86 lines
2.7 KiB
Python
86 lines
2.7 KiB
Python
import os
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import sys
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import argparse
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import warnings
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import onnx
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import torch
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import torch.nn as nn
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from copy import deepcopy
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from ultralytics import YOLO
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from ultralytics.yolo.utils.torch_utils import select_device
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from ultralytics.nn.modules import C2f, Detect
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class DeepStreamOutput(nn.Module):
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def __init__(self):
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super().__init__()
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def forward(self, x):
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x = x.transpose(1, 2)
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boxes = x[:, :, :4]
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scores, classes = torch.max(x[:, :, 4:], 2, keepdim=True)
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return torch.cat((boxes, scores, classes), dim=2)
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def suppress_warnings():
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warnings.filterwarnings('ignore', category=torch.jit.TracerWarning)
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warnings.filterwarnings('ignore', category=UserWarning)
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warnings.filterwarnings('ignore', category=DeprecationWarning)
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def yolov8_export(weights, device):
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model = YOLO(weights)
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model = deepcopy(model.model).to(device)
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for p in model.parameters():
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p.requires_grad = False
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model.eval()
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model.float()
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model = model.fuse()
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for k, m in model.named_modules():
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if isinstance(m, Detect):
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m.dynamic = False
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m.export = True
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m.format = 'onnx'
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elif isinstance(m, C2f):
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m.forward = m.forward_split
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return model
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def main(args):
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suppress_warnings()
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device = select_device('cpu')
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model = yolov8_export(args.weights, device)
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model = nn.Sequential(model, DeepStreamOutput())
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img_size = args.size * 2 if len(args.size) == 1 else args.size
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onnx_input_im = torch.zeros(1, 3, *img_size).to(device)
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onnx_output_file = os.path.basename(args.weights).split('.pt')[0] + '.onnx'
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torch.onnx.export(model, onnx_input_im, onnx_output_file, verbose=False, opset_version=args.opset,
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do_constant_folding=True, input_names=['input'], output_names=['output'], dynamic_axes=None)
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if args.simplify:
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import onnxsim
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model_onnx = onnx.load(onnx_output_file)
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model_onnx, _ = onnxsim.simplify(model_onnx)
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onnx.save(model_onnx, onnx_output_file)
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def parse_args():
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parser = argparse.ArgumentParser(description='DeepStream YOLOv8 conversion')
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parser.add_argument('-w', '--weights', required=True, help='Input weights (.pt) file path (required)')
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parser.add_argument('-s', '--size', nargs='+', type=int, default=[640], help='Inference size [H,W] (default [640])')
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parser.add_argument('--opset', type=int, default=16, help='ONNX opset version')
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parser.add_argument('--simplify', action='store_true', help='ONNX simplify model')
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args = parser.parse_args()
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if not os.path.isfile(args.weights):
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raise SystemExit('Invalid weights file')
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return args
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if __name__ == '__main__':
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args = parse_args()
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sys.exit(main(args))
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