Comments (5)
Are you using Python 2?
from yolo-coreml-mpsnngraph.
no, python 3, like the command in the readme says:
python3 yad2k.py -p ../tiny-yolo-voc.cfg ../tiny-yolo-voc.weights model_data/tiny-yolo-voc.h5
from yolo-coreml-mpsnngraph.
I suggest using the latest version of YAD2K (it's on GitHub somewhere). I only included it in this repo because coremltools needed Keras 1.x at the time.
from yolo-coreml-mpsnngraph.
with that, I get
Traceback (most recent call last):
File "./yad2k.py", line 270, in <module>
_main(parser.parse_args())
File "./yad2k.py", line 156, in _main
buffer=weights_file.read(weights_size * 4))
TypeError: buffer is too small for requested array
:(
from yolo-coreml-mpsnngraph.
Ah, the fun of converting between different deep learning packages that are constantly changing... ;-)
Unfortunately, I don't have time right now to investigate this -- and the script works for the weights that come with this repo, just not for custom models, apparently.
from yolo-coreml-mpsnngraph.
Related Issues (20)
- Why is the feature set 255x13x13 ? HOT 3
- Unable to desearilize object Validation error HOT 2
- it delays HOT 1
- Performance HOT 9
- scaleFit instead of scaleFill HOT 1
- TypeError: __init__() got an unexpected keyword argument 'dtype' HOT 3
- Performance decrease HOT 4
- UIview and adding shapes HOT 3
- error when run " python coreml.py" HOT 5
- Shape of the converted model is wrong HOT 11
- Speed on A11 vs A12 HOT 1
- AttributeError: module 'tensorflow' has no attribute 'concat_v2' HOT 1
- MLMultiArray datatype Flot32 issue HOT 9
- __init__() got an unexpected keyword argument 'dtype' HOT 1
- Converting this repo to support Yolov5 HOT 1
- Error trying to convert model to CoreML HOT 4
- Error converting from h5 to Core ML HOT 1
- Cannot find 'YOLOv3' in scope HOT 1
- assert(features[0].count == 255 * 13 * 13) crash HOT 1
- Get multiple outputs from MPSNNGraph HOT 1
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