fix yolo_box bug (#2034)

* fix yolo_box bug, test=develop

* fix test bug for yolo_box, test=develop

lite/backends/arm/math/yolo_box.cc

@@ -108,7 +108,7 @@ void yolobox(lite::Tensor* X,
   auto anchors_data = anchors.data();
 
   const float* X_data = X->data<float>();
-  float* ImgSize_data = ImgSize->mutable_data<float>();
+  int* ImgSize_data = ImgSize->mutable_data<int>();
 
   float* Boxes_data = Boxes->mutable_data<float>();
 
@@ -116,8 +116,8 @@ void yolobox(lite::Tensor* X,
 
   float box[4];
   for (int i = 0; i < n; i++) {
-    int img_height = static_cast<int>(ImgSize_data[2 * i]);
-    int img_width = static_cast<int>(ImgSize_data[2 * i + 1]);
+    int img_height = ImgSize_data[2 * i];
+    int img_width = ImgSize_data[2 * i + 1];
 
     for (int j = 0; j < an_num; j++) {
       for (int k = 0; k < h; k++) {

lite/operators/yolo_box_op.cc

@@ -31,6 +31,19 @@ bool YoloBoxOp::CheckShape() const {
   CHECK_OR_FALSE(ImgSize);
   CHECK_OR_FALSE(Boxes);
   CHECK_OR_FALSE(Scores);
+
+  auto dim_x = X->dims();
+  auto dim_imgsize = ImgSize->dims();
+  std::vector<int> anchors = param_.anchors;
+  int anchor_num = anchors.size() / 2;
+  auto class_num = param_.class_num;
+  CHECK_OR_FALSE(dim_x.size() == 4);
+  CHECK_OR_FALSE(dim_x[1] == anchor_num * (5 + class_num));
+  CHECK_OR_FALSE(dim_imgsize[0] == dim_x[0]);
+  CHECK_OR_FALSE(dim_imgsize[1] == 2);
+  CHECK_OR_FALSE(anchors.size() > 0 && anchors.size() % 2 == 0);
+  CHECK_OR_FALSE(class_num > 0);
+  return true;
 }
 
 bool YoloBoxOp::InferShape() const {

lite/tests/kernels/yolo_box_compute_test.cc

@@ -101,7 +101,7 @@ class YoloBoxComputeTester : public arena::TestCase {
   float conf_thresh_ = 0.f;
   int downsample_ratio_ = 0;
 
-  DDim _dims0_{{1, 2, 2, 1}};
+  DDim _dims0_{{1, 255, 13, 13}};
   DDim _dims1_{{1, 2}};
 
  public:
@@ -115,7 +115,10 @@ class YoloBoxComputeTester : public arena::TestCase {
         anchors_(anchors),
         class_num_(class_num),
         conf_thresh_(conf_thresh),
-        downsample_ratio_(downsample_ratio) {}
+        downsample_ratio_(downsample_ratio) {
+    int anchor_num = anchors_.size() / 2;
+    _dims0_[1] = anchor_num * (5 + class_num);
+  }
 
   void RunBaseline(Scope* scope) override {
     const lite::Tensor* X = scope->FindTensor(input0_);
@@ -149,14 +152,14 @@ class YoloBoxComputeTester : public arena::TestCase {
 
     auto anchors_data = anchors.data();
     const float* in_data = in->data<float>();
-    const float* imgsize_data = imgsize->data<float>();
+    const int* imgsize_data = imgsize->data<int>();
     float* boxes_data = boxes->mutable_data<float>();
     float* scores_data = scores->mutable_data<float>();
 
     float box[4];
     for (int i = 0; i < n; i++) {
-      int img_height = static_cast<int>(imgsize_data[2 * i]);
-      int img_width = static_cast<int>(imgsize_data[2 * i + 1]);
+      int img_height = imgsize_data[2 * i];
+      int img_width = imgsize_data[2 * i + 1];
       for (int j = 0; j < an_num; j++) {
         for (int k = 0; k < h; k++) {
           for (int l = 0; l < w; l++) {
@@ -218,7 +221,7 @@ class YoloBoxComputeTester : public arena::TestCase {
     }
     std::vector<int> data1(_dims1_.production());
     for (int i = 0; i < _dims1_.production(); i++) {
-      data1[i] = i + 8;
+      data1[i] = 608;
     }
     SetCommonTensor(input0_, _dims0_, data0.data());
     SetCommonTensor(input1_, _dims1_, data1.data());
@@ -227,10 +230,9 @@ class YoloBoxComputeTester : public arena::TestCase {
 
 void test_yolobox(Place place) {
   for (int class_num : {1, 2, 3, 4}) {
-    for (float conf_thresh : {0.5, 0.2, 0.7}) {
-      for (int downsample_ratio : {1, 2, 3}) {
-        std::vector<int> anchor({1, 2, 3, 4});
-
+    for (float conf_thresh : {0.01, 0.2, 0.7}) {
+      for (int downsample_ratio : {16, 32}) {
+        std::vector<int> anchor({10, 13, 16, 30});
         std::unique_ptr<arena::TestCase> tester(new YoloBoxComputeTester(
             place, "def", anchor, class_num, conf_thresh, downsample_ratio));
         arena::Arena arena(std::move(tester), place, 2e-5);