Comments (10)
Are there any error messages in the Xcode debug panel?
from yolo-coreml-mpsnngraph.
Hollance, no, there is no error message in the Xcode debug panel. I was thinking the preprocessing step might be an issue. For example the RGB channel order, the pixel value normalization. Can you share any insight that I need to pay more attention to when converting the model?
Thank you very much
from yolo-coreml-mpsnngraph.
If my model also doesn't work on your iPhone 6 then it sounds like an issue in CoreML, since the model works fine on the iPad Pro.
Does the MPSNNGraph version work on your iPhone?
One thing to try is to pass the usesCPUOnly option (it might be spelled differently) to CoreML when it is making the prediction.
Also, just to make sure: are you sure your input image actually contains any objects for the model to recognize?
from yolo-coreml-mpsnngraph.
Hi, hollance,
I haven't tried MPSNNGraph version. I do test scene with objects covered, for example, cars, bikes, human, etc.
My xcode is xcode 9 beta 5, but I assume beta 4 or beta 5 will not be an issue. I will try enable the usesCPUOnly option and will update my results
from yolo-coreml-mpsnngraph.
I got the same issue and I checked the keras model after converting then the model was not working at this point. No bounding-box until you change the confident score threshold = 0.001xxx. Could you check your model ?
from yolo-coreml-mpsnngraph.
@oishi89 Where/how have you checked that the model isn't working?
I have no iPhone 6 to test this on but the code works fine on the 6s, 7, and iPad Pro.
If the model does not work in Keras, then perhaps the inputs you're giving it are in the wrong format.
from yolo-coreml-mpsnngraph.
The input is trained model with my own data using tiny-yolo-voc.cfg. I tested for making sure it works properly before conversion to Keras. I ran the yad2k.py with output is a file.h5 at this point I also ran the test_yolo.py then no object was detected. Do you have any idea please help
from yolo-coreml-mpsnngraph.
It's probably something in yad2k.py then. Note that I modified yad2k.py to make it work with Keras 1.2, since at the time coremltools did not support Keras 2 yet. You might have better luck with the official version of YAD2K.
from yolo-coreml-mpsnngraph.
I have tried the official version already and both have the same result. I'm very new with Python and Machine learning. If you have time please review the yad2k.py
from yolo-coreml-mpsnngraph.
Unfortunately I don't have the time to debug your model for free. But my services are for hire if you're willing to pay my hourly rate: http://machinethink.net/hire/
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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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