AadeIT

keras_to_tensorflow.py add: from yolo3.model import yolo_head,yolo_body around 60 lines: def load_model(input_model_path, input_json_path=None, input_yaml_path=None):     if not Path(input_model_path).exists():         raise FileNotFoundError(            ...

keras_to_tensorflow.py add: from yolo3.model import yolo_head,yolo_body around 60 lines: def load_model(input_model_path, input_json_path=None, input_yaml_path=None):     if not Path(input_model_path).exists():         raise FileNotFoundError(            ...

@RosabanksiaeAit 我在win10上面的显卡可以跑通只需要把cuda_count改变就可以，但是无法把多块GPU沾满

@RosabanksiaeAit 你把这里改成99就可以进行训练了，你尝试一下，但是无法把多块GPU吃满，还是一块在跑

我也遇到了这个问题，可以说一下解决方案吗？

Namespace(batch_size=4, checkpoint_interval=1, compute_map=False, data_config='config/custom.data', epochs=100, evaluation_interval=1, gradient_accumulations=2, img_size=416, model_def ='config/yolov3-custom.cfg', multiscale_training=True, n_cpu=8, pretrained_weights='weights/darknet53.conv.74') Traceback (most recent call last): File "train.py", line 107, in loss, outputs = model(imgs, targets) File "D:\Anaconda\Anaconda_3\lib\site-packages\torch\nn\modules\module.py",...

I useing datasets name is DETRAC，image size is 960*540,You mean I change the size of the picture?

I changed the image size to 960*544, batch_size=2(I only have two pictures in my training folder, try to see if I can run through), but the problem is still this...

There's no way to think about these parameters, so let me think about it again. Thank you

@xiaoyuzhu666 try,change your filters of config file