-
-
Notifications
You must be signed in to change notification settings - Fork 15.9k
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
1 parent
8cab44e
commit df7988d
Showing
4 changed files
with
37 additions
and
19 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,32 @@ | ||
import argparse | ||
|
||
import onnx | ||
|
||
from models.common import * | ||
|
||
if __name__ == '__main__': | ||
parser = argparse.ArgumentParser() | ||
parser.add_argument('--weights', default='../weights/yolov5s.pt', help='model path RELATIVE to ./models/') | ||
parser.add_argument('--img-size', default=640, help='inference size (pixels)') | ||
parser.add_argument('--batch-size', default=1, help='batch size') | ||
opt = parser.parse_args() | ||
|
||
# Parameters | ||
f = opt.weights.replace('.pt', '.onnx') # onnx filename | ||
img = torch.zeros((opt.batch_size, 3, opt.img_size, opt.img_size)) # image size, (1, 3, 320, 192) iDetection | ||
|
||
# Load pytorch model | ||
google_utils.attempt_download(opt.weights) | ||
model = torch.load(opt.weights)['model'] | ||
model.eval() | ||
# model.fuse() # optionally fuse Conv2d + BatchNorm2d layers TODO | ||
|
||
# Export to onnx | ||
model.model[-1].export = True # set Detect() layer export=True | ||
torch.onnx.export(model, img, f, verbose=False, opset_version=11) | ||
|
||
# Check onnx model | ||
model = onnx.load(f) # load onnx model | ||
onnx.checker.check_model(model) # check onnx model | ||
print(onnx.helper.printable_graph(model.graph)) # print a human readable representation of the graph | ||
print('Export complete. ONNX model saved to %s\nView with https://github.com/lutzroeder/netron' % f) |