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):
