Hi Morganh,
How many classed? 2 classes.
man=10160 instances. not images
woman=10649 instances. not images
Resolution: 608*608
mAP around 65% for both
should I freeze more layers or no zero is enough, or should I freeze more as all the classes fall under PeopleNet?
The specs file
random_seed: 42
model_config {
pretrained_model_file: “/workspace/pretrained_model/tlt_peoplenet_vunpruned_v2.0/resnet34_peoplenet.tlt”
num_layers: 34
freeze_blocks: 0
freeze_blocks: 1
freeze_blocks: 2
freeze_blocks: 3
arch: “resnet”
use_batch_norm: true
activation {
activation_type: “relu”
}
dropout_rate: 0.1
objective_set: {
cov {}
bbox {
scale: 35.0
offset: 0.5
}
}
training_precision {
backend_floatx: FLOAT32
}
}
augmentation_config {
preprocessing {
output_image_width: 608
output_image_height: 608
output_image_channel: 3
min_bbox_width: 1.0
min_bbox_height: 1.0
}
spatial_augmentation {
hflip_probability: 0.5
vflip_probability: 0.0
zoom_min: 1.0
zoom_max: 1.0
translate_max_x: 8.0
translate_max_y: 8.0
}
color_augmentation {
color_shift_stddev: 0.0
hue_rotation_max: 25.0
saturation_shift_max: 0.2
contrast_scale_max: 0.1
contrast_center: 0.5
}
}
bbox_rasterizer_config {
target_class_config {
key: “man”
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: “woman”
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: 0.67
}
cost_function_config {
target_classes {
name: “man”
class_weight: 1.0
coverage_foreground_weight: 0.05
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: “woman”
class_weight: 1.0
coverage_foreground_weight: 0.05
objectives {
name: “cov”
initial_weight: 1.0
weight_target: 1.0
}
objectives {
name: “bbox”
initial_weight: 10.0
weight_target: 10.0
}
}
enable_autoweighting: False
max_objective_weight: 0.9999
min_objective_weight: 0.0001
}
training_config {
batch_size_per_gpu: 7
num_epochs: 700
learning_rate {
soft_start_annealing_schedule {
min_learning_rate: 5e-6
max_learning_rate: 5e-4
soft_start: 0.1
annealing: 0.7
}
}
regularizer {
type: L1
weight: 3e-9
}
optimizer {
adam {
epsilon: 1e-08
beta1: 0.9
beta2: 0.999
}
}
cost_scaling {
enabled: False
initial_exponent: 20.0
increment: 0.005
decrement: 1.0
}
checkpoint_interval: 10
}
postprocessing_config {
target_class_config {
key: “man”
value: {
clustering_config {
coverage_threshold: 0.005
dbscan_eps: 0.15
dbscan_min_samples: 0.05
minimum_bounding_box_height: 10
}
}
}
target_class_config {
key: “woman”
value: {
clustering_config {
coverage_threshold: 0.005
dbscan_eps: 0.15
dbscan_min_samples: 0.05
minimum_bounding_box_height: 10
}
}
}
}
dataset_config {
data_sources: {
tfrecords_path: “/workspace/tfrecrods/train/*”
image_directory_path: “/workspace/dataset/train”
}
image_extension: “jpg”
target_class_mapping {
key: “man”
value: “man”
}
target_class_mapping {
key: “woman”
value: “woman”
}
#validation_fold: 0
validation_data_source: {
tfrecords_path: “/workspace/tfrecords_test/*”
image_directory_path: “/workspace/dataset/test”
}
}
evaluation_config {
validation_period_during_training: 10
first_validation_epoch: 1
minimum_detection_ground_truth_overlap {
key: “man”
value: 0.5
}
minimum_detection_ground_truth_overlap {
key: “woman”
value: 0.5
}
evaluation_box_config {
key: “man”
value {
minimum_height: 4
maximum_height: 9999
minimum_width: 4
maximum_width: 9999
}
}
evaluation_box_config {
key: “woman”
value {
minimum_height: 4
maximum_height: 9999
minimum_width: 4
maximum_width: 9999
}
}
}