Add dynamic batch-size (ONNX) + Fixes

utils/export_yoloV6.py

@@ -51,6 +51,11 @@ def yolov6_export(weights, device):
 
 def main(args):
     suppress_warnings()
+
+    print('\nStarting: %s' % args.weights)
+
+    print('Opening YOLOv6 model\n')
+
     device = torch.device('cpu')
     model = yolov6_export(args.weights, device)
 
@@ -64,15 +69,29 @@ def main(args):
     onnx_input_im = torch.zeros(1, 3, *img_size).to(device)
     onnx_output_file = os.path.basename(args.weights).split('.pt')[0] + '.onnx'
 
+    dynamic_axes = {
+        'input': {
+            0: 'batch'
+        },
+        'output': {
+            0: 'batch'
+        }
+    }
+
+    print('\nExporting the model to ONNX')
     torch.onnx.export(model, onnx_input_im, onnx_output_file, verbose=False, opset_version=args.opset,
-                      do_constant_folding=True, input_names=['input'], output_names=['output'], dynamic_axes=None)
+                      do_constant_folding=True, input_names=['input'], output_names=['output'],
+                      dynamic_axes=dynamic_axes if args.dynamic else None)
 
     if args.simplify:
+        print('Simplifying the ONNX model')
         import onnxsim
         model_onnx = onnx.load(onnx_output_file)
         model_onnx, _ = onnxsim.simplify(model_onnx)
         onnx.save(model_onnx, onnx_output_file)
 
+    print('Done: %s\n' % onnx_output_file)
+
 
 def parse_args():
     parser = argparse.ArgumentParser(description='DeepStream YOLOv6 conversion')
@@ -81,6 +100,7 @@ def parse_args():
     parser.add_argument('--p6', action='store_true', help='P6 model')
     parser.add_argument('--opset', type=int, default=13, help='ONNX opset version')
     parser.add_argument('--simplify', action='store_true', help='ONNX simplify model')
+    parser.add_argument('--dynamic', action='store_true', help='Dynamic batch-size')
     args = parser.parse_args()
     if not os.path.isfile(args.weights):
         raise SystemExit('Invalid weights file')