diff --git a/aidge_backend_opencv/unit_tests/test_tensor.py b/aidge_backend_opencv/unit_tests/test_tensor.py
index a47e9a9812b45f71a3a859ddb04a7ce586f0500a..a3cf628588dcaa9ac479f6a61ced9dad624dc75c 100644
--- a/aidge_backend_opencv/unit_tests/test_tensor.py
+++ b/aidge_backend_opencv/unit_tests/test_tensor.py
@@ -19,7 +19,7 @@ class test_tensor(unittest.TestCase):
# np_array = np.arange(9).reshape(1,1,3,3)
# # Numpy -> Tensor
# t = aidge_core.Tensor(np_array)
- # self.assertEqual(t.dtype(), aidge_core.DataType.Int32)
+ # self.assertEqual(t.dtype(), aidge_core.dtype.int32)
# for i_t, i_n in zip(t, np_array.flatten()):
# self.assertTrue(i_t == i_n)
# for i,j in zip(t.dims(), np_array.shape):
@@ -41,7 +41,7 @@ class test_tensor(unittest.TestCase):
# np_array = np.random.rand(1, 1, 3, 3).astype(np.float32)
# # Numpy -> Tensor
# t = aidge_core.Tensor(np_array)
- # self.assertEqual(t.dtype(), aidge_core.DataType.Float32)
+ # self.assertEqual(t.dtype(), aidge_core.dtype.float32)
# for i_t, i_n in zip(t, np_array.flatten()):
# self.assertTrue(i_t == i_n) # TODO : May need to change this to a difference
# for i,j in zip(t.dims(), np_array.shape):
diff --git a/include/aidge/backend/opencv/data/TensorImpl.hpp b/include/aidge/backend/opencv/data/TensorImpl.hpp
index 84a5e54540794ce432e518e43d5ed13ea80db082..4b548d2157219a3172b947013e4e53faee65d31a 100644
--- a/include/aidge/backend/opencv/data/TensorImpl.hpp
+++ b/include/aidge/backend/opencv/data/TensorImpl.hpp
@@ -31,7 +31,7 @@ public:
virtual void setCvMat(const cv::Mat& mat ) = 0;
};
-template <class T>
+template <class T>
class TensorImpl_opencv : public TensorImpl, public TensorImpl_opencv_ {
private:
// Stores the cv::Mat
@@ -44,7 +44,7 @@ public:
static constexpr const char *Backend = "opencv";
TensorImpl_opencv() = delete;
- TensorImpl_opencv(DeviceIdx_t device, std::vector<DimSize_t> dims)
+ TensorImpl_opencv(DeviceIdx_t device, std::vector<DimSize_t> dims)
: TensorImpl(Backend, device, dims)
{
mDims = dims;
@@ -82,14 +82,20 @@ public:
// native interface
const cv::Mat & data() const override { return mData; }
+ inline std::size_t capacity() const noexcept override { return (mData.total() * mData.channels()); }
+
inline std::size_t scalarSize() const noexcept override final { return sizeof(T); }
+ void zeros() override final {
+ mData.setTo(cv::Scalar::all(T(0)));
+ }
+
void copy(const void *src, NbElts_t length, NbElts_t offset = 0) override final {
const T* srcT = static_cast<const T *>(src);
T* dstT = static_cast<T *>(rawPtr(offset));
- AIDGE_ASSERT(length <= (mData.total() * mData.channels()) || length <= mNbElts, "copy length is above capacity");
- AIDGE_ASSERT(dstT < srcT || dstT >= srcT + length, "overlapping copy is not supported");
+ AIDGE_ASSERT(length <= (mData.total() * mData.channels()) || length <= mNbElts, "TensorImpl_opencv<{}>::copy(): copy length ({}) is above capacity ({})", typeid(T).name(), length, mNbElts);
+ AIDGE_ASSERT(dstT < srcT || dstT >= srcT + length, "TensorImpl_opencv<{}>::copy(): overlapping copy is not supported", typeid(T).name());
std::copy(srcT, srcT + length, dstT);
}
@@ -98,9 +104,9 @@ public:
if (length == 0) {
return;
}
-
+
T* dstT = static_cast<T *>(rawPtr(offset));
- AIDGE_ASSERT(length <= (mData.total() * mData.channels()) || length <= mNbElts, "copy length is above capacity");
+ AIDGE_ASSERT(length <= (mData.total() * mData.channels()) || length <= mNbElts, "TensorImpl_opencv<{}>::copyCast(): copy length ({}) is above capacity ({})", typeid(T).name(), length, mNbElts);
switch (srcDt)
{
case DataType::Float64:
@@ -148,15 +154,15 @@ public:
dstT);
break;
default:
- AIDGE_THROW_OR_ABORT(std::runtime_error, "Unsupported data type.");
+ AIDGE_THROW_OR_ABORT(std::runtime_error, "TensorImpl_opencv<{}>::copyCast(): unsupported data type {}.", typeid(T).name(), srcDt);
break;
}
}
void copyFromDevice(const void *src, const std::pair<std::string, DeviceIdx_t>& device, NbElts_t length, NbElts_t offset = 0) override final {
- AIDGE_ASSERT(device.first == Backend, "backend must match");
- AIDGE_ASSERT(device.second == 0, "device cannot be != 0 for CPU backend");
+ AIDGE_ASSERT(device.first == Backend, "TensorImpl_opencv<{}>::copyFromDevice(): backend must match", typeid(T).name());
+ AIDGE_ASSERT(device.second == 0, "TensorImpl_opencv<{}>::copyFromDevice(): device ({}) cannot be != 0 for CPU backend", typeid(T).name(), device.second);
copy(src, length, offset);
}
@@ -166,7 +172,7 @@ public:
void copyToHost(void *dst, NbElts_t length, NbElts_t offset = 0) const override final {
const T* src = static_cast<const T*>(rawPtr(offset));
- AIDGE_ASSERT(length <= (mData.total() * mData.channels()) || length <= mNbElts, "copy length is above capacity");
+ AIDGE_ASSERT(length <= (mData.total() * mData.channels()) || length <= mNbElts, "TensorImpl_opencv<{}>::copyToHost(): copy length ({}) is above capacity ({})", typeid(T).name(), length, mNbElts);
std::copy(src, src + length, static_cast<T *>(dst));
}
@@ -176,7 +182,7 @@ public:
};
const void *rawPtr(NbElts_t offset = 0) const override final {
- AIDGE_ASSERT((mData.total() * mData.channels()) >= mNbElts, "accessing uninitialized const rawPtr");
+ AIDGE_ASSERT((mData.total() * mData.channels()) >= mNbElts, "TensorImpl_opencv<{}>::rawPtr(): accessing uninitialized const rawPtr", typeid(T).name());
return (mData.ptr<T>() + offset);
};
@@ -186,13 +192,13 @@ public:
};
const void *hostPtr(NbElts_t offset = 0) const override {
- AIDGE_ASSERT((mData.total() * mData.channels()) >= mNbElts, "accessing uninitialized const hostPtr");
- AIDGE_ASSERT(mData.isContinuous(), "CV Matrix not continuous");
+ AIDGE_ASSERT((mData.total() * mData.channels()) >= mNbElts, "TensorImpl_opencv<{}>::hostPtr(): accessing uninitialized const hostPtr", typeid(T).name());
+ AIDGE_ASSERT(mData.isContinuous(), "TensorImpl_opencv<{}>::hostPtr(): CV Matrix not continuous", typeid(T).name());
return (mData.ptr<T>() + offset);
};
void setCvMat(const cv::Mat& mat) override {mData=mat;}
-
+
virtual ~TensorImpl_opencv() = default;
@@ -201,7 +207,7 @@ private:
void lazyInit() {
if ((mData.total() * mData.channels()) < mNbElts) {
// Need more data, a re-allocation will occur
- AIDGE_ASSERT(mData.empty() , "trying to enlarge non-owned data");
+ AIDGE_ASSERT(mData.empty(), "TensorImpl_opencv<{}>: trying to enlarge non-owned data", typeid(T).name());
if (mDims.size() < 3) {
mData = cv::Mat(((mDims.size() > 1) ? static_cast<int>(mDims[0])
diff --git a/version.txt b/version.txt
index 4e379d2bfeab6461d0455bf5bbb8792845d9bbea..bcab45af15a0f1b0166daf8cbf18b17cd8649277 100644
--- a/version.txt
+++ b/version.txt
@@ -1 +1 @@
-0.0.2
+0.0.3