fm64

Thank for your reply, it is indeed difficult without cuda(I am using windows with an Intel chip which makes it even worse) I haven't dig too much in models but...

thanks so much! I will definetely give it a look. Another super noob question, the steps for training the model are there but, is it there like a generated file...

if it's the same as darknet, it is probably the coco dataset.

maybe try adding `input_name_shape_dict={'image': [None, 416, 416, 3]}` on the parameters (use your model's width and height) ``` import coremltools coreml_model = coremltools.converters.keras.convert( './yolo.h5', input_names='input1', image_input_names='input1', output_names=['output1','output2','output3'], input_name_shape_dict={'image': [None, 416,...

after following the reply I replaced in model.py by: ``` #line 338 tf.log() -> tf.math.log() #lines 716 and 754 tf.sets.set_intersection() -> tf.sets.intersection() #lines 718 and 756 tf.sparse_tensor_to_dense() -> tf.sparse.to_dense() #line...