Remove experimental compression builds from the release repository

README.md

@@ -27,5 +27,3 @@ compiled with the Model Zoo converter. The exact checkpoint URLs, exporter
 commits, scripts, and ONNX graphs are under `source/`.
 
 Models are organized by RKNN Toolkit2 version under `models/v<version>/`. Each model and its metadata share a folder.
-
-The RK3588 weight compression trials are archived under [experiments](tree/main/experiments).

experiments/manifest.json

@@ -1,30 +0,0 @@
-[
-  {
-    "name": "yolov8n-weight-compression",
-    "family": "optimization",
-    "task": "detect",
-    "chip": "rk3588",
-    "precision": "fp16",
-    "path": "experiments/v2.5.0/detect/yolov8n-weight-compression/rk3588/fp16",
-    "sha256": "6375c7275e2aa16ddc1639fca085b3f6d323f71180af07b82c2fc070e00eb410",
-    "toolkit_version": "2.5.0",
-    "source_url": "https://github.com/airockchip/rknn_model_zoo/tree/main/examples/yolov8",
-    "upstream_project": "https://github.com/airockchip/rknn_model_zoo/tree/main/examples/yolov8",
-    "conversion": "experimental-compression",
-    "metadata_sha256": "48afa4c902e0f020d5ffafdadcf3b7e799e9986cdb16e2787114908da2f4e5b5"
-  },
-  {
-    "name": "yolov8n-weight-compression",
-    "family": "optimization",
-    "task": "detect",
-    "chip": "rk3588",
-    "precision": "int8",
-    "path": "experiments/v2.5.0/detect/yolov8n-weight-compression/rk3588/int8",
-    "sha256": "f3806db3444fd9034f6ed7f418e3b47b3a57df8a681e8df3859ced98fcb56f0d",
-    "toolkit_version": "2.5.0",
-    "source_url": "https://github.com/airockchip/rknn_model_zoo/tree/main/examples/yolov8",
-    "upstream_project": "https://github.com/airockchip/rknn_model_zoo/tree/main/examples/yolov8",
-    "conversion": "experimental-compression",
-    "metadata_sha256": "48afa4c902e0f020d5ffafdadcf3b7e799e9986cdb16e2787114908da2f4e5b5"
-  }
-]

experiments/v2.5.0/detect/yolov8n-weight-compression/rk3588/fp16/metadata.yaml

@@ -1,89 +0,0 @@
-task: detect
-batch: 1
-channels: 3
-imgsz:
-- 640
-- 640
-names:
-- person
-- bicycle
-- car
-- motorcycle
-- airplane
-- bus
-- train
-- truck
-- boat
-- traffic light
-- fire hydrant
-- stop sign
-- parking meter
-- bench
-- bird
-- cat
-- dog
-- horse
-- sheep
-- cow
-- elephant
-- bear
-- zebra
-- giraffe
-- backpack
-- umbrella
-- handbag
-- tie
-- suitcase
-- frisbee
-- skis
-- snowboard
-- sports ball
-- kite
-- baseball bat
-- baseball glove
-- skateboard
-- surfboard
-- tennis racket
-- bottle
-- wine glass
-- cup
-- fork
-- knife
-- spoon
-- bowl
-- banana
-- apple
-- sandwich
-- orange
-- broccoli
-- carrot
-- hot dog
-- pizza
-- donut
-- cake
-- chair
-- couch
-- potted plant
-- bed
-- dining table
-- toilet
-- tv
-- laptop
-- mouse
-- remote
-- keyboard
-- cell phone
-- microwave
-- oven
-- toaster
-- sink
-- refrigerator
-- book
-- clock
-- vase
-- scissors
-- teddy bear
-- hair drier
-- toothbrush
-target_platform: rk3588
-coordinates: pixels

experiments/v2.5.0/detect/yolov8n-weight-compression/rk3588/fp16/model.rknn

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:6375c7275e2aa16ddc1639fca085b3f6d323f71180af07b82c2fc070e00eb410
-size 7666569

experiments/v2.5.0/detect/yolov8n-weight-compression/rk3588/int8/metadata.yaml

@@ -1,89 +0,0 @@
-task: detect
-batch: 1
-channels: 3
-imgsz:
-- 640
-- 640
-names:
-- person
-- bicycle
-- car
-- motorcycle
-- airplane
-- bus
-- train
-- truck
-- boat
-- traffic light
-- fire hydrant
-- stop sign
-- parking meter
-- bench
-- bird
-- cat
-- dog
-- horse
-- sheep
-- cow
-- elephant
-- bear
-- zebra
-- giraffe
-- backpack
-- umbrella
-- handbag
-- tie
-- suitcase
-- frisbee
-- skis
-- snowboard
-- sports ball
-- kite
-- baseball bat
-- baseball glove
-- skateboard
-- surfboard
-- tennis racket
-- bottle
-- wine glass
-- cup
-- fork
-- knife
-- spoon
-- bowl
-- banana
-- apple
-- sandwich
-- orange
-- broccoli
-- carrot
-- hot dog
-- pizza
-- donut
-- cake
-- chair
-- couch
-- potted plant
-- bed
-- dining table
-- toilet
-- tv
-- laptop
-- mouse
-- remote
-- keyboard
-- cell phone
-- microwave
-- oven
-- toaster
-- sink
-- refrigerator
-- book
-- clock
-- vase
-- scissors
-- teddy bear
-- hair drier
-- toothbrush
-target_platform: rk3588
-coordinates: pixels

experiments/v2.5.0/detect/yolov8n-weight-compression/rk3588/int8/model.rknn

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f3806db3444fd9034f6ed7f418e3b47b3a57df8a681e8df3859ced98fcb56f0d
-size 4317323

source/compress-weights.py

@@ -1,48 +0,0 @@
-"""Try RK3588 weight compression with the original converters and calibration."""
-from pathlib import Path
-import os
-import runpy
-import shutil
-import sys
-
-from rknn.api import RKNN
-
-workspace = Path.home() / "hanzos_workspace"
-matrix = workspace / "nvr-matrix-20261107"
-zoo = workspace / "rknn_model_zoo"
-exports = workspace / "yolo-rknn"
-source, precision = sys.argv[1:]
-output = exports / "optimization/rk3588/yolov8n" / source / precision
-output.parent.mkdir(parents=True, exist_ok=True)
-config = RKNN.config
-
-
-def compress(self, *args, **kwargs):
-    return config(self, *args, **dict(kwargs, compress_weight=True))
-
-
-RKNN.config = compress
-
-if source == "rockchip":
-    original_precision = {"fp16": "fp", "int8": "i8"}[precision]
-    original = exports / "rknn/rk3588/yolov8/yolov8n" / original_precision
-    example = zoo / "examples/yolov8/python"
-    output.mkdir()
-    os.chdir(example)
-    converter = example / "convert.py"
-    sys.argv = [str(converter), str(exports / "onnx/yolov8/yolov8n.onnx"), "rk3588",
-                original_precision, str(output / "model.rknn")]
-    runpy.run_path(str(converter), run_name="__main__")
-    shutil.copy2(original / "metadata.yaml", output)
-elif source == "ultralytics":
-    converter = matrix / "tools/convert-model.py"
-    sys.path.insert(0, str(converter.parent))
-    sys.argv = [str(converter), str(matrix / "weights/yolov8n.pt"), "--chip", "rk3588",
-                "--precision", precision, "--output", str(output)]
-    if precision == "int8":
-        sys.argv += ["--data", str(matrix / "calibration/coco128.yaml")]
-    runpy.run_path(str(converter), run_name="__main__")
-else:
-    raise ValueError(source)
-
-assert (output / "model.rknn").stat().st_size > 0