I would say no need to undersell the accomplishments. Iāve tried to do what you did and lost my dang mind. From the screenshots that were shown when it was being promoted they were using yolo and even if you donāt have as many classes as they do I would say getting as far as you have so far is quite the accomplishment. In your spare time you have matched where they were.
As for the latex I could be wrong but I would think that the problem there would be the uniform color not having the usual details that yolo would look for to differentiate parts as it usually would look for. Perhaps treating latex scenes like a green screen and having large areas of voids changed to a different color or a gradient could bring out the details enough for it to work. Assuming of course that the problem is the tracking is not picking up enough details to properly track.
Yeeeeeah itās always a fun time when you get one bug squashed then finding two more that were hiding it never ends.
I will definitely investigate that option, makes total sense to try that out before running to the raw solution of enriching the dataset with more latex scene pictures (which might also have side effects on the detection quality for regular scenesā¦ who knowsā¦).
Funscript pos. estimation - Fixed - Close up did not deactivate the locked-penis-box, interfering with funscript pos, when it should be 100
Funscript pos. estimation - Fixed - Doggy not triggering action, under specific circumstances
Funscript pos. estimation - Fixed - Major issue in penis-inserted length computation
Funscript pos. estimation - Fixed - Cowgirl not defaulting to tracking absolute position of breast when pussy is covered (her red cloth at some point of the video), under specific circumstances
Funscript pos. estimation - Reworked - Part of the body parts interaction logic, lessening sudden jerky moves from one position to the other
Funscript pos. estimation - Reworked - Discarded hands positions passing over penis location during penetration
Application - Added - A proper logging system, writing to both console and FSGenerator.log => please share that file for any debugging purpose along with all other output files
Application - Added - A version number, for reference, both in logs and in funscript āversionā field
Application - Removed - All message dialog boxes that would prevent a batch processing approach as suggested by @jcwicked (thanks again, and PR on hold for now)
These changes have a major impact on the output files!
Tweaked the initial P-detection and locking. The logic was recently loosened up to be less restrictive, leading to erroneous early tracking
If you have already processed videos, you can reprocess them in minutes if you kept the matching _rawyolo.json file, you do not need to go through the hassle of a full YOLO detection, this fix only concerns the tracking layer of the logic.
So, to be honest @StillHorizon , JAVR is not easy because of the mosaicāed stuff, and I was almost going to answer you with a basic āNo, sorryā.
However, it is true that I included JAVR frames in my dataset for training, but maybe only 10% of the 4500 images used for training.
Yet, I had to make a recent tweak on the initial p-locking logic, making it less restrictive (it was initially waiting to detect a penis in full, with glans, and I can tell you this is not easy with the mosaic barreer).
I think the result shows great potential, great work on this. Is there any way the community can help out to fine tune the model for JAV VR and beyond?
I would gladly accept images and annotations, which is basically the hard part of the job.
I created a script that helps this hefty process, it can work on your video library, extract frames and suggests boxes that you would need to adjust, delete, or add.
This would take part of the dataset that we then train the YOLO model on.
But, oh boy it takes dedication.
It requires to be very thorough, as the quality of the labelling directly impact the quality of the model, thus, the detections and tracking => building of the output signal = funscript.
Just to be clear, most of the boxes with figures less than 1 were auto-detected by the current model, making it more a review and adjust/add/remove than when I started from scratchā¦ Back then, I had to do everything lol
it never ends.
