Refactor Keras Feature Notebooks (#1238)

* Refactored feature notebooks in Keras. Standardized function usage across notebooks. Updated model examples to use the ImageNet validation set as the representative dataset (except for the pruning and qat notebooks). Added keras post training quantization notebook --------- Co-authored-by: liord <[email protected]>
sony · Oct 8, 2024 · fb13d32 · fb13d32
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diff --git a/tutorials/notebooks/mct_features_notebooks/README.md b/tutorials/notebooks/mct_features_notebooks/README.md
@@ -10,12 +10,12 @@ These techniques are essential for further optimizing models and achieving super
 <details id="keras-ptq">
   <summary>Post-Training Quantization (PTQ)</summary>
 
-  | Tutorial                     | Included Features                                                                                   |
-  |------------------------------|-----------------------------------------------------------------------------------------------------|
-  | [MobileNetV2](../imx500_notebooks/keras/example_keras_mobilenetv2_for_imx500.ipynb)  | &#x2705; PTQ                                                                                        |
-  | [Mixed-Precision MobileNetV2](keras/example_keras_mobilenet_mixed_precision.ipynb) | &#x2705; PTQ <br/> &#x2705; Mixed-Precision                                                         |
-  | [Nanodet-Plus](../imx500_notebooks/keras/example_keras_nanodet_plus_for_imx500.ipynb)             | &#x2705; PTQ                                                                                        |
-  | [YoloV8-nano](keras/example_keras_yolov8n.ipynb)              | &#x2705; PTQ                                                                                        |
+  | Tutorial                                                                                   | Included Features                                                                                   |
+  |--------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------|
+  | [Basic Post-Training Quantization (PTQ)](keras/example_keras_post-training_quantization.ipynb)          | &#x2705; PTQ                                                                                        |
+  | [MobileNetV2](../imx500_notebooks/keras/example_keras_mobilenetv2_for_imx500.ipynb)        | &#x2705; PTQ                                                                                        |
+  | [Mixed-Precision MobileNetV2](keras/example_keras_mobilenet_mixed_precision.ipynb)         | &#x2705; PTQ <br/> &#x2705; Mixed-Precision                                                         |
+  | [Nanodet-Plus](../imx500_notebooks/keras/example_keras_nanodet_plus_for_imx500.ipynb)      | &#x2705; PTQ                                                                                        |
   | [EfficientDetLite0](../imx500_notebooks/keras/example_keras_effdet_lite0_for_imx500.ipynb) | &#x2705; PTQ <br/> &#x2705; [sony-custom-layers](https://github.com/sony/custom_layers) integration |
 
 </details>