#!/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())