by_box=False, fraction_of_no_box=0) #create train/test loaders, with CUSTOM COLLATE function dataloader = torch.utils.data.DataLoader(dataset, batch_size=1, shuffle=True, collate_fn=AVD.collate) id_to_name = GetDataSet.get_class_id_to_name_dict(data_path) name_to_id = {} for cid in id_to_name.keys(): name_to_id[id_to_name[cid]] = cid target_images = get_target_images(target_path, name_to_id.keys(), for_testing=True, means=means) #test multiple trained nets for model_name in trained_model_names: print model_name # load net net = TDID() network.load_net(trained_model_path + model_name + '.h5', net) print('load model successfully!') net.cuda() net.eval() # evaluation test_net(model_name,
#i.e. target_path/target_0/* has one type of target image for each object # target_path/target_1/* has another type of target image #type of target image can mean different things, #probably different type is different view #each type can have multiple images, #i.e. target_0/* can have multiple images per object #target_path = '/net/bvisionserver3/playpen/ammirato/Data/instance_detection_targets/AVD_single_bb_targets/' #target_path = '/net/bvisionserver3/playpen/ammirato/Data/instance_detection_targets/sygen_many_bb_similar_targets/' #target_path = '/net/bvisionserver3/playpen/ammirato/Data/instance_detection_targets/AVD_BB_exact_few/' #target_path = '/net/bvisionserver3/playpen/ammirato/Data/instance_detection_targets/AVD_BB_exact_few_and_other_BB_gen/' #target_path = '/net/bvisionserver3/playpen10/ammirato/Data/instance_detection_targets/AVD_BB_exact_few_and_other_BB_gen_160_varied/' #target_path = '/net/bvisionserver3/playpen10/ammirato/Data/instance_detection_targets/AVD_BB_exact_few_and_other_BB_gen_160/' target_path = '/net/bvisionserver3/playpen10/ammirato/Data/instance_detection_targets/AVD_BB_exact_few_and_other_BB_gen_and_AVD_ns_BB_160/' #val_target_path = '/net/bvisionserver3/playpen10/ammirato/Data/instance_detection_targets/AVD_BB_exact_few_and_other_BB_gen_160/' val_target_path = target_path target_images = get_target_images(target_path,name_to_id.keys(), preload_images=preload_target_images,means=None) if use_torch_vgg: val_target_images = get_target_images(target_path,name_to_id.keys(), for_testing=True, bn_normalize=True) else: val_target_images = get_target_images(target_path,name_to_id.keys(), for_testing=True, means=means) #make sure only targets that have ids, and have target images are chosen chosen_ids = list(set(set(chosen_ids) & set(name_to_id.values()))) for vci in val_chosen_ids: vci = list(set(set(vci) & set(name_to_id.values()))) for cid in chosen_ids:
means = np.array([[[102.9801, 115.9465, 122.7717]]]) #path that holds dirs of all targets #i.e. target_path/target_0/* has one type of target image for each object # target_path/target_1/* has another type of target image #type of target image can mean different things, #probably different type is different view #each type can have multiple images, #i.e. target_0/* can have multiple images per object #target_path = '/net/bvisionserver3/playpen/ammirato/Data/instance_detection_targets/AVD_single_bb_targets/' #target_path = '/net/bvisionserver3/playpen/ammirato/Data/instance_detection_targets/sygen_many_bb_similar_targets/' #target_path = '/net/bvisionserver3/playpen/ammirato/Data/instance_detection_targets/AVD_BB_exact_few/' #target_path = '/net/bvisionserver3/playpen/ammirato/Data/instance_detection_targets/AVD_BB_exact_few_and_other_BB_gen/' target_path = '/net/bvisionserver3/playpen10/ammirato/Data/instance_detection_targets/AVD_BB_exact_few_and_other_BB_gen_and_AVD_ns_BB_80/' target_images = get_target_images(target_path, name_to_id.keys(), preload_images=preload_target_images) val_target_images = get_target_images(target_path, name_to_id.keys(), for_testing=True, means=means) #make sure only targets that have ids, and have target images are chosen chosen_ids = list(set(set(chosen_ids) & set(name_to_id.values()))) for vci in val_chosen_ids: vci = list(set(set(vci) & set(name_to_id.values()))) for cid in chosen_ids: if cid == 0: continue if ((len(target_images[id_to_name[cid]]) < 1) or (len(target_images[id_to_name[cid]][0])) < 1):