def test_input_fn(model):
model_helper.AddVideoInput(
model,
test_reader,
batch_size=batch_per_device,
length_rgb=args.clip_length_rgb,
clip_per_video=1,
decode_type=0,
random_mirror=False,
random_crop=False,
sampling_rate_rgb=args.sampling_rate_rgb,
scale_h=args.scale_h,
scale_w=args.scale_w,
crop_size=args.crop_size,
video_res_type=args.video_res_type,
short_edge=min(args.scale_h, args.scale_w),
num_decode_threads=args.num_decode_threads,
do_multi_label=args.multi_label,
num_of_class=args.num_labels,
input_type=args.input_type,
length_of=args.clip_length_of,
sampling_rate_of=args.sampling_rate_of,
frame_gap_of=args.frame_gap_of,
do_flow_aggregation=args.do_flow_aggregation,
flow_data_type=args.flow_data_type,
get_rgb=(args.input_type == 0),
get_optical_flow=(args.input_type == 1),
get_video_id=args.get_video_id,
use_local_file=args.use_local_file,
)
def add_video_input(model):
model_helper.AddVideoInput(
model,
train_reader,
batch_size=batch_per_device,
length_rgb=args.clip_length_rgb,
clip_per_video=1,
random_mirror=True,
decode_type=0,
sampling_rate_rgb=args.sampling_rate_rgb,
scale_h=args.scale_h,
scale_w=args.scale_w,
crop_size=args.crop_size,
video_res_type=args.video_res_type,
short_edge=min(args.scale_h, args.scale_w),
num_decode_threads=args.num_decode_threads,
do_multi_label=args.multi_label,
num_of_class=args.num_labels,
random_crop=True,
input_type=args.input_type,
length_of=args.clip_length_of,
sampling_rate_of=args.sampling_rate_of,
frame_gap_of=args.frame_gap_of,
do_flow_aggregation=args.do_flow_aggregation,
flow_data_type=args.flow_data_type,
get_rgb=(args.input_type == 0 or args.input_type >= 3),
get_optical_flow=(args.input_type == 1 or args.input_type >= 4),
get_logmels=(args.input_type >= 2),
get_video_id=args.get_video_id,
jitter_scales=[int(n) for n in args.jitter_scales.split(',')],
use_local_file=args.use_local_file,
)
def test_input_fn(model):
model_helper.AddVideoInput(
test_model,
test_reader,
batch_size=args.batch_size,
clip_per_video=args.clip_per_video,
decode_type=1,
length_rgb=args.clip_length_rgb,
sampling_rate_rgb=args.sampling_rate_rgb,
scale_h=args.scale_h,
scale_w=args.scale_w,
crop_size=args.crop_size,
num_decode_threads=4,
num_of_class=args.num_labels,
random_mirror=False,
random_crop=False,
input_type=args.input_type,
length_of=args.clip_length_of,
sampling_rate_of=args.sampling_rate_of,
frame_gap_of=args.frame_gap_of,
do_flow_aggregation=args.do_flow_aggregation,
flow_data_type=args.flow_data_type,
get_rgb=(args.input_type == 0),
get_optical_flow=(args.input_type == 1),
get_video_id=args.get_video_id,
use_local_file=args.use_local_file,
)
def test_input_fn(model):
model_helper.AddVideoInput(test_data_loader, test_reader,
**video_input_args)
def input_fn(model):
model_helper.AddVideoInput(model, reader, **video_input_args)
