Help with 06. Train Faster-RCNN end-to-end on PASCAL VOC example

I’m new on gluon and I decided to run the examples to get familiar with the coding style (I used keras a couple years ago and this hybrid style is a little bit confusing to me).
My problem is that I can run the examples, but after successfully executing every cell on this example I upload an external image and the net seems to be incapable of detecting any object.
I pasted the same cell on the 02. Predict with pre-trained Faster RCNN models and the pre-trained net had no problem detecting every person on the image, so it seems to me that the model in the example is not being trained correctly.
Has this happened to anyone else?
Am I missing something?

Thank you in advance!

(by the way, I have try uncommenting the 32th line of the training loop (the one with utograd.backward), changing the break-if limit on the same loop with no luck)


My test image

Cell to detect objects on the image
short, max_size = 600, 800
RCNN_transform = presets.rcnn.FasterRCNNDefaultTrainTransform(short, max_size)

myImg = ‘unnamed.jpg’
x, img = data.transforms.presets.rcnn.load_test(myImg)

box_ids, scores, bboxes = net(x)
ax = utils.viz.plot_bbox(img, bboxes[0], scores[0], box_ids[0], class_names=net.classes)