CAFFE model generation

I need generation of CAFFE + MobileNet SSD model based on images (you will get them) so that any OpenCV example app (e.g. its readNetFromCaffe() function) can accurately infer the moving objects on the road into the following four classes:
1. Vehicles (1000 images)
2. Cargo vehicles (1000 images: 700 trucks and 300 vans should go into same class)
3. Citybus (1000 images)
4. Touristbus (12 images)

All images are in 704x576 resolution and are labeled as such.
Inference will run on Win10 machine inside my own C++ app that is based upon OpenCV ver. 4.10 and *from realtime video* . Recognition accuracy should reach >= 95%. FPS rate should be >= 10 FPS (e.g raw inference time <= 100 ms on Intel I7 CPU).

Model might be perhaps done in Caffe2 instead (if you are more convenient with it) but the final result must be fully functional and accurate in the above mentioned environment.
About the recuiter
Member since Sep 11, 2017
Aedan Burke
from Galway, Ireland

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