71 lines
2.3 KiB
Python
71 lines
2.3 KiB
Python
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import numpy as np
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__all__ = ['eval_cls_run']
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import logging
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FORMAT = '%(asctime)s-%(levelname)s: %(message)s'
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logging.basicConfig(level=logging.INFO, format=FORMAT)
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logger = logging.getLogger(__name__)
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def eval_cls_run(exe, eval_info_dict):
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"""
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Run evaluation program, return program outputs.
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"""
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total_sample_num = 0
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total_acc_num = 0
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total_batch_num = 0
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for data in eval_info_dict['reader']():
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img_num = len(data)
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img_list = []
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label_list = []
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for ino in range(img_num):
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img_list.append(data[ino][0])
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label_list.append(data[ino][1])
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img_list = np.concatenate(img_list, axis=0)
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outs = exe.run(eval_info_dict['program'], \
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feed={'image': img_list}, \
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fetch_list=eval_info_dict['fetch_varname_list'], \
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return_numpy=False)
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softmax_outs = np.array(outs[1])
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if len(softmax_outs.shape) != 1:
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softmax_outs = np.array(outs[0])
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acc, acc_num = cal_cls_acc(softmax_outs, label_list)
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total_acc_num += acc_num
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total_sample_num += len(label_list)
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# logger.info("eval batch id: {}, acc: {}".format(total_batch_num, acc))
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total_batch_num += 1
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avg_acc = total_acc_num * 1.0 / total_sample_num
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metrics = {'avg_acc': avg_acc, "total_acc_num": total_acc_num, \
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"total_sample_num": total_sample_num}
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return metrics
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def cal_cls_acc(preds, labels):
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acc_num = 0
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for pred, label in zip(preds, labels):
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if pred == label:
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acc_num += 1
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return acc_num / len(preds), acc_num
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