Hi, I was wondering how I can use one of the pretrained models from model ZOO to detect only one specific class of objects.
For example, if I’m using ‘ssd_512_resnet50_v1_coco’, I want to detect only one of the 80 COCO classes in images (say, “person”).
I’ve been trying to slice the array resulting from inference:
class_IDs, scores, bounding_boxes = net(x)
but the problem is that boolean masks are not supported, so if I try to select:
i t doesn’t work (the internal condition returns an array of 0s and 1s instead of True and False).
I managed to do it by using the following code:
class_IDs, scores, bounding_boxes = net(x) selected_class_ID =  selected_scores =  selected_bbox =  for ID, score, box in zip(class_IDs.asnumpy(), scores.asnumpy(), bounding_boxes.asnumpy()): # using ID== 0 because is the classID for "person" in COCO if (ID==0) & (score>0.45): selected_class_ID.append(ID) selected_scores.append(score) selected_bbox.append(box) selected_class_ID = nd.array(selected_class_ID) selected_scores = nd.array(selected_scores) selected_bbox = nd.array(selected_bbox) ax = utils.viz.plot_bbox(img, selected_bbox, selected_scores, selected_class_ID, thresh=.4, class_names=net.classes)
But it is kinda involved…is there anything else I could do?