Download scripts/export_plate.py from imbcmdth/rfdetr-onnx: direct link, hf CLI and curl.
- Browser
- Download file 2.38 kB
-
https://huggingface.co/imbcmdth/rfdetr-onnx/resolve/main/scripts/export_plate.py
- Command line
-
hf download hf://imbcmdth/rfdetr-onnx/scripts/export_plate.py
-
curl -L -o export_plate.py https://huggingface.co/imbcmdth/rfdetr-onnx/resolve/main/scripts/export_plate.py
2.38 kB
| """Export the RF-DETR Medium licence-plate checkpoint to ONNX at 576x576. | |
| The checkpoint is our own fine-tune, made with `rfdetr==1.10.1` from | |
| Roboflow's rf-detr-medium.pth on Open Images V7's "Vehicle registration plate" | |
| boxes (annotations CC BY 4.0), the group-of boxes dropped: 4,497 training | |
| images with 6,554 plates, 724 validation images with 985. Twenty epochs at | |
| 576, batch 8 with two steps of gradient accumulation, on one RTX 4090; the | |
| EMA weights with the best validation mAP, epoch 4 at 0.655 mAP 50:95, are | |
| the checkpoint exported here. | |
| The export mirrors scripts/export_face.py: the rfdetr package's own | |
| model.export(format="onnx"), opset 17. num_classes is NOT passed, so the head | |
| is exported as trained. rfdetr 1.10.1 lays a one-class head out as the class | |
| plus one spare slot, so `labels` is 1x300x2: index 0 is the plate, index 1 | |
| was never trained toward anything and stays quiet. | |
| """ | |
| import glob | |
| import hashlib | |
| import os | |
| import shutil | |
| import sys | |
| from rfdetr import RFDETRMedium | |
| CKPT = r"E:/projects/model-work/ckpt/rfdetr_medium_plate.pth" | |
| OUTDIR = r"E:/projects/model-work/export-plate" | |
| FINAL = r"E:/projects/rfdetr-onnx/rf-detr-medium-plate.onnx" | |
| def sha256(path): | |
| digest = hashlib.sha256() | |
| with open(path, "rb") as handle: | |
| for chunk in iter(lambda: handle.read(1 << 20), b""): | |
| digest.update(chunk) | |
| return digest.hexdigest() | |
| def main(): | |
| os.makedirs(OUTDIR, exist_ok=True) | |
| model = RFDETRMedium(pretrain_weights=CKPT, resolution=576) | |
| print("model_config.num_classes =", model.model_config.num_classes) | |
| print("model_config.resolution =", model.model_config.resolution) | |
| print("class_embed out_features =", model.model.model.class_embed.out_features) | |
| model.export(format="onnx", output_dir=OUTDIR, opset_version=17) | |
| produced = sorted(glob.glob(os.path.join(OUTDIR, "*.onnx"))) | |
| for path in produced: | |
| print("produced", path, os.path.getsize(path), sha256(path)) | |
| if len(produced) != 1: | |
| print("expected exactly one .onnx, got", produced) | |
| sys.exit(1) | |
| if os.path.exists(FINAL): | |
| print("refusing to overwrite existing", FINAL) | |
| sys.exit(1) | |
| shutil.copyfile(produced[0], FINAL) | |
| print("final", FINAL, os.path.getsize(FINAL), sha256(FINAL)) | |
| print("source_pth", CKPT, os.path.getsize(CKPT), sha256(CKPT)) | |
| if __name__ == "__main__": | |
| main() | |