentation or the sample script linked above on how to achieve this.

Could someone please suggest an appropriate solution or guide on how to integrate DTM generation into my existing workflow using Agisoft Metashape Python API version 1.8.5? Any code examples or step-by-step instructions would be greatly appreciated.

Thank you in advance for your assistance!

5

Python and Java API / Color contrast of the elevation data

« on: August 14, 2023, 09:30:02 AM »

I've successfully generated Orthomosaic TIF, DSM TIF, 3D model, and point cloud using the Python API in Agisoft Metashape 1.8.5. However, I've noticed that the DSM TIF image has an excessively high color contrast, and I'd like to adjust this. Are there any options or methods within Agisoft Metashape 1.8.5 Python API that allow me to modify the color contrast of the DSM TIF image during or after generation?

This is my code for the reference

Code: [Select]

chunk.buildDem(source_data=Metashape.DenseCloudData, interpolation=Metashape.Interpolation.EnabledInterpolation)
chunk.exportRaster('/dem.tif', source_data = Metashape.ElevationData)

6

Python and Java API / Continuation of Processing with Agisoft Python API 1.8.5

« on: July 05, 2023, 09:45:48 AM »

I hope this message finds you well. I am writing to seek assistance regarding the Agisoft Python API 1.8.5 and its processing capabilities when handling large datasets.

Currently, I am utilizing the Agisoft Python API 1.8.5 to process a set of 50 images in chunks. This process generates the required output, including a point cloud, orthoimage, digital elevation model (DEM), and a 3D model. However, I now have an additional set of 25 images that I would like to include in the processing pipeline.

My question is whether it is possible to seamlessly continue the processing by adding the new set of 25 images to the existing dataset, or if the entire dataset needs to be reprocessed from scratch. I am seeking a solution that can help me save both time and resources.

I would greatly appreciate it if you could provide guidance on how to efficiently continue the processing with the Agisoft Python API 1.8.5 without the need for complete reprocessing. Any insights or recommendations regarding this matter would be highly valuable.

Thank you very much for your attention to this inquiry. I look forward to hearing from you soon.