Remove denoise module and thirdparty OIDN.

This is replaced by a much lighter weight and faster JNLM denoiser. OIDN is still much more accurate, and may be provided as an optional backend in the future, but the JNLM denoiser seems good enough for most use cases and removing OIDN reduces the build system complexity, binary size, and build times very significantly.

1 files changed, 0 insertions, 66 deletions

diff --git a/thirdparty/oidn/common/tensor.h b/thirdparty/oidn/common/tensor.h
deleted file mode 100644
index 48e7d1123d..0000000000
--- a/thirdparty/oidn/common/tensor.h
+++ /dev/null
@@ -1,66 +0,0 @@
-// ======================================================================== //
-// Copyright 2009-2019 Intel Corporation                                    //
-//                                                                          //
-// 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.                                           //
-// ======================================================================== //
-
-#pragma once
-
-#include "platform.h"
-#include <vector>
-#include <map>
-
-namespace oidn {
-
-  template<typename T>
-  using shared_vector = std::shared_ptr<std::vector<T>>;
-
-  // Generic tensor
-  struct Tensor
-  {
-    float* data;
-    std::vector<int64_t> dims;
-    std::string format;
-    shared_vector<char> buffer; // optional, only for reference counting
-
-    __forceinline Tensor() : data(nullptr) {}
-
-    __forceinline Tensor(const std::vector<int64_t>& dims, const std::string& format)
-      : dims(dims),
-        format(format)
-    {
-      buffer = std::make_shared<std::vector<char>>(size() * sizeof(float));
-      data = (float*)buffer->data();
-    }
-
-    __forceinline operator bool() const { return data != nullptr; }
-
-    __forceinline int ndims() const { return (int)dims.size(); }
-
-    // Returns the number of values
-    __forceinline size_t size() const
-    {
-      size_t size = 1;
-      for (int i = 0; i < ndims(); ++i)
-        size *= dims[i];
-      return size;
-    }
-
-    __forceinline float& operator [](size_t i) { return data[i]; }
-    __forceinline const float& operator [](size_t i) const { return data[i]; }
-  };
-
-  // Parses tensors from a buffer
-  std::map<std::string, Tensor> parseTensors(void* buffer);
-
-} // namespace oidn