YOLO11-RKNN2 / source /convert_official.py
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Add tested Rockchip RKOPT FP16 and INT8 detectors (Toolkit 2.3.2)
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#!/usr/bin/env python3
"""Download the ONNX listed by Rockchip and invoke its unmodified converters."""
import argparse
import concurrent.futures
import hashlib
from importlib.metadata import version
import json
from pathlib import Path
import re
import shutil
import subprocess
import sys
import tempfile
import yaml
DETECTORS = ("yolov5", "yolov6", "yolov7", "yolov8", "yolov10", "yolo11",
"yolo26", "yolox", "ppyoloe", "yolo_world")
TASKS = ("yolov5_seg", "yolov8_seg", "yolov8_pose", "yolov8_obb")
SUPPLIED_ONNX = {
"yolo26n": "https://meta.zbox.filez.com/v/link/view/dddfdaa76107404a8a358673fa31a041",
"yolo26m": "https://meta.zbox.filez.com/v/link/view/198e90ee6bc94c71ad2002d5f9897ac4",
}
def inventory(zoo):
for family in (*DETECTORS, *TASKS):
readme = zoo / "examples" / family / "README.md"
urls = re.findall(r"\((https://[^)]+\.onnx)\)", readme.read_text())
assets = {Path(url).stem: url for url in urls}
if family in ("yolov8_pose", "yolov8_obb"):
assets = {name: url for name, url in assets.items() if "v5n-" in name or "v8n-" in name}
if family == "yolo26":
assets.update({"yolo26n": None, "yolo26m": None})
for name, url in assets.items():
yield family, name, url
def download(root, zoo, family, name, url):
destination = root / "onnx" / family / f"{name}.onnx"
destination.parent.mkdir(parents=True, exist_ok=True)
if not destination.is_file():
local = zoo / "examples" / family / "model" / destination.name
if not url and local.is_file():
shutil.copy2(local, destination)
elif url:
partial = destination.with_suffix(".part")
subprocess.run(["curl", "-fLsS", "--retry", "2", "--connect-timeout", "12",
"--max-time", "180", "-o", partial, url], check=True)
partial.replace(destination)
else:
raise FileNotFoundError(
f"Download {SUPPLIED_ONNX[name]} and save its ONNX as {destination}")
import onnx
onnx.load(str(destination), load_external_data=False)
return destination
def digest(path):
checksum = hashlib.sha256()
with path.open("rb") as stream:
for block in iter(lambda: stream.read(1024 * 1024), b""):
checksum.update(block)
return checksum.hexdigest()
def write_metadata(zoo, family, model, destination, chip):
if family == "yolo_world":
return
import onnx
inputs = onnx.load(str(model), load_external_data=False).graph.input
shape = [dim.dim_value for dim in inputs[0].type.tensor_type.shape.dim]
if len(shape) != 4 or shape[:2] != [1, 3] or min(shape[2:]) <= 0:
raise RuntimeError(f"Expected static NCHW RGB model, got {shape}")
assets = zoo / "examples" / family / "model"
labels = next(assets.glob("*labels_list.txt"))
tasks = {"yolov5_seg": "segment", "yolov8_seg": "segment",
"yolov8_pose": "pose", "yolov8_obb": "obb"}
task = tasks.get(family, "detect")
info = {
"task": task, "batch": 1, "channels": 3, "imgsz": shape[2:],
"names": [line.strip() for line in labels.read_text().splitlines() if line.strip()],
"target_platform": chip,
"coordinates": "pixels",
}
if family in ("yolov5", "yolov5_seg", "yolov7"):
values = [float(value) for value in next(assets.glob("anchors_*.txt")).read_text().split()]
info.update(head="anchored", anchors=[values[i:i + 6] for i in range(0, len(values), 6)])
if family == "yolox":
info["head"] = "yolox"
if family in ("yolov10", "yolo26"):
info["end2end"] = True
if task == "pose":
info["kpt_shape"] = [17, 3]
(destination / "metadata.yaml").write_text(yaml.safe_dump(info, sort_keys=False))
def convert(root, zoo, asset, chip, precision, refresh_metadata=False):
family, name, model, source = asset
destination = root / "rknn" / chip / family / name / precision
destination.mkdir(parents=True, exist_ok=True)
output = destination / "model.rknn"
receipt = destination / "conversion.json"
if not refresh_metadata and output.is_file() and receipt.is_file() and (
family == "yolo_world" or (destination / "metadata.yaml").is_file()):
return f"cached {family}/{name} {chip} {precision}"
work_root = root / "scratch"
work_root.mkdir(exist_ok=True)
with tempfile.TemporaryDirectory(dir=work_root, prefix=f"{name}-{chip}-{precision}-") as scratch:
# Keep the relative dataset and model paths expected by the official scripts.
tree = Path(scratch)
(tree / "datasets").symlink_to(zoo / "datasets")
example = tree / "examples" / family
example.mkdir(parents=True)
(example / "model").symlink_to(zoo / "examples" / family / "model")
working = example / "python"
shutil.copytree(zoo / "examples" / family / "python", working)
staged = destination / "model.partial.rknn"
commands = []
if family == "yolo_world":
subdir = "clip_text" if name == "clip_text" else "yolo_world"
script = f"{subdir}/convert.py"
commands.append([script, str(model), chip, precision, str(staged)])
elif family == "yolov8_pose":
if precision == "i8":
commands.append(["convert.py", str(model), chip, "i8", "1"])
commands.append(["convert.py", str(model), chip, "i8", "2", str(staged)])
else:
commands.append(["convert.py", str(model), chip, "fp", "1", str(staged)])
else:
commands.append(["convert.py", str(model), chip, precision, str(staged)])
if not output.is_file():
with (destination / "convert.log").open("w") as log:
for command in commands:
print(subprocess.list2cmdline(command), file=log, flush=True)
subprocess.run([sys.executable, *command], cwd=working,
stdout=log, stderr=subprocess.STDOUT, check=True)
if not staged.is_file() or not staged.stat().st_size:
raise RuntimeError("Converter did not produce an RKNN file")
staged.replace(output)
write_metadata(zoo, family, model, destination, chip)
receipt.write_text(json.dumps({
"source": source, "onnx_sha256": digest(model), "rknn_sha256": digest(output),
"commands": commands, "toolkit_python": sys.executable,
"toolkit_version": version("rknn-toolkit2"),
"zoo_commit": subprocess.check_output(
["git", "-C", str(zoo), "rev-parse", "HEAD"], text=True).strip(),
}, indent=2) + "\n")
return f"ok {family}/{name} {chip} {precision}"
def main():
parser = argparse.ArgumentParser(description=__doc__)
root = Path(__file__).resolve().parent
parser.add_argument("--zoo", type=Path, default=root.parent / "rknn_model_zoo",
help="Model Zoo checkout (default: ../rknn_model_zoo)")
parser.add_argument("--jobs", type=int, default=4)
parser.add_argument("--model", action="append", help="Limit the run to named variants")
parser.add_argument("--chip", choices=("rk3576", "rk3588"), action="append")
parser.add_argument("--precision", choices=("i8", "fp"), action="append")
parser.add_argument("--refresh-metadata", action="store_true")
args = parser.parse_args()
zoo = args.zoo.resolve()
inventory_rows = [item for item in inventory(zoo) if not args.model or item[1] in args.model]
failures = 0
with concurrent.futures.ThreadPoolExecutor(max_workers=6) as downloads, \
concurrent.futures.ThreadPoolExecutor(max_workers=args.jobs) as workers:
pending = {downloads.submit(download, root, zoo, *item): item for item in inventory_rows}
builds = {}
for future in concurrent.futures.as_completed(pending):
family, name, source = pending[future]
try:
model = future.result()
asset = family, name, model, source or SUPPLIED_ONNX.get(name) or str(model)
for chip in args.chip or ("rk3576", "rk3588"):
for precision in args.precision or ("i8", "fp"):
if name == "clip_text" and precision == "i8":
continue
job = workers.submit(convert, root, zoo, asset, chip, precision,
args.refresh_metadata)
builds[job] = family, name, chip, precision
except Exception as error:
print(f"asset failed {family}/{name}: {error}", flush=True)
failures += 1
for future in concurrent.futures.as_completed(builds):
try:
print(future.result(), flush=True)
except Exception as error:
print(f"build failed {' '.join(builds[future])}: {error}", flush=True)
failures += 1
return bool(failures)
if __name__ == "__main__":
raise SystemExit(main())