Add mask target generator operator for Mask-RCNN

src/operator/contrib/mrcnn_target-inl.h

@@ -0,0 +1,132 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you 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.
+ */
+
+/*!
+ *  Copyright (c) 2019 by Contributors
+ * \file mrcnn_target-inl.h
+ * \brief Mask-RCNN target generator
+ * \author Serge Panev
+ */
+
+
+#ifndef MXNET_OPERATOR_CONTRIB_MRCNN_TARGET_INL_H_
+#define MXNET_OPERATOR_CONTRIB_MRCNN_TARGET_INL_H_
+
+#include <mxnet/operator.h>
+#include <vector>
+#include "../operator_common.h"
+#include "../mshadow_op.h"
+#include "../tensor/init_op.h"
+
+namespace mxnet {
+namespace op {
+
+namespace mrcnn_index {
+  enum ROIAlignOpInputs {kRoi, kGtMask, kMatches, kClasses};
+  enum ROIAlignOpOutputs {kMask, kMaskClasses};
+}  // namespace mrcnn_index
+
+struct MRCNNTargetParam : public dmlc::Parameter<MRCNNTargetParam> {
+  int num_rois;
+  int num_classes;
+  int mask_size;
+  int sample_ratio;
+
+  DMLC_DECLARE_PARAMETER(MRCNNTargetParam) {
+    DMLC_DECLARE_FIELD(num_rois)
+    .describe("Number of sampled RoIs.");
+    DMLC_DECLARE_FIELD(num_classes)
+    .describe("Number of classes.");
+    DMLC_DECLARE_FIELD(mask_size)
+    .describe("Size of the pooled masks.");
+    DMLC_DECLARE_FIELD(sample_ratio).set_default(2)
+    .describe("Sampling ratio of ROI align. Set to -1 to use adaptative size.");
+  }
+};
+
+inline bool MRCNNTargetShape(const NodeAttrs& attrs,
+                            std::vector<mxnet::TShape>* in_shape,
+                            std::vector<mxnet::TShape>* out_shape) {
+  using namespace mshadow;
+  const MRCNNTargetParam& param = nnvm::get<MRCNNTargetParam>(attrs.parsed);
+
+  CHECK_EQ(in_shape->size(), 4) << "Input:[rois, gt_masks, matches, cls_targets]";
+
+  // (B, N, 4)
+  mxnet::TShape tshape = in_shape->at(mrcnn_index::kRoi);
+  CHECK_EQ(tshape.ndim(), 3) << "rois should be a 2D tensor of shape [batch, rois, 4]";
+  CHECK_EQ(tshape[2], 4) << "rois should be a 2D tensor of shape [batch, rois, 4]";
+  auto batch_size = tshape[0];
+  auto num_rois = tshape[1];
+
+  // (B, M, H, W)
+  tshape = in_shape->at(mrcnn_index::kGtMask);
+  CHECK_EQ(tshape.ndim(), 4) << "gt_masks should be a 4D tensor";
+  CHECK_EQ(tshape[0], batch_size) << " batch size should be the same for all the inputs.";
+
+  // (B, N)
+  tshape = in_shape->at(mrcnn_index::kMatches);
+  CHECK_EQ(tshape.ndim(), 2) << "matches should be a 2D tensor";
+  CHECK_EQ(tshape[0], batch_size) << " batch size should be the same for all the inputs.";
+
+  // (B, N)
+  tshape = in_shape->at(mrcnn_index::kClasses);
+  CHECK_EQ(tshape.ndim(), 2) << "matches should be a 2D tensor";
+  CHECK_EQ(tshape[0], batch_size) << " batch size should be the same for all the inputs.";
+
+  // out: 2 * (B, N, C, MS, MS)
+  auto oshape = Shape5(batch_size, num_rois, param.num_classes, param.mask_size, param.mask_size);
+  out_shape->clear();
+  out_shape->push_back(oshape);
+  out_shape->push_back(oshape);
+  return true;
+}
+
+inline bool MRCNNTargetType(const NodeAttrs& attrs,
+                           std::vector<int>* in_type,
+                           std::vector<int>* out_type) {
+  CHECK_EQ(in_type->size(), 4);
+  int dtype = (*in_type)[1];
+  CHECK_NE(dtype, -1) << "Input must have specified type";
+
+  out_type->clear();
+  out_type->push_back(dtype);
+  out_type->push_back(dtype);
+  return true;
+}
+
+template<typename xpu>
+void MRCNNTargetRun(const MRCNNTargetParam& param, const std::vector<TBlob> &inputs,
+                    const std::vector<TBlob> &outputs, mshadow::Stream<xpu> *s);
+
+template<typename xpu>
+void MRCNNTargetCompute(const nnvm::NodeAttrs& attrs,
+                const OpContext &ctx,
+                const std::vector<TBlob> &inputs,
+                const std::vector<OpReqType> &req,
+                const std::vector<TBlob> &outputs) {
+  auto s = ctx.get_stream<xpu>();
+  const auto& p = dmlc::get<MRCNNTargetParam>(attrs.parsed);
+  MRCNNTargetRun<xpu>(p, inputs, outputs, s);
+}
+
+}  // namespace op
+}  // namespace mxnet
+
+#endif  // MXNET_OPERATOR_CONTRIB_MRCNN_TARGET_INL_H_