Big update

utils/export_yolox.py

@@ -0,0 +1,81 @@
+import os
+import sys
+import argparse
+import warnings
+import onnx
+import torch
+import torch.nn as nn
+from yolox.exp import get_exp
+from yolox.utils import replace_module
+from yolox.models.network_blocks import SiLU
+
+
+class DeepStreamOutput(nn.Module):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x):
+        boxes = x[:, :, :4]
+        objectness = x[:, :, 4:5]
+        scores, classes = torch.max(x[:, :, 5:], 2, keepdim=True)
+        return torch.cat((boxes, scores, classes, objectness), dim=2)
+
+
+def suppress_warnings():
+    warnings.filterwarnings('ignore', category=torch.jit.TracerWarning)
+    warnings.filterwarnings('ignore', category=UserWarning)
+    warnings.filterwarnings('ignore', category=DeprecationWarning)
+
+
+def yolox_export(weights, exp_file):
+    exp = get_exp(exp_file)
+    model = exp.get_model()
+    ckpt = torch.load(weights, map_location='cpu')
+    model.eval()
+    if 'model' in ckpt:
+        ckpt = ckpt['model']
+    model.load_state_dict(ckpt)
+    model = replace_module(model, nn.SiLU, SiLU)
+    model.head.decode_in_inference = True
+    return model, exp
+
+
+def main(args):
+    suppress_warnings()
+    device = torch.device('cpu')
+    model, exp = yolox_export(args.weights, args.exp)
+
+    model = nn.Sequential(model, DeepStreamOutput())
+
+    img_size = [exp.input_size[1], exp.input_size[0]]
+
+    onnx_input_im = torch.zeros(1, 3, *img_size).to(device)
+    onnx_output_file = os.path.basename(args.weights).split('.pt')[0] + '.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 YOLOX conversion')
+    parser.add_argument('-w', '--weights', required=True, help='Input weights (.pth) file path (required)')
+    parser.add_argument('-c', '--exp', required=True, help='Input exp (.py) file path (required)')
+    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.exp):
+        raise SystemExit('Invalid exp file')
+    return args
+
+
+if __name__ == '__main__':
+    args = parse_args()
+    sys.exit(main(args))