I have a big problem yet described and discussed here: Problem with Partial Use of Photos during Creation of Orthophoto in WebODM .I have drone pictures over forest and it is impossible to get a complete orthofoto. Just a quarter will be finished. What can I do? I tried out all adaptions of parameters yet described, but nothing changes…
Thank you !
Hi @TommyB 
have you been able to process it with some other software, or just WebODM? I ask because perhaps there’s something wrong with the input data. Dense vegetation is particularly difficult to stitch. If you can upload your pictures on Google Drive we can take a look and make recommendations.
I also had problems getting WebODM or Open Drone Map to process forest images. Using defaul settings, I would either get an error or a partial reconstruction using less than a quarter of the images. Following suggestions in the forum, I increased the min-num-features to the 12000 to 24000 range and use pmvs. I still have some images omitted from the analysis, but rerunning can improve the resulting orthomosaic. I suspect that the random process of obtaining strips from each image influences successful matching. I also found that I had to fly missions at higher altitudes (100 to 120 m). I haven’t been able to process images from missions at the 40 to 50 m altitude with 80% overlap. I suspect that I would have to increase overlap to 90%.
The other issue with processing images with ODM is failure to allocate sufficient memory for the application. I had to set up a virtual server running Ubuntu to finally succeed in processing images. I adhere to the minimum recommended configuration, but still have occasional failures due to memory issues. Parallax issues and uniformity of forest cover create problems for ODM and other mapping software. Nevertheless, you can get partial reconstructions from ODM by increasing min-num-features and using the pmvs option. If you encounter memory issues, you will need to migrate your application to a larger platform.
I cannot find a pmvs option in WebODM. Please advise asap as I experience the same issues with forested areas and the ‘Forest’ preset produces less desirable results than my own experimentation with parameters.
Processing forest images with ODM remains difficult. I have now switched to using the WebODM Lightning server (command line option) with greater success. I find that simply using the defaults (min-num-features 8000) and using
./odm images/image_folder_name --skip-3dmodel
works well most of the time. I still have some occasional problems with receiving only partial orthoimages from some image sets, and the stitching process is very sensitive to the image overlap. At an altitude of 150 m, I am unable to obtain consistent orthoimages with overlaps of less than 80% for forests, especially after the canopy closes. The best overlap appears to be near 90%.
When I was using ODM with a virtual server, I also found that rerunning the program with the same image set often produced different orthoimages (sometimes complete). It appears that the selection of strips for image matching is random.
Because I have had difficulty in obtaining consistent orthoimages from my flights, I have had to develop R scripts to analyze and align individual images. (I use a Sentea Double 4K Multispectral Sensor to obtain narrow band red, green, and blue bands from one camera and red edge and near infrared from a second camera in the sensor.) Looking at overlapping images, I am amazed that ODM works at all. The parallax effect on adjacent images is visually striking and images of closed canopies are difficulty to align manually. There is indeed magic in the ODM algorithms.
Regarding the pmvs option. I have found that the documentation of options lags code changes in the various versions of ODM and keeping current with updates is thus a high priority. I now exclusively use the Lightning network WebODM for my work, and I recommend using the command line to insure consistent use of options. I have found that using drop down menus in WebODM interface to manually select options for each job is an open invitation for error.