Change tensorimpl opencv `future_std::span<cv::Mat>` to `cv::Mat`

Why ? TensorImpl_opencv attribute future_std::span<cv::Mat> mData; is not relevant.

MR Content :

• Change to cv::Mat mData;
• Adapt functions of TensorImpl_opencv
• Adapt tests
• Change the opencv::imread flag from IMREAD_COLOR to IMREAD_UNCHANGED and adpat tests. The flag IMREAD_COLOR was always loading 3 channels, even for grayscale images while IMREAD_UNCHANGED adapts to the input file. See : https://docs.opencv.org/4.x/d8/d6a/group__imgcodecs__flags.html#ga61d9b0126a3e57d9277ac48327799c80

---

Implement the solution presented in issue #3 (closed).

• Change the constructor of TensorImpl to take the dimensions of the tensor as argument instead of the number of elements. For tensorImpl_opencv :
• Add mDims attribute in the class to use in Lazy_init (Instanciation of cv::Mat)
• Override the resize function from TensorImpl.hpp to update mDims

include/aidge/backend/opencv/data/TensorImpl.hpp

@@ -27,35 +27,38 @@ namespace Aidge {
 
 class TensorImpl_opencv_ {
 public:
-    virtual const cv::Mat& getCvMat() const = 0;
+    virtual const cv::Mat& data() const = 0;
     virtual void setCvMat(const cv::Mat& mat ) = 0;
 };
 
-template <class T> class TensorImpl_opencv : public TensorImpl, public TensorImpl_opencv_ {
+template <class T> 
+class TensorImpl_opencv : public TensorImpl, public TensorImpl_opencv_ {
 private:
-    const Tensor &mTensor; // Impl needs to access Tensor information, but is not
-                           // supposed to change it!
+    // Stores the cv::Mat
+    cv::Mat mData;
 
-    future_std::span<cv::Mat> mData;
-
-    std::unique_ptr<cv::Mat> mDataOwner = std::unique_ptr<cv::Mat>(new cv::Mat(0, 0, detail::CV_C1_CPP_v<T>));
+protected:
+    std::vector<DimSize_t> mDims;
 
 public:
     static constexpr const char *Backend = "opencv";
 
-    TensorImpl_opencv(const Tensor &tensor)
-      : TensorImpl(Backend), mTensor(tensor) {}
+    TensorImpl_opencv() = delete;
+    TensorImpl_opencv(DeviceIdx_t device, std::vector<DimSize_t> dims) 
+    : TensorImpl(Backend, device, dims)
+    {
+        mDims = dims;
+    }
 
     bool operator==(const TensorImpl &otherImpl) const override final {
         // Create iterators for both matrices
-        cv::MatConstIterator_<T> it1 = mDataOwner->begin<T>();
-        const future_std::span<cv::Mat> tmp = reinterpret_cast<const TensorImpl_opencv<T> &>(otherImpl).data();
+        cv::MatConstIterator_<T> it1 = mData.begin<T>();
 
-        const cv::Mat otherData = *(tmp.data());
+        const cv::Mat & otherData = reinterpret_cast<const TensorImpl_opencv<T> &>(otherImpl).data();
         cv::MatConstIterator_<T> it2 = otherData.begin<T>();
 
         // Iterate over the elements and compare them
-        for (; it1 != mDataOwner->end<T>(); ++it1, ++it2) {
+        for (; it1 != mData.end<T>(); ++it1, ++it2) {
             if (*it1 != *it2) {
                 return false;
             }
@@ -63,157 +66,160 @@ public:
         return true;
     }
 
-    static std::unique_ptr<TensorImpl_opencv> create(const Tensor &tensor) {
-        return std::make_unique<TensorImpl_opencv<T>>(tensor);
+    static std::unique_ptr<TensorImpl_opencv> create(DeviceIdx_t device, std::vector<DimSize_t> dims) {
+        return std::make_unique<TensorImpl_opencv<T>>(device, dims);
+    }
+
+    void resize(std::vector<DimSize_t> dims) override{
+        mDims = dims;
+        size_t product = 1;
+        for (size_t num : dims) {
+            product *= num;
+        }
+        mNbElts = product;
     }
 
     // native interface
-    const future_std::span<cv::Mat> data() const { return mData; }
+    const cv::Mat & data() const override { return mData; }
 
-    inline std::size_t scalarSize() const override { return sizeof(T); }
+    inline std::size_t scalarSize() const noexcept override final { return sizeof(T); }
 
-    inline std::size_t size() const override { return mData.size(); }
+    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));
 
-    void setDevice(DeviceIdx_t device) override {
-        AIDGE_ASSERT(device == 0, "device cannot be != 0 for Opencv backend");
-    }
+        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");
+        std::copy(srcT, srcT + length, dstT);
 
-    void copy(const void *src, NbElts_t length, NbElts_t offset = 0) override {
-        AIDGE_ASSERT(length <= mData.size() || length <= mTensor.size(), "copy length is above capacity");
-        std::copy(static_cast<const T *>(src), static_cast<const T *>(src) + length,
-                  static_cast<T *>(rawPtr()) + offset);
     }
 
-    void copyCast(const void *src, NbElts_t length, const DataType srcDt) override {
+    void copyCast(const void *src, const DataType srcDt, NbElts_t length, NbElts_t offset = 0) override final{
         if (length == 0) {
             return;
         }
-
-        AIDGE_ASSERT(length <= mData.size() || length <= mTensor.size(), "copy length is above capacity");
-        switch (srcDt) {
+        
+        T* dstT = static_cast<T *>(rawPtr(offset));
+        AIDGE_ASSERT(length <= (mData.total() * mData.channels()) || length <= mNbElts, "copy length is above capacity");
+        switch (srcDt)
+        {
             case DataType::Float64:
                 std::copy(static_cast<const double*>(src), static_cast<const double*>(src) + length,
-                    static_cast<T *>(rawPtr()));
+                        dstT);
                 break;
             case DataType::Float32:
                 std::copy(static_cast<const float*>(src), static_cast<const float*>(src) + length,
-                    static_cast<T *>(rawPtr()));
+                        dstT);
                 break;
             case DataType::Float16:
                 std::copy(static_cast<const half_float::half*>(src), static_cast<const half_float::half*>(src) + length,
-                    static_cast<T *>(rawPtr()));
+                        dstT);
                 break;
             case DataType::Int64:
                 std::copy(static_cast<const int64_t*>(src), static_cast<const int64_t*>(src) + length,
-                    static_cast<T *>(rawPtr()));
+                        dstT);
                 break;
             case DataType::UInt64:
                 std::copy(static_cast<const uint64_t*>(src), static_cast<const uint64_t*>(src) + length,
-                    static_cast<T *>(rawPtr()));
+                        dstT);
                 break;
             case DataType::Int32:
                 std::copy(static_cast<const int32_t*>(src), static_cast<const int32_t*>(src) + length,
-                    static_cast<T *>(rawPtr()));
+                        dstT);
                 break;
             case DataType::UInt32:
                 std::copy(static_cast<const uint32_t*>(src), static_cast<const uint32_t*>(src) + length,
-                    static_cast<T *>(rawPtr()));
+                        dstT);
                 break;
             case DataType::Int16:
                 std::copy(static_cast<const int16_t*>(src), static_cast<const int16_t*>(src) + length,
-                    static_cast<T *>(rawPtr()));
+                        dstT);
                 break;
             case DataType::UInt16:
                 std::copy(static_cast<const uint16_t*>(src), static_cast<const uint16_t*>(src) + length,
-                    static_cast<T *>(rawPtr()));
+                        dstT);
                 break;
             case DataType::Int8:
                 std::copy(static_cast<const int8_t*>(src), static_cast<const int8_t*>(src) + length,
-                    static_cast<T *>(rawPtr()));
+                        dstT);
                 break;
             case DataType::UInt8:
                 std::copy(static_cast<const uint8_t*>(src), static_cast<const uint8_t*>(src) + length,
-                    static_cast<T *>(rawPtr()));
+                        dstT);
                 break;
             default:
                 AIDGE_THROW_OR_ABORT(std::runtime_error, "Unsupported data type.");
+                break;
         }
     }
 
 
-    void copyFromDevice(const void *src, NbElts_t length, const std::pair<std::string, DeviceIdx_t>& device) override {
+    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");
-        copy(src, length);
+        copy(src, length, offset);
     }
 
-    void copyFromHost(const void *src, NbElts_t length) override {
-        copy(src, length);
+    void copyFromHost(const void *src, NbElts_t length, NbElts_t offset = 0) override final {
+        copy(src, length, offset);
     }
 
-    void copyToHost(void *dst, NbElts_t length) const override {
-        AIDGE_ASSERT(length <= mData.size() || length <= mTensor.size(), "copy length is above capacity");
-        const T* src = static_cast<const T*>(rawPtr());
-        std::copy(static_cast<const T *>(src), static_cast<const T *>(src) + length,
-                  static_cast<T *>(dst));
+    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");
+        std::copy(src, src + length, static_cast<T *>(dst));
     }
 
-    void *rawPtr(NbElts_t offset = 0) override {
+    void *rawPtr(NbElts_t offset = 0) override final {
         lazyInit();
-        return (mData.data()->ptr() + offset*sizeof(T));
+        return (mData.ptr<T>() + offset);
     };
 
-    const void *rawPtr(NbElts_t offset = 0) const override {
-        AIDGE_ASSERT(mData.size() >= mTensor.size(), "accessing uninitialized const rawPtr");
-        return (mData.data()->ptr() + offset*sizeof(T));
+    const void *rawPtr(NbElts_t offset = 0) const override final {
+        AIDGE_ASSERT((mData.total() * mData.channels()) >= mNbElts, "accessing uninitialized const rawPtr");
+        return (mData.ptr<T>() + offset);
     };
 
-    void *hostPtr(NbElts_t offset = 0) override {
+    void *hostPtr(NbElts_t offset = 0) override final {
         lazyInit();
-        std::cout << *reinterpret_cast<T *>(mData.data()->ptr()) + offset << std::endl;
-        return (mData.data()->ptr() + offset*sizeof(T));
+        return (mData.ptr<T>() + offset);
     };
 
     const void *hostPtr(NbElts_t offset = 0) const override {
-        AIDGE_ASSERT(mData.size() >= mTensor.size(), "accessing uninitialized const hostPtr");
-        return (mData.data()->ptr() + offset*sizeof(T));
+        AIDGE_ASSERT((mData.total() * mData.channels()) >= mNbElts, "accessing uninitialized const hostPtr");
+        AIDGE_ASSERT(mData.isContinuous(), "CV Matrix not continuous");
+        return (mData.ptr<T>() + offset);
     };
 
-    const cv::Mat& getCvMat() const override { return *mDataOwner.get(); }
-    void setCvMat(const cv::Mat& mat) override {mDataOwner.reset(new cv::Mat(std::move(mat)));}
-
+    void setCvMat(const cv::Mat& mat) override {mData=mat;}
+    
 
   virtual ~TensorImpl_opencv() = default;
 
 private:
 
   void lazyInit() {
-    if (mData.size() < mTensor.size()) {
+    if ((mData.total() * mData.channels()) < mNbElts) {
         // Need more data, a re-allocation will occur
-        AIDGE_ASSERT(mData.empty() || mDataOwner != nullptr, "trying to enlarge non-owned data");
+        AIDGE_ASSERT(mData.empty() , "trying to enlarge non-owned data");
 
-        cv::Mat myNewMatrix;
-        if (mTensor.nbDims() < 3) {
-            myNewMatrix = cv::Mat(((mTensor.nbDims() > 1) ? static_cast<int>(mTensor.dims()[1])
-                                                    : (mTensor.nbDims() > 0) ? 1
+        if (mDims.size() < 3) {
+            mData = cv::Mat(((mDims.size() > 1) ? static_cast<int>(mDims[0])
+                                                    : (mDims.size() > 0) ? 1
                                                                             : 0),
-                            (mTensor.nbDims() > 0) ? static_cast<int>(mTensor.dims()[0]) : 0,
+                            (mDims.size() > 0) ? static_cast<int>(mDims[1]) : 0,
                             detail::CV_C1_CPP_v<T>);
         } else {
             std::vector<cv::Mat> channels;
 
-            for (std::size_t k = 0; k < mTensor.dims()[2]; ++k) {
-                channels.push_back(cv::Mat(static_cast<int>(mTensor.dims()[1]),
-                                        static_cast<int>(mTensor.dims()[0]),
+            for (std::size_t k = 0; k < mDims[2]; ++k) {
+                channels.push_back(cv::Mat(static_cast<int>(mDims[0]),
+                                        static_cast<int>(mDims[1]),
                                         detail::CV_C1_CPP_v<T>));
             }
 
-            cv::merge(channels, myNewMatrix);
+            cv::merge(channels, mData);
         }
-
-        mDataOwner.reset(new cv::Mat(std::forward<cv::Mat>(myNewMatrix)));
-        mData = future_std::span<cv::Mat>(mDataOwner.get(), mTensor.size());
-
     }
   }
 };