To evaluate kitti dataset with tlt-evaluate, please refer to the jupyter notebook inside the docker.
To evaluate the peoplenet with tlt-evaluate, refer to People Net - - #5 by Morganh
More, one spec for reference.
random_seed: 42
dataset_config {
data_sources {
tfrecords_path: “your tfrecord”
image_directory_path: “your own image”
}
image_extension: “jpg”
target_class_mapping {
key: “person”
value: “Person”
}
target_class_mapping {
key: “Person”
value: “Person”
}
target_class_mapping {
key: “rider”
value: “Person”
}
target_class_mapping {
key: “Rider”
value: “Person”
}
target_class_mapping {
key: “personal_bag”
value: “Bag”
}
target_class_mapping {
key: “rolling_bag”
value: “Bag”
}
target_class_mapping {
key: “face”
value: “Face”
}validation_fold: 0
}
augmentation_config {
preprocessing {
output_image_width: 960
output_image_height: 544
crop_right: 960
crop_bottom: 544
min_bbox_width: 1.0
min_bbox_height: 1.0
output_image_channel: 3
}
spatial_augmentation {
hflip_probability: 0.5
zoom_min: 1.0
zoom_max: 1.0
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
}
}
postprocessing_config {
target_class_config {
key: “Person”
value {
clustering_config {
coverage_threshold: 0.00499999988824
dbscan_eps: 0.20000000298
dbscan_min_samples: 0.0500000007451
minimum_bounding_box_height: 4
}
}
}
target_class_config {
key: “Bag”
value {
clustering_config {
coverage_threshold: 0.00499999988824
dbscan_eps: 0.15000000596
dbscan_min_samples: 0.0500000007451
minimum_bounding_box_height: 4
}
}
}
target_class_config {
key: “Face”
value {
clustering_config {
coverage_threshold: 0.00499999988824
dbscan_eps: 0.15000000596
dbscan_min_samples: 0.0500000007451
minimum_bounding_box_height: 4
}
}
}
}
model_config {
pretrained_model_file: “/workspace/its/peoplenet/resnet34_peoplenet.tlt”
num_layers: 34
load_graph: True
use_batch_norm: False
activation {
activation_type: “relu”
}
objective_set {
bbox {
scale: 35.0
offset: 0.5
}
cov {
}
}
training_precision {
backend_floatx: FLOAT32
}
arch: “resnet”
}
evaluation_config {
validation_period_during_training: 1
first_validation_epoch: 1
minimum_detection_ground_truth_overlap {
key: “Person”
value: 0.699999988079
}
minimum_detection_ground_truth_overlap {
key: “Bag”
value: 0.5
}
minimum_detection_ground_truth_overlap {
key: “Face”
value: 0.5
}
evaluation_box_config {
key: “Person”
value {
minimum_height: 20
maximum_height: 9999
minimum_width: 10
maximum_width: 9999
}
}
evaluation_box_config {
key: “Bag”
value {
minimum_height: 20
maximum_height: 9999
minimum_width: 10
maximum_width: 9999
}
}
evaluation_box_config {
key: “Face”
value {
minimum_height: 20
maximum_height: 9999
minimum_width: 10
maximum_width: 9999
}
}
average_precision_mode: INTEGRATE
}
cost_function_config {
target_classes {
name: “Person”
class_weight: 1.0
coverage_foreground_weight: 0.0500000007451
objectives {
name: “cov”
initial_weight: 1.0
weight_target: 1.0
}
objectives {
name: “bbox”
initial_weight: 10.0
weight_target: 10.0
}
}
target_classes {
name: “Bag”
class_weight: 8.0
coverage_foreground_weight: 0.0500000007451
objectives {
name: “cov”
initial_weight: 1.0
weight_target: 1.0
}
objectives {
name: “bbox”
initial_weight: 10.0
weight_target: 1.0
}
}
target_classes {
name: “Face”
class_weight: 4.0
coverage_foreground_weight: 0.0500000007451
objectives {
name: “cov”
initial_weight: 1.0
weight_target: 1.0
}
objectives {
name: “bbox”
initial_weight: 10.0
weight_target: 10.0
}
}
enable_autoweighting: true
max_objective_weight: 0.999899983406
min_objective_weight: 9.99999974738e-05
}
training_config {
batch_size_per_gpu: 16
num_epochs: 10
learning_rate {
soft_start_annealing_schedule {
min_learning_rate: 10e-10
max_learning_rate: 10e-10
soft_start: 0.0
annealing: 0.3
}
}
regularizer {
type: L1
weight: 3.00000002618e-09
}
optimizer {
adam {
epsilon: 9.99999993923e-09
beta1: 0.899999976158
beta2: 0.999000012875
}
}
cost_scaling {
initial_exponent: 20.0
increment: 0.005
decrement: 1.0
}
checkpoint_interval: 10
}
bbox_rasterizer_config {
target_class_config {
key: “Person”
value {
cov_center_x: 0.5
cov_center_y: 0.5
cov_radius_x: 0.40000000596
cov_radius_y: 0.40000000596
bbox_min_radius: 1.0
}
}
target_class_config {
key: “Bag”
value {
cov_center_x: 0.5
cov_center_y: 0.5
cov_radius_x: 1.0
cov_radius_y: 1.0
bbox_min_radius: 1.0
}
}
target_class_config {
key: “Face”
value {
cov_center_x: 0.5
cov_center_y: 0.5
cov_radius_x: 1.0
cov_radius_y: 1.0
bbox_min_radius: 1.0
}
}
deadzone_radius: 0.400000154972
}