Revision e1467a79dc6580ae009d827b5e6f274faff3b339 authored by liqunfu on 27 March 2020, 21:42:04 UTC, committed by GitHub on 27 March 2020, 21:42:04 UTC
support Pooling ops with Sequence axis
README.md
# CNTK Examples: Image/FeatureExtraction
## Overview
|Data: |A small toy data set of food items in a fridge (grocery).
|:---------|:---
|Purpose |Demonstrate how to evaluate and write out different layers of a trained model using Python.
|Network |Pre-trained ResNet_18 model.
|Training |None, only evaluation of different layers of the model.
## Running the example
### Getting the data
We use the `grocery` toy data set ([Examples/Image/DataSets/Grocery](../DataSets/Grocery)) and a pre-trained ResNet_18 model [PretrainedModels/ResNet18_ImageNet_CNTK.model](../../../PretrainedModels). To download both run
`python install_data_and_model.py`
### Details
Run `python FeatureExtraction.py` to generate the output of a specific layer. Please refer to the comments in the Python code directly for how to choose different layers for evaluation.
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