Comments (4)
bendangnuksung
commented on June 11, 2024
1
Glad it worked. Do let me know if you find a workaround with opencv load model.
As for now closing the issue.
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bendangnuksung
commented on June 11, 2024
Did you replace your custom config in main.py, current line no: 103. i.e 'config = get_config()' ?
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lunasdejavu
commented on June 11, 2024
ya, I used config = ShapesConfig(2) since the number of my class is only 1 +background
I am keeping trying now,
btw what is the VESRION_NUMBER means in user_config.py?
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lunasdejavu
commented on June 11, 2024
the frozen_graph.pb can be saved now
but too bad I can't read it by opencv 4.1 cv::dnn::readNet() :(
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Related Issues (20)
- Frozen graph generates difference results compared to the original model HOT 2
- there is not any files in the folder about serving_model/1/variables. HOT 12
- Which .pb file should I use? The one in serving model or the one in frozen model? HOT 2
- How to use saved_model.pb in Tensorflow Model Server？ HOT 8
- Can not convert to tflite (UnicodeDecodeError: 'utf-8' codec can't decode byte 0xbb in position 3: invalid start byte) HOT 3
- Converting frozen graph in mvNCCompile
- output_names=[out.op.name for out in model.outputs][:4] should be modified to get the 5 loss nodes HOT 2
- What should the inputs and outputs of the SavedModel SignatureDef look like? HOT 2
- About How to predict by tensorflow serving. HOT 2
- How can I read input and output node from frozen inference model (.pb)? HOT 2
- Inference speed really slow! HOT 2
- Rest Api Error
- { "error": "Malformed request: GET /v1/models/mask:predict" } HOT 1
- Unable to convert to tensorflow serving HOT 2
- Deployment on serving failed
- Error help pleas
- sending your input data instances as a JSON object to deployed model HOT 3
- gRPC error HOT 2
- error while converting keras model to tensorflow saved model format
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