Update for v1.0

tests/python/demo_object_detection.py

@@ -0,0 +1,27 @@
+import argparse
+
+def get_argsparser():
+    """Parse commandline."""
+    parser = argparse.ArgumentParser(description="Bianbu AI Python Demo for Object Detection.")
+    parser.add_argument("--image", "-i", type=str, required=True, help="input test image path")
+    parser.add_argument("--model", "-m", type=str, required=True, help="input test model(*.onnx) path")
+    parser.add_argument("--label", "-l", type=str, required=True, help="input test label path")
+    parser.add_argument("--intra", type=int, default=2, help="intra thread number for backend(e.g. onnxruntime)")
+    parser.add_argument("--inter", type=int, default=2, help="inter thread number for backend(e.g. onnxruntime)")
+    return parser.parse_args()
+
+
+if __name__ == "__main__":
+    args = get_argsparser()
+
+    import cv2
+    from bianbuai import ObjectDetectionOption, ObjectDetectionTask
+    option = ObjectDetectionOption()
+    option.model_path = args.model
+    option.label_path = args.label
+    option.intra_threads_num = args.intra
+    option.inter_threads_num = args.inter
+    task = ObjectDetectionTask(option)
+    outputs = task.Detect(cv2.imread(args.image))
+    for i, box in enumerate(outputs):
+        print("bbox[%2d] x1y1x2y2: (%4d,%4d,%4d,%4d), score: %5.3f, label_text: %s" % (i, box.x1, box.y1, box.x2, box.y2, box.score, box.label_text))