Hello guys!
I retrained MobilenetSSD by using the Tensorflow Obect Detection API, and am now trying to load the frozen inference graph using the dnn module function:
net = cv.dnn.readNetFromTensorflow(prototxt, weights)
where I use https://github.com/opencv/opencv_extra/tree/master/testdata/dnn/ssd_mobilenet_v1_coco.pbtxt as 'pbtxt' with the num_classes set to my retrained number of classes and the frozen graph as 'weights'.
However, the output is just a bunch of random boxes. The inference is correct when using pure tensorflow, but that is too slow for my application.
My theory is a mismatch between the structure of graph definitions used by the Tensorflow Object Detection and the one used by OpenCV dnn module, but I would love to hear if anyone have any experience with the problem or some suggestions on how to solve it?
I am using Opencv 3.4.0 with contrib modules.
Kind regards, XenonHawk