| # Copyright 2019 Google LLC |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # https://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| |
| """Python wrapper for ImprintingEngine.""" |
| |
| import edgetpu.swig.edgetpu_cpp_wrapper |
| |
| |
| class ImprintingEngine(edgetpu.swig.edgetpu_cpp_wrapper.ImprintingEngine): |
| """Python wrapper for Imprinting Engine.""" |
| |
| def TrainAll(self, input_data): |
| """Trains model given input of all categories. |
| |
| Args: |
| input_data: {string : list of numpy.array}, map between new |
| category's label and training data. |
| |
| Returns: |
| map between output id and label {int, string}. |
| """ |
| ret = {} |
| for category, tensors in input_data.items(): |
| ret[self.Train(tensors)] = category |
| return ret |