stm32-modelzoo-app / object_detection /user_config_pt.yaml
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operation_mode: prediction
# ---------------- General Configuration ---------------- #
general:
saved_models_dir: 'st_yolodv2milli_actrelu_pt' # sub-dir, concat with output_dir
logger: 'tensorboard'
global_seed: 42
# ---------------- Model Configuration ---------------- #
model:
framework: 'torch'
model_type : st_yolod # this config is for yolod model family
# following are supported models
# ['st_yolodv2milli_actrelu_pt', 'st_yolodv2tiny_actrelu_pt']
model_name: st_yolodv2milli_actrelu_pt
pretrained: True
pretrained_dataset: coco # this yaml is for coco style annotation only
input_shape: [3, 640, 640] # (channel, height, width)
pretrained_input_shape : [3, 640, 640]
num_classes: 80 # number of classes
# ---------------- Dataset Configuration ---------------- #
dataset:
format : coco
dataset_name : coco
class_names: ["person","bicycle","car","motorcycle","airplane","bus","train","truck","boat","traffic light","fire hydrant","stop sign","parking meter","bench","bird","cat","dog","horse","sheep","cow","elephant","bear","zebra","giraffe","backpack","umbrella","handbag","tie","suitcase","frisbee","skis","snowboard","sports ball","kite","baseball bat","baseball glove","skateboard","surfboard","tennis racket","bottle","wine glass","cup","fork","knife","spoon","bowl","banana","apple","sandwich","orange","broccoli","carrot","hot dog","pizza","donut","cake","chair","couch","potted plant","bed","dining table","toilet","tv","laptop","mouse","remote","keyboard","cell phone","microwave","oven","toaster","sink","refrigerator","book","clock","vase","scissors","teddy bear","hair drier","toothbrush"]
seed: 123
num_workers: 4 # Set worker to 4 training process costs a lot of memory, reduce this value.
multiscale_range: 5 # Actual multiscale ranges: [640 - 5 * 32, 640 + 5 * 32]. To disable multiscale training, set the value to 0.
random_size: [10, 20] # You can uncomment this line to specify a multiscale range
prediction_path: ./datasets
# ---------------- preprocessing Configuration ---------------- #
preprocessing:
rescaling:
scale : 1 # not used for yolod
offset : 0 # not used for yolod
mean : [127,127,127] # not used for yolod
std : 128.0 # not used for yolod
resizing:
aspect_ratio: fit # not used for yolod
interpolation: nearest # not used for yolod
color_mode: rgb
# ---------------- postrocessing Configuration ---------------- #
postprocessing:
confidence_thresh: 0.001
NMS_thresh: 0.5
IoU_eval_thresh: 0.5
plot_metrics: False #True # Plot precision versus recall curves. Default is False.
max_detection_boxes: 100
mlflow:
uri: ./pt/src/experiments_outputs/mlruns
hydra:
run:
dir: ./pt/src/experiments_outputs/${now:%Y_%m_%d_%H_%M_%S}