model_input.py

# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
#
# 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
#
#     http://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.

from __future__ import absolute_import
from __future__ import print_function
from __future__ import division

from collections import OrderedDict

from paddle import fluid

__all__ = ['create_feed']

# yapf: disable
feed_var_def = [
    {'name': 'im_info',       'shape': [3],  'dtype': 'float32', 'lod_level': 0},
    {'name': 'im_id',         'shape': [1],  'dtype': 'int32',   'lod_level': 0},
    {'name': 'gt_box',        'shape': [4],  'dtype': 'float32', 'lod_level': 1},
    {'name': 'gt_label',      'shape': [1],  'dtype': 'int32',   'lod_level': 1},
    {'name': 'is_crowd',      'shape': [1],  'dtype': 'int32',   'lod_level': 1},
    {'name': 'gt_mask',       'shape': [2],  'dtype': 'float32', 'lod_level': 3},
    {'name': 'is_difficult',  'shape': [1],  'dtype': 'int32',   'lod_level': 1},
    {'name': 'gt_score',      'shape': [1],  'dtype': 'float32', 'lod_level': 0},
    {'name': 'im_shape',      'shape': [3],  'dtype': 'float32', 'lod_level': 0},
    {'name': 'im_size',       'shape': [2],  'dtype': 'int32',   'lod_level': 0},
]
# yapf: enable


def create_feed(feed, iterable=False):
    image_shape = feed.image_shape
    feed_var_map = {var['name']: var for var in feed_var_def}
    feed_var_map['image'] = {
        'name': 'image',
        'shape': image_shape,
        'dtype': 'float32',
        'lod_level': 0
    }

    # tensor padding with 0 is used instead of LoD tensor when 
    # num_max_boxes is set
    if getattr(feed, 'num_max_boxes', None) is not None:
        feed_var_map['gt_label']['shape'] = [feed.num_max_boxes]
        feed_var_map['gt_score']['shape'] = [feed.num_max_boxes]
        feed_var_map['gt_box']['shape'] = [feed.num_max_boxes, 4]
        feed_var_map['is_difficult']['shape'] = [feed.num_max_boxes]
        feed_var_map['gt_label']['lod_level'] = 0
        feed_var_map['gt_score']['lod_level'] = 0
        feed_var_map['gt_box']['lod_level'] = 0
        feed_var_map['is_difficult']['lod_level'] = 0

    feed_vars = OrderedDict([(key, fluid.layers.data(
        name=feed_var_map[key]['name'],
        shape=feed_var_map[key]['shape'],
        dtype=feed_var_map[key]['dtype'],
        lod_level=feed_var_map[key]['lod_level'])) for key in feed.fields])

    loader = fluid.io.DataLoader.from_generator(
        feed_list=list(feed_vars.values()),
        capacity=64,
        use_double_buffer=True,
        iterable=iterable)
    return loader, feed_vars