mode='test')
genVal = DataGenerator(imagesMeta=data.valGTMeta,
cfg=cfg,
data_type='val',
do_meta=True,
mode='test')
# genTest = DataGenerator(imagesMeta = data.testGTMeta, cfg=cfg, data_type='test', do_meta=True)
Models = methods.AllModels(cfg,
mode='test',
do_rpn=False,
do_det=True,
do_hoi=False)
Stages = stages.AllStages(cfg,
Models,
obj_mapping,
hoi_mapping,
mode='test')
# Val data
evalVal = det_test.saveEvalData(genVal, Stages, cfg, obj_mapping)
det_test.saveEvalResults(genVal, cfg)
# Test data
#evalTest = det_test.saveEvalData(genTest, Stages, cfg, obj_mapping)
#det_test.saveEvalResults(evalTest, genTest, cfg)
# Train data
#evalTrain = det_test.saveEvalData(genTrain, Stages, cfg, obj_mapping)
#det_test.saveEvalResults(evalTrain, genTrain, cfg)
data = extract_data.object_data(False)
# config
cfg = data.cfg
#cfg.do_fast_hoi = True
obj_mapping = data.class_mapping
hoi_mapping = data.hoi_labels
# data
genTrain = DataGenerator(imagesMeta=data.trainGTMeta,
cfg=cfg,
data_type='train',
do_meta=True)
#genTest = DataGenerator(imagesMeta = data.valGTMeta, cfg=cfg, data_type='test', do_meta=True, mode='test', approach='new')
Stages = stages.AllStages(cfg, None, obj_mapping, hoi_mapping, mode='test')
#imageID = 'HICO_test2015_00005579'
#imageMeta = genTest.imagesMeta[imageID]
#X, y, imageDims = Stages.stagezero(imageMeta, genTest.data_type)
#imageInputs = utils.load_obj(cfg.my_input_path + 'testnewest/' + imageID)
#Y_tmp = filters_hoi.loadData(imageInputs, imageDims, cfg)
#[hbboxes, obboxes, target_labels, all_val_map] = Y_tmp
#hbboxes, obboxes, target_labels, val_map = filters_hoi.reduceTargets(Y_tmp, cfg)
#patterns = filters_hoi.createInteractionPatterns(hbboxes, obboxes, cfg)
#hcrops, ocrops = filters_hoi.convertBB2Crop(X, hbboxes, obboxes, imageDims)
#Models = methods.AllModels(cfg, mode='test', do_rpn=True, do_det=True, do_hoi=False)
#cfg.det_nms_overlap_thresh = 0.5
#Stages = stages.AllStages(cfg, Models, obj_mapping, hoi_mapping, mode='train')
#
##STAGE 0
genVal = DataGenerator(imagesMeta=data.valGTMeta,
cfg=cfg,
data_type='test',
do_meta=True,
mode='test')
# genTest = DataGenerator(imagesMeta = data.valGTMeta, cfg=cfg, data_type='test', do_meta=True, mode='test')
#if False:
Models = methods.AllModels(cfg,
mode='test',
do_rpn=True,
do_det=True,
do_hoi=True)
Stages = stages.AllStages(cfg,
Models,
obj_mapping,
hoi_mapping,
mode='test',
return_times=True)
generator = genVal
genIterator = generator.begin()
nb_iterations = 1
all_times = np.zeros((nb_iterations, 5))
for i in range(nb_iterations):
X, y, imageMeta, imageDims, times = next(genIterator)
# imageID = 'Play_Saxophone_007'
# imageMeta = generator.imagesMeta[imageID]
# X, y, imageDims = Stages.stagezero(imageMeta, generator.data_type)
data = extract_data.object_data()
cfg = data.cfg
obj_mapping = data.class_mapping
hoi_mapping = data.hoi_labels
# Create batch generators
genTrain = DataGenerator(imagesMeta = data.trainGTMeta, cfg=cfg, data_type='train', do_meta=True)
genTest = DataGenerator(imagesMeta = data.valGTMeta, cfg=cfg, data_type='test', do_meta=True)
Models = methods.AllModels(cfg, mode='test', do_rpn=True, do_det=True, do_hoi=False)
sys.stdout.flush()
if True:
cfg.det_nms_overlap_thresh = 0.5
Stages = stages.AllStages(cfg, Models, obj_mapping, hoi_mapping, mode='train')
imageInputs, imageID, bboxes = hoi_test.saveInputData(genTest, Stages, cfg)
cfg.det_nms_overlap_thresh = 0.9
Stages = stages.AllStages(cfg, Models, obj_mapping, hoi_mapping, mode='train')
imageInputs, imageID, bboxes = hoi_test.saveInputData(genTrain, Stages, cfg)
# cfg.det_nms_overlap_thresh = 0.5
# Stages = stages.AllStages(cfg, Models, obj_mapping, hoi_mapping, mode='train')
# imageInputs, imageID, bboxes = hoi_test.saveInputData(genTrain, Stages, cfg, do_train_eval=True)
if False:
# imageID = 'HICO_train2015_00025124'
imageInputs = utils.load_obj(cfg.my_output_path + imageID)
# keys = list(inputMeta.keys())