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)