I am using DeepStackAi with Blue Iris (a video security software).
I have configured it with a test camera.
The camera I use is one that has quiet good night vision (IPC-HDW5231R-Z).
I am only identifying persons in the generated pictures (-e VISION-DETECTION=True in the docker command). I am using the CPU version.
Day time detection seems to work as it should. I did not get any false alerts during my testing.
Nighttime is very different - it doesn’t detect any persons at all.
I am pretty sure all is configured OK since day time works without any issues but not sure why it doesn’t detect at night.
I can try and tweak the night time picture - more contrast and such.
But I am wondering if there is a better way? Like to “train” the model by feeding it some of the nighttime pictured generated by Blue Iris?
Hello @MnM, thanks for bringing this up.
You can run DeepStack in high accuracy model by adding -e MODE=HIgh . This would run slower but would detect better.
Also, can you share sample images from the test camera, so we can investigate this better?
@john are there object detection models trained on images from night vision (IR cameras like the IPC-HDW5231R-Z)? I am also interested in true thermal imaging (FLIR) cameras
I expect the pictures that @MnM are not of such high resolution and contrast as these example images, but it is very interesting that a silhouette works so well! Suggests that some pre-processing of the IR images might improve accuracy, perhaps by applying thresholding?
How did you manage to tune Deepstack in order to have good nightime image detection? I have False Negatives always with IR b/w images and I have a good IR camera.
During daytime works really great.
