Comments (1)
I have not been training this models, just convert weights, look at original paper.
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Related Issues (20)
- The drop connect rate (aka survival rate) is incorrect HOT 2
- Top 1 AND Top 5 ACCURACIES
- ValueError: Unknown layer: FixedDropout HOT 6
- Depthwise separable convolution for _expand_conv
- if _IMAGENET_MEAN is None:
- ValueError: Layer #0 (named "efficientnetb0" in the current model) was found to correspond to layer efficientnet-b0 in the save file. However the new layer efficientnetb0 expects 312 weights, but the saved weights have 309 elements. HOT 1
- How to take multiple output from pretrained network
- ValueError: rate must be a scalar tensor or a float in the range [0, 1), got 1 HOT 1
- how can i change backbone from resnet to efficientnet HOT 6
- Some question about the grid search
- Invalid argument: Incompatible shapes: [131072] vs. [262144] HOT 1
- The input must have 3 channels, I need 1 channel HOT 2
- I have malimg dataset and i want to apply EfficientNet model, can u help to do that ? be
- Efficientnet model not saving completely after training
- ModuleNotFoundError: No module named 'keras_applications' HOT 2
- Difference of EfficientNetB0 between this model and Official Tensorflow
- Bad prediction result using EfficientNet
- Remove `FixedDropout`
- Pickling errors for `preprocess_input` due to `functools.wraps`
- How to create a new network that has the same backbone but two detection heads: one with the imagenet weights and the second head with the new custom classes. I want to predict both imagenet and custom classes with the model
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