Add YOLOv8 support

nvdsinfer_custom_impl_Yolo/yoloForward_v8.cu

@@ -0,0 +1,62 @@
+/*
+ * Created by Marcos Luciano
+ * https://www.github.com/marcoslucianops
+ */
+
+#include <stdint.h>
+
+__global__ void gpuYoloLayer_v8(const float* input, int* num_detections, float* detection_boxes, float* detection_scores,
+    int* detection_classes, const float scoreThreshold, const uint netWidth, const uint netHeight,
+    const uint numOutputClasses, const uint64_t outputSize)
+{
+  uint x_id = blockIdx.x * blockDim.x + threadIdx.x;
+
+  if (x_id >= outputSize)
+    return;
+
+  float maxProb = 0.0f;
+  int maxIndex = -1;
+
+  for (uint i = 0; i < numOutputClasses; ++i) {
+    float prob = input[x_id * (4 + numOutputClasses) + i + 4];
+    if (prob > maxProb) {
+      maxProb = prob;
+      maxIndex = i;
+    }
+  }
+
+  if (maxProb < scoreThreshold)
+    return;
+
+  int count = (int)atomicAdd(num_detections, 1);
+
+  detection_boxes[count * 4 + 0] = input[x_id * (4 + numOutputClasses) + 0];
+  detection_boxes[count * 4 + 1] = input[x_id * (4 + numOutputClasses) + 1];
+  detection_boxes[count * 4 + 2] = input[x_id * (4 + numOutputClasses) + 2];
+  detection_boxes[count * 4 + 3] = input[x_id * (4 + numOutputClasses) + 3];
+  detection_scores[count] = maxProb;
+  detection_classes[count] = maxIndex;
+}
+
+cudaError_t cudaYoloLayer_v8(const void* input, void* num_detections, void* detection_boxes, void* detection_scores,
+    void* detection_classes, const uint& batchSize, uint64_t& outputSize, const float& scoreThreshold, const uint& netWidth,
+    const uint& netHeight, const uint& numOutputClasses, cudaStream_t stream);
+
+cudaError_t cudaYoloLayer_v8(const void* input, void* num_detections, void* detection_boxes, void* detection_scores,
+    void* detection_classes, const uint& batchSize, uint64_t& outputSize, const float& scoreThreshold, const uint& netWidth,
+    const uint& netHeight, const uint& numOutputClasses, cudaStream_t stream)
+{
+  int threads_per_block = 16;
+  int number_of_blocks = (outputSize / threads_per_block) + 1;
+
+  for (unsigned int batch = 0; batch < batchSize; ++batch) {
+    gpuYoloLayer_v8<<<number_of_blocks, threads_per_block, 0, stream>>>(
+        reinterpret_cast<const float*>(input) + (batch * (4 + numOutputClasses) * outputSize),
+        reinterpret_cast<int*>(num_detections) + (batch),
+        reinterpret_cast<float*>(detection_boxes) + (batch * 4 * outputSize),
+        reinterpret_cast<float*>(detection_scores) + (batch * outputSize),
+        reinterpret_cast<int*>(detection_classes) + (batch * outputSize),
+        scoreThreshold, netWidth, netHeight, numOutputClasses, outputSize);
+  }
+  return cudaGetLastError();
+}