# Copyright (c) 2020 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. import paddle from paddle import _C_ops from paddle import in_dynamic_mode from paddle.common_ops_import import Variable, LayerHelper, check_variable_and_dtype, check_type, check_dtype @paddle.jit.not_to_static def roi_align(input, rois, output_size, spatial_scale=1.0, sampling_ratio=-1, rois_num=None, aligned=True, name=None): check_type(output_size, 'output_size', (int, tuple), 'roi_align') if isinstance(output_size, int): output_size = (output_size, output_size) pooled_height, pooled_width = output_size if in_dynamic_mode(): assert rois_num is not None, "rois_num should not be None in dygraph mode." align_out = _C_ops.roi_align( input, rois, rois_num, "pooled_height", pooled_height, "pooled_width", pooled_width, "spatial_scale", spatial_scale, "sampling_ratio", sampling_ratio, "aligned", aligned) return align_out else: check_variable_and_dtype(input, 'input', ['float32', 'float64'], 'roi_align') check_variable_and_dtype(rois, 'rois', ['float32', 'float64'], 'roi_align') helper = LayerHelper('roi_align', **locals()) dtype = helper.input_dtype() align_out = helper.create_variable_for_type_inference(dtype) inputs = { "X": input, "ROIs": rois, } if rois_num is not None: inputs['RoisNum'] = rois_num helper.append_op( type="roi_align", inputs=inputs, outputs={"Out": align_out}, attrs={ "pooled_height": pooled_height, "pooled_width": pooled_width, "spatial_scale": spatial_scale, "sampling_ratio": sampling_ratio, "aligned": aligned, }) return align_out class ROIAlign(object): def __init__(self, pooled_height, pooled_width, spatial_scale, sampling_ratio, rois_num): self.roialign_layer_attrs = { "pooled_height": pooled_height, "pooled_width": pooled_width, "spatial_scale": spatial_scale, 'sampling_ratio': sampling_ratio, 'rois_num': rois_num, } def __call__(self, x0, x1): out = roi_align(input=x0, rois=x1, **self.roialign_layer_attrs) return out