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detection_onnxruntime_static.py

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+# _base_ = ["./_base_/base_static.py", "../_base_/backends/onnxruntime.py"]
+
+onnx_config = dict(
+    type='onnx',
+    export_params=True,
+    keep_initializers_as_inputs=False,
+    opset_version=11,
+    save_file='end2end.onnx',
+    input_names=['input'],
+    output_names=['dets', 'labels'],
+    input_shape=None,
+    optimize=True)
+
+backend_config = dict(type='onnxruntime')
+
+
+codebase_config = dict(
+    type='mmdet',
+    task='ObjectDetection',
+    model_type='end2end',
+    post_processing=dict(
+        score_threshold=0.05,
+        confidence_threshold=0.005,  # for YOLOv3
+        iou_threshold=0.5,
+        max_output_boxes_per_class=200,
+        pre_top_k=5000,
+        keep_top_k=100,
+        background_label_id=-1,
+    ))

pose-detection_simcc_onnxruntime_dynamic.py

@@ -0,0 +1,19 @@
+# _base_ = ["./pose-detection_static.py", "../_base_/backends/onnxruntime.py"]
+
+# onnx_config = dict(input_shape=None)
+
+codebase_config = dict(type="mmpose", task="PoseDetection")
+
+backend_config = dict(type='onnxruntime')
+
+onnx_config = dict(
+    input_shape=[192, 256],
+    output_names=["simcc_x", "simcc_y"],
+    dynamic_axes={
+        "input": {
+            0: "batch",
+        },
+        "simcc_x": {0: "batch"},
+        "simcc_y": {0: "batch"},
+    },
+)