please, what parameters are needed for optimal forecast of the model in BatchGenerator
train_dataset.generate(batch_size=batch_size,
shuffle=True,
train=True,
ssd_box_encoder=ssd_box_encoder,
convert_to_3_channels=True,
equalize=True,
brightness=(0.5, 2, 0.5),
flip=0.5,
translate=False,
scale=False,
max_crop_and_resize=(img_height, img_width, 1, 3),
This one is important because the Pascal VOC images vary in size
random_pad_and_resize=(img_height, img_width, 1, 3, 0.5),
# This one is important because the Pascal VOC images vary in size
random_crop=False,
crop=False,
resize=False,
gray=False,
limit_boxes=True,
# While the anchor boxes are not being clipped, the ground truth boxes should be
include_thresh=0.5)
please, what parameters are needed for optimal forecast of the model in BatchGenerator train_dataset.generate(batch_size=batch_size, shuffle=True, train=True, ssd_box_encoder=ssd_box_encoder, convert_to_3_channels=True, equalize=True, brightness=(0.5, 2, 0.5), flip=0.5, translate=False, scale=False, max_crop_and_resize=(img_height, img_width, 1, 3),
This one is important because the Pascal VOC images vary in size