Hello everyone,
I Customized my own yolov3 with Tlt, and was about to port it on python
Problem is : when testing model in yolo notebook, inferences are really slow : they cap at 2.53 it/s with batch size one, fp size 32 or 16 (same result), and model pruned, then retrained.
My graphic card is a Titan RTX.
My config :
random_seed: 42
yolo_config {
big_anchor_shape: “[(114.94, 60.67), (159.06, 114.59), (297.59, 176.38)]”
mid_anchor_shape: “[(42.99, 31.91), (79.57, 31.75), (56.80, 56.93)]”
small_anchor_shape: “[(15.60, 13.88), (30.25, 20.25), (20.67, 49.63)]”
matching_neutral_box_iou: 0.5arch: “resnet”
nlayers: 18
arch_conv_blocks: 2loss_loc_weight: 0.75
loss_neg_obj_weights: 200.0
loss_class_weights: 1.0freeze_blocks: 0
freeze_bn: false
}
training_config {
batch_size_per_gpu: 8
num_epochs: 80
enable_qat: false
learning_rate {
soft_start_annealing_schedule {
min_learning_rate: 1e-6
max_learning_rate: 1e-4
soft_start: 0.1
annealing: 0.8
}
}
regularizer {
type: L1
weight: 5e-5
}
}
eval_config {
validation_period_during_training: 10
average_precision_mode: SAMPLE
batch_size: 8
matching_iou_threshold: 0.5
}
nms_config {
confidence_threshold: 0.01
clustering_iou_threshold: 0.6
top_k: 200
}
augmentation_config {
preprocessing {
output_image_width: 1248
output_image_height: 384
output_image_channel: 3
crop_right: 1248
crop_bottom: 384
min_bbox_width: 1.0
min_bbox_height: 1.0
}
spatial_augmentation {
hflip_probability: 0.5
vflip_probability: 0.0
zoom_min: 0.7
zoom_max: 1.8
translate_max_x: 8.0
translate_max_y: 8.0
}
color_augmentation {
hue_rotation_max: 25.0
saturation_shift_max: 0.20000000298
contrast_scale_max: 0.10000000149
contrast_center: 0.5
}
}
dataset_config {
data_sources: {
tfrecords_path: “/workspace/tlt-experiments/data/tfrecords/kitti_trainval/kitti_trainval*”
image_directory_path: “/workspace/tlt-experiments/data/training”
}
image_extension: “jpg”
target_class_mapping {
key: “car”
value: “car”
}
validation_fold: 0
}
‘’‘’
Other trouble, when doing inference with yolo, it seems that non max suppression is not applied. Is it normal?