Messages

1

General / size of non coded targets

« on: February 04, 2016, 03:11:29 PM »

Dear All,
I am about to test usage of non-coded targets in an aerial mission and their automatic detection by Photoscan. In the tutorial about coded targets there is a suggestion on the size of the coded targets. But I cannot find any indications about the rage of sizes for the non-coded targets (not in the manual, neither in tutorials). Could someone shed some light on that? Any experiences?

kind regards,
Ola

2

General / point pixel coordinates in undistorted images

« on: November 03, 2015, 01:02:32 PM »

Dear All,

Based on the camera model estimated in Photoscan and coordinates of an object in a distorted image (col,row), I try to compute coordinates of the object in the undistorted image (col_und, row_und) provided by Photoscan.
I export the images without centering the principal point (but I also tried with this option enabled).
I follow the formulas provided in the user manual but cannot get the values right. There is only the radial distortion that is present in the images (all tangential distortion = 0, as well as the skew value).

I noticed that the undistorted image should be larger than the original, but the exported undistorted image is of the same size as the input image. I suspect this "crop" causes a shift in my computations but I am not able figure out what the sift is.

Could some shed some light on this subject? How to find coordinates of an object in the undistorted image exported in PS based on the camera model and coordinates of an object in a distorted image.

best regards,
Ola

3

General / Re: Only align photos

« on: March 23, 2015, 01:11:30 PM »

I only wanted Agisfot to align the snaps and make an orto from them with no 3D model.

Hi juansre,
An ortho is by definition created using a 3D model. If you do not need geometrically correct result you should look for software to perform image stitching (e.g.  image composite editor - free software).

Best,
Ola

4

General / Re: 'Reference' based image alignment - images divided in 2 groups

« on: February 17, 2015, 01:33:35 PM »

Hi Alexey,

Indeed, I interpolated image positions in between the points and the image alignment (Reference based) was successful.

Thank you for your prompt support!

Best,
Ola

5

General / 'Reference' based image alignment - images divided in 2 groups

« on: February 16, 2015, 05:24:41 PM »

Hi,

I work with a set of geo-tagged images acquired in one strip with >90% forward overlap and try to align them using the 'Reference' pair selection method. The images are nadir looking but I set the average terrain height anyway. I am aware of the fact that single image strips are far from being optimal for photogrammetric image processing, but I try to understand why the image set is always aligned in two groups (see attachment). Images within each group are aligned correctly, but in between the two groups alignment is incorrect. Initial image geo-location (GPS positions) looks logical and correct (with reasonably equal spacing between successive images in the strip), but Photoscan doesn't even look for matches between the last image in group 1 and the first image of group 2. Any suggestions on which parameter could I tune to avoid this behavior? Processing data using Generic or Disabled pair selection mode is much more time consuming....

best,
Ola

6

Python and Java API / Fisheye sensor - setting type

« on: January 29, 2015, 05:01:18 PM »

Hi All,

I need to write a simple script to automate data processing: image alignment, dense points cloud creation, meshing, etc. The one shown in page 5 of the Python API Reference works well for a frame camera, what about a fisheye sensor?
Anyone knows how to set the sensor to Fisheye?

best regards,

Ola

7

General / Hardware requirements - GPU

« on: January 16, 2014, 01:02:36 PM »

Hi,

We have a machine with 24 Gb RAM, 2 x 2.67GHz CPU and a mother board meeting Photoscan requirements but the graphic hard seems to be a weak point:

•   Graphics Processor
o   ATI ES1000
•   Video Memory
o   32 MB
•   Video Interfaces
o   VGA

(see http://www.techpowerup.com/gpudb/2102/es1000.html for more details.)

Could you please provide indications about what is the influence of the weak GPU on the performance of Photoscan in image alignment and dense point matching?

Would changing the graphic card to this one
http://www.asus.com/Graphics_Cards/GT6401GD3L/#specifications
improve the performance dramatically?

best regards,

osima

8

General / Re: Camera based chunks alingment

« on: January 13, 2014, 11:42:17 AM »

Hi Alexey,

Sorry for my late reply.
Please find the following screenshots attached:
Chunk1: chunk1.jpg
Chunk 2: chunk2.jpg
both chunks aligned and merged: chunks.jpg

This is the best that I could get so far (after removing 2-3 images common to both chunks). It seems like the positions of images common to both chunks are aligned but not their orientations.
Any ideas how could this be improved?

Best regards,
Aleksandra

9

General / Re: Camera based chunks alingment

« on: January 04, 2014, 04:02:43 PM »

Hi JMR,

Yes, one of the chunks is bold (reference). None of the chunks is scaled at this point but I tried both options: with and without fixed scale, with no success.

Best,

Ola

10

General / Re: Importing IMU

« on: January 04, 2014, 03:59:21 PM »

Hi Geobit,

Thank you for your extensive info about how IMU works. I appreciate the time you spent on replying but this is not an answer to my question.

By using the position and orientation of images  the number of image combinations used in matching could be significantly reduced and this is a long awaited feature in PS, at least from my point of view.
I thought that if the IMU data can be now imported to PS (it seems to be a new feature), maybe they are also used in the processing workflow. Are they?

Best,

Ola

11

General / Re: Importing IMU

« on: January 03, 2014, 04:57:16 PM »

Hi Alexey,

How are the IMU data used in Photoscan? I cannot find any info about using IMU data in the documentation.

best regards,

Ola

12

General / Camera based chunks alingment

« on: January 03, 2014, 03:38:49 PM »

Hi,

I have problems with understanding how the camera based chunks alignment works.

I have a project including several chunks. All the chunks include images from one camera (precalibrated, fixed), acquired from different positions. There are four images common to all the chunks (e.g.: A.jpg, B.jpg, C.jpg, D.jpg are present in every chunk).
When I select Workflow/Align chunks/Camera based alignment (fix scale unchecked), the chunks are not aligned as I would imagine they should be. In another words, after alignment the position of A.jpg, B.jpg, C.jpg, D.jpg from Chunk 1 is not the same as position of A.jpg B.jpg, C.jpg, D.jpg from Chunk 2 (they seem to be shifted).

Could someone shed some light on the camera based chunks alignment? I would like to understand what I do wrong.

Best regards,
Ola
 

13

Python and Java API / Re: AlignChunks runtime error

« on: December 11, 2013, 03:13:18 PM »

Hi Alexey,

Thanks a lot! I noticed this change in the change log. Good stuff

Best,
Ola

14

Python and Java API / Re: AlignChunks runtime error

« on: December 11, 2013, 03:04:14 PM »

Hi Alexey,

Thank you for your prompt response. I will try version 1.0.

Best,
Ola

15

Python and Java API / AlignChunks runtime error

« on: December 11, 2013, 02:11:27 PM »

Hi,
I am a beginner in Python, but managed pretty well so far.

At least until I got this cryptic message thrown by the console:

Traceback (most recent call last):
  File "//tsclient/D/Tools/ownScripts/Python_PhotoScan/first_test_multiple_chunks_oneCalibration.py", line 50, in <module>
    PhotoScan.alignChunks(doc.chunks,doc.chunks[1], method="points", accuracy="high", preselection=False, filter_mask=False, point_limit=40000)
RuntimeError: More keyword list entries (7) than format specifiers (5)

This is the code that I use:

Code: [Select]

#PhotoScan 0.9.1 build 1703 (64bit)
import PhotoScan
import os, os.path
import string

doc = PhotoScan.Document()

path="X:/FirstData/Chunks/"  #path to the image folder
cameraCalibPath = "CamCalibration.xml" #path to the camera calibration file
cameraCalibration = PhotoScan.Calibration()
cameraCalibration.load(path + cameraCalibPath)
print (cameraCalibration.width)

#For every folder with image subsets
for root, dirs, files in os.walk(path):


    for name in dirs:
        photos_list = os.listdir(os.path.join(root, name))
        chunk = PhotoScan.Chunk()
        chunk.label = name
        doc.chunks.add(chunk) #add a new chunk
        sensor = PhotoScan.Sensor()
        sensor.width = cameraCalibration.width
        sensor.height = cameraCalibration.height
        sensor.user_calib = cameraCalibration
        sensor.fixed = True
       
        for photo_name in photos_list:     #add all images from the folder
            camera = PhotoScan.Camera()
            camera.open(os.path.join(root, name) + "/" + photo_name)
            if (photo_name.rsplit(".",1)[1] =="jpg") :
               camera.label = camera.path.rsplit("/",1)[1]
               camera.sensor = sensor 
               chunk.sensors.add(sensor)
               chunk.photos.add(camera)

doc.save("X:/FirstData/Chunks/proj1.psz")

#Align Photos in every chunk
for chunk in doc.chunks:
    chunk.matchPhotos(accuracy = "high", preselection="disabled", filter_mask=False, point_limit=40000)
    chunk.alignPhotos()   
    #Build Geometry
    chunk.buildDepth(quality="high", filter="aggressive", gpu_mask=0, cpu_cores_inactive=1)
    chunk.buildModel(object="height field", geometry="smooth", faces=0, filter_threshold=0, hole_threshold=10)   
    doc.save("X:/FirstData/Chunks/proj1.psz")

#Align chunks
PhotoScan.alignChunks(doc.chunks,doc.chunks[1], method="points", accuracy="high", preselection=False, filter_mask=False, point_limit=40000)
PhotoScan.mergeChunks(doc.chunks, merge_models=False, merge_markers=False)



Could anyone shed some light on what I do wrong?

Best regards,

Ola