Add DAMO-YOLO + Fixes

utils/export_damoyolo.py

@@ -0,0 +1,86 @@
+import os
+import sys
+import argparse
+import warnings
+import onnx
+import torch
+import torch.nn as nn
+from damo.base_models.core.ops import RepConv, SiLU
+from damo.config.base import parse_config
+from damo.detectors.detector import build_local_model
+from damo.utils.model_utils import replace_module
+
+
+class DeepStreamOutput(nn.Module):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x):
+        boxes = x[1]
+        scores, classes = torch.max(x[0], 2, keepdim=True)
+        return torch.cat((boxes, scores, classes), dim=2)
+
+
+def suppress_warnings():
+    warnings.filterwarnings('ignore', category=torch.jit.TracerWarning)
+    warnings.filterwarnings('ignore', category=UserWarning)
+    warnings.filterwarnings('ignore', category=DeprecationWarning)
+
+
+def damoyolo_export(weights, config_file, device):
+    config = parse_config(config_file)
+    config.model.head.export_with_post = True
+    model = build_local_model(config, device)
+    ckpt = torch.load(weights, map_location=device)
+    model.eval()
+    if 'model' in ckpt:
+        ckpt = ckpt['model']
+    model.load_state_dict(ckpt, strict=True)
+    model = replace_module(model, nn.SiLU, SiLU)
+    for layer in model.modules():
+        if isinstance(layer, RepConv):
+            layer.switch_to_deploy()
+    model.head.nms = False
+    return config, model
+
+
+def main(args):
+    suppress_warnings()
+    device = torch.device('cpu')
+    cfg, model = damoyolo_export(args.weights, args.config, device)
+
+    model = nn.Sequential(model, DeepStreamOutput())
+
+    img_size = args.size * 2 if len(args.size) == 1 else args.size
+
+    onnx_input_im = torch.zeros(1, 3, *img_size).to(device)
+    onnx_output_file = cfg.miscs['exp_name'] + '.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)
+
+    if args.simplify:
+        import onnxsim
+        model_onnx = onnx.load(onnx_output_file)
+        model_onnx, _ = onnxsim.simplify(model_onnx)
+        onnx.save(model_onnx, onnx_output_file)
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(description='DeepStream DAMO-YOLO conversion')
+    parser.add_argument('-w', '--weights', required=True, help='Input weights (.pth) file path (required)')
+    parser.add_argument('-c', '--config', required=True, help='Input config (.py) file path (required)')
+    parser.add_argument('-s', '--size', nargs='+', type=int, default=[640], help='Inference size [H,W] (default [640])')
+    parser.add_argument('--opset', type=int, default=11, help='ONNX opset version')
+    parser.add_argument('--simplify', action='store_true', help='ONNX simplify model')
+    args = parser.parse_args()
+    if not os.path.isfile(args.weights):
+        raise SystemExit('Invalid weights file')
+    if not os.path.isfile(args.config):
+        raise SystemExit('Invalid config file')
+    return args
+
+
+if __name__ == '__main__':
+    args = parse_args()
+    sys.exit(main(args))