Closed alialilc closed 5 years ago
Hi alialilc, sorry for my late reply. The first model in experiments corresponds to the first class in class_names and so on. So the names do not have to match. Did you try with integers instead of strings for the classes? Check the returned all_class_idcs in line 52 aae_retina_webcam_pose.py
it's helpful, thanks a lot!
I want to use the camera to detect multiple object poses. I have trained 3 models and introduced them in aae_retina_webcam.cfg: Experiments = ['exp_group/my_autoencoder', 'exp_group/my_autoencoder-1', 'exp_group/my_autoencoder-2'], The retinanet network has also been trained and has been verified to correctly identify these models in the picture, as introduced in aae_retina_webcam.cfg as follows: [DETECTOR] Detector_model_path = /home/a/Downloads/keras-retinanet-master/newmodel.h5 Backbone = resnet50 Class_names = ['1','5','6'] However, in video stream detection aae_retina_webcam_pose.py, only one model can always be detected. Is the model name trained in AAE consistent with the model name of the retinanet training? For example, the model name is ‘1.ply’ and in retinanet is '1’.