deepstream5.1
tlt3.0
train.txt
random_seed: 42
yolov4_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)]”
box_matching_iou: 0.25
arch: “resnet”
nlayers: 10
arch_conv_blocks: 2
loss_loc_weight: 0.8
loss_neg_obj_weights: 100.0
loss_class_weights: 0.5
label_smoothing: 0.0
big_grid_xy_extend: 0.05
mid_grid_xy_extend: 0.1
small_grid_xy_extend: 0.2
freeze_bn: false
#freeze_blocks: 0
force_relu: false
}
training_config {
batch_size_per_gpu: 12
num_epochs: 80
enable_qat: false
checkpoint_interval: 1
learning_rate {
soft_start_cosine_annealing_schedule {
min_learning_rate: 1e-6
max_learning_rate: 1e-4
soft_start: 0.3
}
}
regularizer {
type: L1
weight: 3e-5
}
optimizer {
adam {
epsilon: 1e-7
beta1: 0.9
beta2: 0.999
amsgrad: false
}
}
#pretrain_model_path: “/workspace/tlt-experiments/yolo_v4/pretrained_resnet10/tlt_pretrained_object_detection_vresnet10/resnet_10.hdf5”
pretrain_model_path:"/workspace/tlt-experiments/yolo_v4/experiment_dir_unpruned/weights/yolov4_resnet10_epoch_014.tlt"
}
eval_config {
average_precision_mode: SAMPLE
batch_size: 8
matching_iou_threshold: 0.5
}
nms_config {
confidence_threshold: 0.001
clustering_iou_threshold: 0.5
top_k: 200
}
augmentation_config {
hue: 0.1
saturation: 1.5
exposure:1.5
vertical_flip:0
horizontal_flip: 0.5
jitter: 0.3
output_width: 640
output_height: 384
randomize_input_shape_period: 0
mosaic_prob: 0.5
mosaic_min_ratio:0.2
}
dataset_config {
data_sources: {
label_directory_path: “/workspace/tlt-experiments/data/training/label_2”
image_directory_path: “/workspace/tlt-experiments/data/training/image_2”
}
include_difficult_in_training: true
target_class_mapping {
key: “person”
value: “person”
}
validation_data_sources: {
label_directory_path: “/workspace/tlt-experiments/data/val/label_2”
image_directory_path: “/workspace/tlt-experiments/data/val/image_2”
}
}
[nvinfer config file]
[property]
gpu-id=0
net-scale-factor=1.0
offsets=103.939;116.779;123.68
model-color-format=1
labelfile-path=/home/satchel/deepstream_models/person1/labels.txt
model-engine-file=/home/satchel/deepstream_models/person1/yolov4_resnet10_epoch_080.etlt_b1_gpu0_fp32.engine
#int8-calib-file=…/…/models/yolov4/cal.bin
tlt-encoded-model=/home/satchel/deepstream_models/person1/yolov4_resnet10_epoch_080.etlt
tlt-model-key=***
infer-dims=3;384;640
maintain-aspect-ratio=1
uff-input-order=0
uff-input-blob-name=Input
batch-size=1
network-mode=0
num-detected-classes=1
interval=0
gie-unique-id=1
is-classifier=0
#network-type=0
cluster-mode=3
output-blob-names=BatchedNMS
parse-bbox-func-name=NvDsInferParseCustomBatchedNMSTLT
custom-lib-path=/home/satchel/deepstream_models/person1/libnvds_infercustomparser_tlt.so
[class-attrs-all]
pre-cluster-threshold=0.3
roi-top-offset=0
roi-bottom-offset=0
detected-min-w=0
detected-min-h=0
detected-max-w=0
detected-max-h=0
the reference deploy project
https://github.com/NVIDIA-AI-IOT/deepstream_tlt_apps
export ENABLE_DEBUG=1
log out:
label/conf/ x/y x/y – 0 6.14712e+32 0.00782681 0.00782668 0.00782092 0.0078125
label/conf/ x/y x/y – 0 5.79216e+32 0.0078125 0.0078125 0.00782681 0.00782681
label/conf/ x/y x/y – 0 4.93015e+32 0.00781612 0.0078125 0.0078125 0.00782681
label/conf/ x/y x/y – 0 4.5752e+32 0.00782681 0.0078125 0.00782681 0.00782681
label/conf/ x/y x/y – 0 3.99207e+32 0.0078125 0.0078125 0.00782037 0.00782681
could someone help me? Thanks very much!