Added example for yolo/onnxruntime.

Adds an example using tensor_filter framework=tensorrt10.

Signed-off-by: Bram Veldhoen <[email protected]>

bash_script/example_yolo/gst-launch-object-detection-yolov5-onnxruntime.sh

@@ -0,0 +1,22 @@
+#!/usr/bin/env bash
+
+## torchscript (pytorch)
+gst-launch-1.0 \
+  v4l2src name=cam_src ! videoconvert ! videoscale ! \
+    video/x-raw,width=1000,height=1000,format=RGB,pixel-aspect-ratio=1/1,framerate=30/1 ! tee name=t \
+  t. ! queue leaky=2 max-size-buffers=2 ! videoscale ! \
+    video/x-raw,width=320,height=320,format=RGB ! tensor_converter ! \
+    tensor_transform mode=transpose option=1:2:0:3 ! \
+    tensor_transform mode=arithmetic option=typecast:float32,div:255.0 ! \
+    queue ! tensor_filter framework=onnxruntime model=yolov5su.onnx input=320:320:3:1 inputtype=float32 output=2100:84:1 outputtype=float32 latency=1 ! \
+    tensor_transform mode=transpose option=1:0:2:3 ! \
+    other/tensors,num_tensors=1,types=float32,dimensions=84:2100:1,format=static ! \
+    tensor_decoder mode=bounding_boxes option1=yolov8 option2=coco.txt option3=1 option4=1000:1000 option5=320:320 ! \
+    video/x-raw,width=1000,height=1000,format=RGBA ! mix.sink_0 \
+  t. ! queue leaky=2 max-size-buffers=10 ! mix.sink_1 \
+  compositor name=mix sink_0::zorder=2 sink_1::zorder=1 ! videoconvert ! ximagesink sync=false
+
+## Note that the `tensor_transfrom mode=transpose option=1:2:0:3`
+## change the data layout NHWC -> NCHW:
+## [1, 320h, 320w, 3] -> [1, 3, 320h, 320w]
+## The NCHW layout required by pytorch model

bash_script/example_yolo/gst-launch-object-detection-yolov5-tensorrt.sh → bash_script/example_yolo/gst-launch-object-detection-yolov5-tensorrt10.sh

@@ -8,7 +8,7 @@ gst-launch-1.0 \
     video/x-raw,width=320,height=320,format=RGB ! tensor_converter ! \
     tensor_transform mode=transpose option=1:2:0:3 ! \
     tensor_transform mode=arithmetic option=typecast:float32,div:255.0 ! \
-    queue ! tensor_filter framework=tensorrt model=yolov5su.onnx latency=1 ! \
+    queue ! tensor_filter framework=tensorrt10 model=yolov5su.onnx latency=1 ! \
     tensor_transform mode=transpose option=1:0:2:3 ! \
     other/tensors,num_tensors=1,types=float32,dimensions=84:2100:1,format=static ! \
     tensor_decoder mode=bounding_boxes option1=yolov8 option2=coco.txt option3=1 option4=1000:1000 option5=320:320 ! \

bash_script/example_yolo/meson.build

@@ -12,9 +12,3 @@ if have_pytorch
     install_dir: examples_install_dir
   )
 endif
-
-if have_tensorrt
-  install_data('gst-launch-object-detection-yolov5-tensorrt.sh',
-    install_dir: examples_install_dir
-  )
-endif