I have a very large dataset from a senseFly eBee drone. With all the photos combined, there are around 5000. I have split it into sub projects with a maximum of 500 photos per project. This put it into 9 sub projects and I am still getting the images clustering in some of the sub projects. Has anyone else experienced this? If so, how was this issue resolved?
PC Specs:
Intel Core i7 6950X 10 Core - Overclocked to 3.6 Ghz
64GB of RAM
500GB Samsung Pro SSD
EVGA GEFORCE GTX 1070 8GB GDDR
Hello Stephen,
Multiple blocks indicate that there were not enough matches between the different blocks to provide a global optimization. The different blocks might not be perfectly georeferenced with respect to each other.
Adding Manual Tie Points between the blocks and reoptimizing can connect the blocks together. By marking a point in several images, we indicate that certain point should be reprojected as closer as possible in the 3D model, considering all the images reprojections. For more information: https://support.pix4d.com/hc/en-us/articles/202560349
Additionally, enabling the option Rematch may improve the connection between the blocks. For more information about the Rematch option: https://support.pix4d.com/hc/en-us/articles/205327965#label5
Before merging the sub-projects, could you confirm you added MTPs or GCPs to make the connection between the different subsets of images?
For more information about processing large datasets: https://support.pix4d.com/hc/en-us/articles/202558579
Best regards,
We’ve run 18,000 images with no problems.
100 GCPs
took a little while though