zhukangkang(朱康康)

my dataset format is /home/data/JPEGImages/34--Baseball_34_Baseball_Baseball_34_465.jpg 227,250,256,281,0 928,938,75,87,0 in one line each image and threshold is default as score_threshold=.6, iou_threshold=.5 also i just set one classes and label is 0

i tried 0.1,as some has result, but seems not correct, so i retrained based on the final model, but loss keep on >13 , so how can i reduce the...

input_shape = (416,416) batch_size = 16 learning rate as use your default not changed lr=1e-3 (freeze) lr=1e-4(unfreeze)

no, as i not change the freezing operation in the code

also what about the memory usage with your GPU , as i tested with 980TI > 5GB

first time i trained with both frozen and unfrozen, second time ,i retrain with set the frozen as false like you said above based on the first step result model...

as the dataset i trained on yolo v3 dosn't has such issue , and loss is ~ 1.8

as i just want a good performance ,but now seems not , thanks for your replay, i will check it more

can you give some detail explain about the commit calloc function, as i just want reduce in test stage on device, not training