diff --git a/docs/introduction/installation.md b/docs/introduction/installation.md
index 8831a8ba..3610b0e8 100644
--- a/docs/introduction/installation.md
+++ b/docs/introduction/installation.md
@@ -88,9 +88,10 @@ You can find CUDA installers on [NVIDIA CUDA Toolkit Archive Website](https://de
 - Install [SSCMA](https://github.com/Seeed-Studio/ModelAssistant) deps
 
 ```sh
+pip3 install openmim && \
 pip3 install -r requirements/base.txt && \
 mim install -r requirements/mmlab.txt && \
-mim install -e .
+pip3 install -e . --no-deps
 ```
 
 ### Step 4 - Install Extra Dependencies (Optional)
@@ -124,16 +125,18 @@ Or you can do the configuration manually using Conda's configuration file.
 conda env create -n sscma -f environment.yml && \
 conda activate sscma && \
 pip3 install -r requirements/inference.txt -r requirements/export.txt -r requirements/tests.txt && \
+pip3 install openmim && \
 mim install -r requirements/mmlab.txt && \
-mim install -e .
+pip3 install -e . --no-deps
 ```
 
 ```sh [GPU (CUDA)]
 conda env create -n sscma -f environment_cuda.yml && \
 conda activate sscma && \
 pip3 install -r requirements/inference.txt -r requirements/export.txt -r requirements/tests.txt && \
+pip3 install openmim && \
 mim install -r requirements/mmlab.txt && \
-mim install -e .
+pip3 install -e . --no-deps
 ```
 
 :::
diff --git a/docs/zh_cn/introduction/installation.md b/docs/zh_cn/introduction/installation.md
index 3ae151fb..cf6ba712 100644
--- a/docs/zh_cn/introduction/installation.md
+++ b/docs/zh_cn/introduction/installation.md
@@ -88,9 +88,10 @@ conda activate sscma
 - 安装 [SSCMA](https://github.com/Seeed-Studio/ModelAssistant) 依赖项
 
 ```sh
+pip3 install openmim && \
 pip3 install -r requirements/base.txt && \
 mim install -r requirements/mmlab.txt && \
-mim install -e .
+pip3 install -e . --no-deps
 ```
 
 ### 第 4 步 - 安装额外依赖项（可选）
@@ -124,16 +125,18 @@ bash scripts/setup_linux.sh
 conda env create -n sscma -f environment.yml && \
 conda activate sscma && \
 pip3 install -r requirements/inference.txt -r requirements/export.txt -r requirements/tests.txt && \
+pip3 install openmim && \
 mim install -r requirements/mmlab.txt && \
-mim install -e .
+pip3 install -e . --no-deps
 ```
 
 ```sh [GPU（CUDA）]
 conda env create -n sscma -f environment_cuda.yml && \
 conda activate sscma && \
 pip3 install -r requirements/inference.txt -r requirements/export.txt -r requirements/tests.txt && \
+pip3 install openmim && \
 mim install -r requirements/mmlab.txt && \
-mim install -e .
+pip3 install -e . --no-deps
 ```
 
 :::
diff --git a/notebooks/Google-Colab-SWFIT-YOLO-A1101-Example.ipynb b/notebooks/Google-Colab-SWFIT-YOLO-A1101-Example.ipynb
index dea1ebeb..9bc5f961 100644
--- a/notebooks/Google-Colab-SWFIT-YOLO-A1101-Example.ipynb
+++ b/notebooks/Google-Colab-SWFIT-YOLO-A1101-Example.ipynb
@@ -52,13 +52,8 @@
       },
       "outputs": [],
       "source": [
-        "# Ethos-U-Vela need to be installed this way, or SSCMA does not work anymore...\n",
-        "!git clone https://review.mlplatform.org/ml/ethos-u/ethos-u-vela.git\n",
-        "%cd ethos-u-vela\n",
-        "!pip install .\n",
-        "%cd..\n",
-        "!git clone https://github.com/Seeed-Studio/SSCMA.git  # currently we're using experimental 2.0 version branch\n",
-        "%cd /content/SSCMA"
+        "!git clone https://github.com/Seeed-Studio/ModelAssistant.git -b 2.0.0\n",
+        "%cd ModelAssistant"
       ]
     },
     {
@@ -67,7 +62,7 @@
         "id": "LWAE--J9sAmW"
       },
       "source": [
-        "**Step 1:** Install python third-party library"
+        "**Step 1:** Install the dependencies. The setup script installs a modern PyTorch-compatible dependency stack and compiles [MMCV](https://github.com/open-mmlab/mmcv) from source (there are no prebuilt MMCV wheels for recent PyTorch/Python versions), which takes about 10-15 minutes on Colab."
       ]
     },
     {
@@ -78,7 +73,7 @@
       },
       "outputs": [],
       "source": [
-        "!pip install ."
+        "!bash scripts/setup_colab.sh"
       ]
     },
     {
diff --git a/pyproject.toml b/pyproject.toml
index e107eeb1..06356d00 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,3 +1,10 @@
+[build-system]
+# PEP 517/660 build via setuptools. Without this, pip falls back to the
+# deprecated legacy `setup.py egg_info`/`setup.py develop` path, which is
+# removed in newer pip releases and fails on modern environments (e.g. Colab).
+requires = ["setuptools>=64,<81", "wheel"]
+build-backend = "setuptools.build_meta"
+
 [tool.isort]
 profile = "black"
 
diff --git a/requirements/base.txt b/requirements/base.txt
index 3cd67992..2acf3dae 100644
--- a/requirements/base.txt
+++ b/requirements/base.txt
@@ -5,7 +5,12 @@ libusb1
 
 # sensor
 cbor
-numpy>=1.23.0,<2.0.0
+# numpy < 2.3: numba (preinstalled on Colab) requires numpy < 2.3, while
+# everything else in a modern image (opencv 5, jax, ml-dtypes, tensorflow
+# 2.20, h5py, keras) requires numpy >= 2. A numpy < 2.0 pin forces a numpy
+# 1.26 source build on Python 3.13 and makes pip downgrade half of the
+# preinstalled stack (opencv, keras, ml-dtypes, h5py, vela).
+numpy>=1.23.0,<2.3.0
 
 
 
@@ -13,8 +18,11 @@ numpy>=1.23.0,<2.0.0
 opencv-python>=4.9.0.80
 
 
-# openmmlab package manager
-openmim>=0.3.7
+# NOTE: openmim is intentionally NOT listed here. It pulls in `openxlab`,
+# which hard-pins `setuptools~=60.2.0` - a version too old to build anything
+# on Python >= 3.12 (pkgutil.ImpImporter was removed). If you need the `mim`
+# command, install it separately with `pip install openmim` and mind your
+# setuptools version afterwards.
 packaging>=23.1
 pandas>=2.0.0
 pillow>=9.4.0
diff --git a/requirements/export.txt b/requirements/export.txt
index 68a357f9..90ae5bb4 100644
--- a/requirements/export.txt
+++ b/requirements/export.txt
@@ -5,4 +5,12 @@ TinyNeuralNetwork @ https://files.seeedstudio.com/sscma/library/TinyNeuralNetwor
 pnnx
 
 # vela
-ethos-u-vela
\ No newline at end of file
+# NOTE: pinned to a range with prebuilt wheels for Python >= 3.12.
+# ethos-u-vela <= 4.1.0 ships sdists only and its legacy setup.py fails to
+# build on Python >= 3.12 (needs flatbuffers at build time). Worse, vela
+# 3.7.0 declares NO dependencies at all, so pip's resolver can always
+# backtrack to it when anything else conflicts - silently turning a
+# dependency conflict into a source build that then fails.
+# 5.1.0 is verified with tools/export.py and the vela CLI flags used in the
+# docs/notebooks; bump the ceiling after re-verifying.
+ethos-u-vela>=4.2.0,<=5.1.0
\ No newline at end of file
diff --git a/requirements/inference.txt b/requirements/inference.txt
index ef713162..a0ab9f1a 100644
--- a/requirements/inference.txt
+++ b/requirements/inference.txt
@@ -1,7 +1,13 @@
 libusb1>=3.0.0
-pnnx==0.0.4
+# NOTE: keep unpinned. The previous pin (==0.0.4) resolved to an ancient
+# placeholder release, and it conflicts with the unpinned pnnx in
+# requirements/export.txt.
+pnnx
 ncnn>=1.0.20230517
 onnx>=1.14.0
+# torch.onnx.export uses the dynamo exporter by default since PyTorch 2.9,
+# which requires onnxscript
+onnxscript>=0.1.0
 onnxmltools>=1.11.2
 onnxruntime>=1.15.1
 onnxsim>=0.4.33
diff --git a/requirements/mmlab.txt b/requirements/mmlab.txt
index a022d18a..020f38f0 100644
--- a/requirements/mmlab.txt
+++ b/requirements/mmlab.txt
@@ -1,5 +1,11 @@
-# use openmim to install
-mmcls>=1.0.0.rc6
-mmcv-full<=2.1.0
-mmdet>=3.0.0, <3.1.0 # mmyolo currently does not support mmdet 3.1.0
-mmengine>=0.8.2
+# OpenMMLab dependencies
+# NOTE: mmcv 2.2.0 is the last mmcv release and the only one that compiles
+# against recent PyTorch (>= 2.6). There are no prebuilt mmcv wheels for
+# recent PyTorch/Python combinations, so mmcv must be built from source
+# (scripts/setup_colab.sh does this). mmdet 3.0.x / mmcls 1.0.0rc6 hard-code
+# an mmcv < 2.1.0 ceiling at import time; use scripts/patch_mmlab_versions.py
+# to relax that assertion after installation.
+mmcls>=1.0.0rc6
+mmcv>=2.2.0,<=2.2.0
+mmdet>=3.0.0,<3.1.0
+mmengine>=0.8.2,<1.0.0
diff --git a/requirements/pytorch_cpu.txt b/requirements/pytorch_cpu.txt
index 1052b6e9..62af8902 100644
--- a/requirements/pytorch_cpu.txt
+++ b/requirements/pytorch_cpu.txt
@@ -1,5 +1,9 @@
 -i https://download.pytorch.org/whl/cpu
 
-torch<=2.0.1
-torchaudio<=2.0.2
-torchvision<=0.15.2
+# NOTE: no upper version bound on purpose. The previous ceiling (torch<=2.0.1)
+# has no wheels for Python >= 3.12 and made the whole installation fail.
+# torch/torchvision/torchaudio versions must stay mutually compatible;
+# on Google Colab the preinstalled versions are used as-is.
+torch>=2.1.0
+torchaudio>=2.1.0
+torchvision>=0.16.0
diff --git a/requirements/pytorch_cuda.txt b/requirements/pytorch_cuda.txt
index 990e36a2..da057cce 100644
--- a/requirements/pytorch_cuda.txt
+++ b/requirements/pytorch_cuda.txt
@@ -1,5 +1,9 @@
--i https://download.pytorch.org/whl/cu118
-
-torch<=2.0.1
-torchaudio<=2.0.2
-torchvision<=0.15.2
+# NOTE: no upper version bound on purpose. The previous ceiling (torch<=2.0.1)
+# has no wheels for Python >= 3.12 and made the whole installation fail.
+# Modern PyPI torch wheels already bundle the CUDA runtime, so no custom
+# index URL is required anymore. torch/torchvision/torchaudio versions must
+# stay mutually compatible; on Google Colab the preinstalled versions are
+# used as-is.
+torch>=2.1.0
+torchaudio>=2.1.0
+torchvision>=0.16.0
diff --git a/scripts/patch_mmlab_versions.py b/scripts/patch_mmlab_versions.py
new file mode 100755
index 00000000..1cbcc5aa
--- /dev/null
+++ b/scripts/patch_mmlab_versions.py
@@ -0,0 +1,144 @@
+#!/usr/bin/env python3
+# Copyright (c) Seeed Technology Co.,Ltd. All rights reserved.
+"""Relax the hard-coded MMCV upper-version assertions of mmdet/mmcls.
+
+mmdet 3.0.x and mmcls 1.0.0rc6 assert ``mmcv < 2.1.0`` at import time.
+We deliberately use mmcv 2.2.0 - the final mmcv release and the only one
+that compiles against recent PyTorch (>= 2.6) - so the assertion must be
+relaxed in the *installed* packages.
+
+The patch is applied in-place to the installed ``__init__.py`` files and
+fails loudly if the expected pattern is not found (e.g. the package
+versions drifted), instead of silently doing nothing.
+
+Usage:
+    python scripts/patch_mmlab_versions.py            # patch
+    python scripts/patch_mmlab_versions.py --verify   # patch + import check
+"""
+
+import argparse
+import importlib.util
+import os
+import re
+import sys
+
+# packages -> new mmcv maximum version (mmcv 3.x does not exist, so this
+# effectively disables the upper bound while remaining an explicit bound)
+PACKAGES = {
+    'mmdet': '3.0.0',
+    'mmcls': '3.0.0',
+}
+
+PATTERN = re.compile(r"mmcv_maximum_version\s*=\s*['\"][\d.]+['\"]")
+
+
+def patch_package(name: str, new_maximum: str) -> bool:
+    spec = importlib.util.find_spec(name)
+    if spec is None or not spec.submodule_search_locations:
+        print(f'[SKIP] {name} is not installed')
+        return False
+
+    init_file = os.path.join(spec.submodule_search_locations[0], '__init__.py')
+    with open(init_file, 'r', encoding='utf-8') as f:
+        content = f.read()
+
+    replacement = f"mmcv_maximum_version = '{new_maximum}'"
+    patched, count = PATTERN.subn(replacement, content)
+
+    if count == 0:
+        if f"mmcv_maximum_version = '{new_maximum}'" in content:
+            print(f'[OK]   {name}: already patched ({init_file})')
+            return True
+        print(f'[FAIL] {name}: no mmcv_maximum_version found in {init_file}')
+        print('       The installed version may have changed - please check it manually.')
+        return False
+
+    with open(init_file, 'w', encoding='utf-8') as f:
+        f.write(patched)
+    print(f'[OK]   {name}: mmcv_maximum_version -> {new_maximum} ({init_file})')
+    return True
+
+
+ADAFACTOR_OLD = "        OPTIMIZERS.register_module(name='Adafactor', module=Adafactor)\n        transformer_optimizers.append('Adafactor')"
+ADAFACTOR_NEW = (
+    "        if 'Adafactor' not in OPTIMIZERS:\n"
+    "            OPTIMIZERS.register_module(name='Adafactor', module=Adafactor)\n"
+    "            transformer_optimizers.append('Adafactor')"
+)
+
+
+def patch_mmengine_adafactor() -> bool:
+    """Guard mmengine's transformers-Adafactor registration.
+
+    mmengine (<= 0.10.7, including the current upstream) unconditionally
+    registers transformers' Adafactor when transformers is installed. Since
+    torch >= 2.9 ships torch.optim.Adafactor - already registered under the
+    same name - importing mmengine.optim crashes with
+    ``KeyError: 'Adafactor is already registered in optimizer ...'`` whenever
+    both torch >= 2.9 and transformers are present (both are preinstalled on
+    Colab).
+    """
+    spec = importlib.util.find_spec('mmengine')
+    if spec is None or not spec.submodule_search_locations:
+        print('[SKIP] mmengine is not installed')
+        return False
+
+    builder_file = os.path.join(
+        spec.submodule_search_locations[0], 'optim', 'optimizer', 'builder.py'
+    )
+    with open(builder_file, 'r', encoding='utf-8') as f:
+        content = f.read()
+
+    if ADAFACTOR_NEW in content:
+        print(f'[OK]   mmengine: Adafactor guard already present ({builder_file})')
+        return True
+    if ADAFACTOR_OLD not in content:
+        print(f'[FAIL] mmengine: Adafactor registration pattern not found in {builder_file}')
+        print('       The installed mmengine version may have changed - please check it manually.')
+        return False
+
+    with open(builder_file, 'w', encoding='utf-8') as f:
+        f.write(content.replace(ADAFACTOR_OLD, ADAFACTOR_NEW))
+    print(f'[OK]   mmengine: guarded Adafactor registration ({builder_file})')
+    return True
+
+
+def verify_imports() -> bool:
+    ok = True
+    for name in ('mmcv', 'mmdet', 'mmcls', 'mmengine'):
+        try:
+            module = __import__(name)
+            print(f'[OK]   import {name} {module.__version__}')
+        except Exception as exc:  # noqa: BLE001
+            print(f'[FAIL] import {name}: {exc}')
+            ok = False
+    if ok:
+        try:
+            # triggers the optimizer registration code paths
+            from mmengine.optim.optimizer import OPTIMIZERS  # noqa: F401
+
+            print('[OK]   mmengine optimizer registry builds')
+        except Exception as exc:  # noqa: BLE001
+            print(f'[FAIL] mmengine optimizer registry: {exc}')
+            ok = False
+    return ok
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument('--verify', action='store_true', help='also verify the patched packages can be imported')
+    args = parser.parse_args()
+
+    results = [patch_package(name, maximum) for name, maximum in PACKAGES.items()]
+    results.append(patch_mmengine_adafactor())
+    if not all(results):
+        sys.exit(1)
+
+    if args.verify and not verify_imports():
+        sys.exit(1)
+
+    print('Done.')
+
+
+if __name__ == '__main__':
+    main()
diff --git a/scripts/setup_colab.sh b/scripts/setup_colab.sh
index 97f70d53..f9e2aa29 100755
--- a/scripts/setup_colab.sh
+++ b/scripts/setup_colab.sh
@@ -1,8 +1,17 @@
 #!/bin/bash
+# Setup script for Google Colab (also works on plain Linux with NVIDIA GPU).
+#
+# Order matters:
+#   1. torch/torchvision/torchaudio must be installed FIRST and must not be
+#      replaced afterwards - the mmcv extension is compiled against them.
+#      (Some dependencies, e.g. pyvww, pull an unpinned `torchvision`, whose
+#      latest release pins an exact torch version and would silently swap it.)
+#   2. numpy is pinned (< 2.3, for numba) BEFORE anything is compiled.
+#   3. mmcv is compiled from source LAST, after all pip installs are done.
+set -e
 
-
-# configs
-CUDA_AVAILABLE="$(command -v nvidia-smi)"
+# always operate from the repository root, regardless of the caller's cwd
+cd "$(dirname "${BASH_SOURCE[0]}")/.."
 
 
 # ansi colors
@@ -11,38 +20,142 @@ GREEN='\033[032m'
 BLUE='\033[034m'
 RST='\033[m'
 
+
 # check cuda
 echo -en "Checking if CUDA available... "
-if [ ! "${CUDA_AVAILABLE}" ]; then
+if [ ! "$(command -v nvidia-smi)" ]; then
     echo -en "${RED}Not found!${RST}\n"
-    echo -en "Please enable GPU Runtime${RST}\n"
+    echo -en "Please enable the GPU runtime (Runtime -> Change runtime type)${RST}\n"
     exit 1
 else
     echo -en "${GREEN}OK${RST}\n"
 fi
 
-# limit torch version
-pip install torch==2.0.0 torchvision==0.15.1 torchaudio==2.0.1
-
-# install base deps
-echo -en "Installing base deps... "
-pip install -r requirements/base.txt -r requirements/inference.txt -r requirements/export.txt -r requirements/tests.txt
 
-if [ "$?" != 0 ]; then
-    echo -en "Install base deps failed... ${RED}Exiting${RST}\n"
-    exit 1
+# step 1: ensure a modern pytorch stack; on Colab the preinstalled one is used
+echo -en "${BLUE}Ensuring PyTorch stack... ${RST}\n"
+if ! python -c "import torch, torchvision, torchaudio" > /dev/null 2>&1; then
+    pip install torch torchvision torchaudio
 fi
+python -c "import torch, torchvision, torchaudio; print(f'torch={torch.__version__} torchvision={torchvision.__version__} torchaudio={torchaudio.__version__}')"
 
+# Pin the torch stack for every subsequent pip install: pip's resolver does
+# not respect locally-versioned (+cpu/+cuXXX) installed packages and would
+# otherwise happily replace them (e.g. pnnx depends on plain `torch`), which
+# breaks the mmcv build and the CUDA/driver match.
+CONSTRAINTS_FILE="$(mktemp)"
+trap 'rm -f "${CONSTRAINTS_FILE}"' EXIT
+python -c "import torch, torchvision, torchaudio; print(f'torch=={torch.__version__}'); print(f'torchvision=={torchvision.__version__}'); print(f'torchaudio=={torchaudio.__version__}')" > "${CONSTRAINTS_FILE}"
+cat "${CONSTRAINTS_FILE}"
 
-# openmim install deps
-echo -en "Installing OpenMIM deps... \n"
-mim install -r requirements/mmlab.txt && \
-mim install mmcv==2.0.0 && \
-mim install -e .
-if [ "$?" != 0 ]; then
-    echo -en "OpenMIM install deps failed... ${RED}Exiting${RST}\n"
-    exit 1
-fi
+
+# step 2: build tools and pinned numpy (must happen before compiling mmcv)
+echo -en "${BLUE}Installing build tools... ${RST}\n"
+# setuptools<81: still ships the distutils shim required by TinyNeuralNetwork
+pip install "numpy>=1.23.0,<2.3.0" "setuptools>=49.4.0,<81" Cython ninja wheel packaging
+
+
+# step 3: python dependencies (with the torch stack constrained, nothing here
+# can pull a different torch version)
+echo -en "${BLUE}Installing base deps... ${RST}\n"
+pip install -c "${CONSTRAINTS_FILE}" -r requirements/base.txt -r requirements/inference.txt -r requirements/export.txt -r requirements/tests.txt
+
+
+# step 4: OpenMMLab deps (pip metadata of mmdet/mmcls does not pull mmcv, so
+# this cannot interfere with the mmcv source build below)
+echo -en "${BLUE}Installing OpenMMLab deps... ${RST}\n"
+pip install -c "${CONSTRAINTS_FILE}" "mmengine>=0.8.2,<1.0.0" "mmdet>=3.0.0,<3.1.0" "mmcls>=1.0.0rc6"
+
+# vela: wheel-only. Sdist releases (<= 4.1.0) fail to build on Python >= 3.12
+# (their setup.py imports flatbuffers at build time), and the metadata-less
+# vela 3.7.0 is pip's favorite backtracking target on conflict-heavy
+# environments like Colab.
+pip install --only-binary ethos-u-vela "ethos-u-vela>=4.2.0,<=5.1.0"
+
+
+# step 5: build mmcv from source - there are no prebuilt wheels for recent
+# PyTorch/Python versions. Compiling with CUDA ops takes ~10-15 min on Colab.
+# MAX_JOBS is capped at 4 by default: each nvcc job needs ~1-2 GB RAM and
+# Colab instances only have ~12 GB. Override with MAX_JOBS=N on bigger hosts.
+#
+# The sdist is downloaded and patched BEFORE building: mmcv 2.2.0's setup.py
+# get_version() does exec(...) at function scope and reads locals(), which no
+# longer works on Python >= 3.13 (PEP 667) and kills the build with
+# "KeyError: '__version__'" at the metadata step. It cannot be fetched with
+# pip (neither pip install nor pip download): pip ALWAYS builds the sdist's
+# metadata first - i.e. runs the broken setup.py before we can patch it - so
+# the sdist is fetched from PyPI out-of-band (with sha256 verification).
+echo -en "${BLUE}Building mmcv 2.2.0 from source (this takes a while)... ${RST}\n"
+MMCV_BUILD_DIR="$(mktemp -d)"
+trap 'rm -rf "${CONSTRAINTS_FILE}" "${MMCV_BUILD_DIR}"' EXIT
+read -r MMCV_URL MMCV_SHA256 < <(python - <<'EOF'
+import json
+import urllib.request
+
+with urllib.request.urlopen('https://pypi.org/pypi/mmcv/2.2.0/json') as r:
+    data = json.load(r)
+sdist = next(u for u in data['urls'] if u['packagetype'] == 'sdist')
+print(sdist['url'], sdist['digests']['sha256'])
+EOF
+)
+curl -fSL --retry 3 -o "${MMCV_BUILD_DIR}/mmcv-2.2.0.tar.gz" "${MMCV_URL}"
+echo "${MMCV_SHA256}  ${MMCV_BUILD_DIR}/mmcv-2.2.0.tar.gz" | sha256sum -c -
+tar xzf "${MMCV_BUILD_DIR}/mmcv-2.2.0.tar.gz" -C "${MMCV_BUILD_DIR}"
+python - "${MMCV_BUILD_DIR}/mmcv-2.2.0/setup.py" <<'EOF'
+import sys
+
+path = sys.argv[1]
+src = open(path).read()
+old = (
+    "    with open(version_file, encoding='utf-8') as f:\n"
+    "        exec(compile(f.read(), version_file, 'exec'))\n"
+    "    return locals()['__version__']"
+)
+new = (
+    "    namespace = {}\n"
+    "    with open(version_file, encoding='utf-8') as f:\n"
+    "        exec(compile(f.read(), version_file, 'exec'), namespace)\n"
+    "    return namespace['__version__']"
+)
+if old not in src:
+    if 'namespace' in src and "namespace['__version__']" in src:
+        print('mmcv setup.py already py3.13-compatible, nothing to patch')
+        sys.exit(0)
+    print('ERROR: could not find get_version() exec pattern in mmcv setup.py -')
+    print('mmcv may have changed; please report this.')
+    sys.exit(1)
+open(path, 'w').write(src.replace(old, new))
+print('patched mmcv setup.py get_version() for Python >= 3.13')
+EOF
+MMCV_WITH_OPS=1 MAX_JOBS="${MAX_JOBS:-4}" pip install --no-build-isolation --no-cache-dir "${MMCV_BUILD_DIR}/mmcv-2.2.0"
+
+
+# step 6: relax the mmcv < 2.1.0 assertion hard-coded in mmdet/mmcls
+echo -en "${BLUE}Patching OpenMMLab version checks... ${RST}\n"
+python scripts/patch_mmlab_versions.py --verify
+
+
+# step 7: install sscma itself (deps were installed above; --no-deps avoids
+# re-resolving legacy pins)
+echo -en "${BLUE}Installing sscma... ${RST}\n"
+pip install --no-deps -e .
+
+
+# step 8: smoke test
+echo -en "${BLUE}Running smoke test... ${RST}\n"
+python - <<'EOF'
+import torch
+import mmcv
+import mmdet
+import mmcls
+import mmengine
+import sscma.datasets, sscma.engine, sscma.evaluation, sscma.models, sscma.visualization
+from mmcv.ops import nms
+
+keep = nms(torch.rand(10, 4), torch.rand(10), 0.5)
+print(f'sscma={sscma.__version__} mmcv={mmcv.__version__} mmdet={mmdet.__version__} '
+      f'mmcls={mmcls.__version__} mmengine={mmengine.__version__} torch={torch.__version__}')
+print('mmcv ops (nms) work:', len(keep[0]) > 0)
+EOF
 
 echo -en "Finished setup... ${GREEN}OK${RST}\n"
-exit 0
diff --git a/scripts/setup_docker.sh b/scripts/setup_docker.sh
index 6bf4f3c6..09e8544e 100755
--- a/scripts/setup_docker.sh
+++ b/scripts/setup_docker.sh
@@ -49,9 +49,13 @@ fi
 
 
 # openmim install deps
+# NOTE: openmim is no longer part of requirements/base.txt (it drags in a
+# setuptools pin that breaks Python >= 3.12); install it explicitly and keep
+# a working setuptools afterwards.
 echo -en "Installing OpenMIM deps... \n"
+${PYTHON_PATH} -m pip install openmim "setuptools>=69,<81" && \
 ${PYTHON_PATH} -m mim install -r requirements/mmlab.txt && \
-${PYTHON_PATH} -m mim install -e .
+${PYTHON_PATH} -m pip install -e . --no-deps
 if [ "$?" != 0 ]; then
     echo -en "OpenMIM install deps failed... ${RED}Exiting${RST}\n"
     exit 1
diff --git a/scripts/setup_linux.sh b/scripts/setup_linux.sh
index 795c1f72..cfcf62c4 100755
--- a/scripts/setup_linux.sh
+++ b/scripts/setup_linux.sh
@@ -67,9 +67,13 @@ fi
 
 
 # openmim install deps
+# NOTE: openmim is no longer part of requirements/base.txt (it drags in a
+# setuptools pin that breaks Python >= 3.12); install it explicitly and keep
+# a working setuptools afterwards.
 echo -en "Installing OpenMIM deps... \n"
+conda run -n sscma pip install openmim "setuptools>=69,<81" && \
 conda run -n sscma mim install -r requirements/mmlab.txt && \
-conda run -n sscma mim install -e .
+conda run -n sscma pip install -e . --no-deps
 if [ "$?" != 0 ]; then
     echo -en "OpenMIM install deps failed... ${RED}Exiting${RST}\n"
     exit 1
diff --git a/setup.py b/setup.py
index 840ef7c9..5128e2c0 100644
--- a/setup.py
+++ b/setup.py
@@ -15,10 +15,13 @@ def readme():
 
 
 def get_version():
+    # NOTE: exec into an explicit namespace dict - writing to function
+    # locals() via exec no longer works on Python >= 3.13
+    namespace = {}
     version_file = 'sscma/version.py'
     with open(version_file, 'r', encoding='utf-8') as f:
-        exec(compile(f.read(), version_file, 'exec'))
-    return locals()['__version__']
+        exec(compile(f.read(), version_file, 'exec'), namespace)
+    return namespace['__version__']
 
 
 def parse_line(line: str):
@@ -47,7 +50,17 @@ def parse_requirements(fpath: str = ''):
             line = line.strip()
             if line and not line.startswith('#'):
                 if line.startswith('-r'):
-                    res = parse_requirements(line.split(' ')[-1])
+                    target = line.split(' ')[-1]
+                    # OpenMMLab packages (mmcv/mmdet/mmcls/mmengine) are
+                    # environment-sensitive: mmcv has no prebuilt wheels for
+                    # recent PyTorch/Python and must be built from source with
+                    # MMCV_WITH_OPS=1. They must NOT end up in install_requires,
+                    # otherwise `pip install .` would silently build a CPU-only
+                    # (or legacy mmcv-full) mmcv and break the installation.
+                    # Install them with scripts/setup_colab.sh or manually.
+                    if target.endswith('mmlab.txt'):
+                        continue
+                    res = parse_requirements(target)
                     reqs += res[0]
                     index += res[1]
                 elif line.startswith('-i'):
diff --git a/sscma/datasets/utils/download.py b/sscma/datasets/utils/download.py
index 447c98d6..2d4b9fe3 100644
--- a/sscma/datasets/utils/download.py
+++ b/sscma/datasets/utils/download.py
@@ -158,7 +158,7 @@ def check_file(path, store_dir=None, data_name=None):
             download_dir = (
                 f"{os.environ['HOME']}/datasets"
                 if platform.system() == 'Linux' and not store_dir
-                else 'D:\datasets'
+                else r'D:\datasets'
                 if not store_dir
                 else store_dir
             )
@@ -175,7 +175,7 @@ def check_file(path, store_dir=None, data_name=None):
             download_dir = (
                 f"{os.environ['HOME']}/datasets"
                 if platform.system() == 'Linux' and not store_dir
-                else 'D:\datasets'
+                else r'D:\datasets'
                 if not store_dir
                 else store_dir
             )
diff --git a/tools/export.py b/tools/export.py
index bf22effb..ce92ba6c 100644
--- a/tools/export.py
+++ b/tools/export.py
@@ -6,6 +6,13 @@
 import tempfile
 
 import torch
+
+# PyTorch >= 2.6 changed the default of `torch.load` to `weights_only=True`,
+# which rejects checkpoints containing non-tensor objects (e.g. NumPy arrays
+# in `meta`) and breaks mmengine's checkpoint loading. Restore the previous
+# behavior for our trusted checkpoints; can be overridden from outside.
+os.environ.setdefault('TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD', '1')
+
 from tqdm import tqdm
 
 current_path = osp.dirname(osp.abspath(__file__))
@@ -291,6 +298,15 @@ def export_pnnx(args, model):
     import sys
 
     import pnnx
+
+    if not hasattr(pnnx, 'wrapper'):
+        raise RuntimeError(
+            f'The installed pnnx=={getattr(pnnx, "__version__", "unknown")} no longer provides '
+            '"pnnx.wrapper" (removed in pnnx >= 20231211, which also switched from TorchScript to '
+            'torch.export). The "pnnx" export target is currently incompatible with modern pnnx '
+            'releases - please export with --targets tflite/onnx/vela instead.'
+        )
+
     from pnnx.wrapper import convert_inputshape_to_cmd
 
     model.eval()
@@ -497,13 +513,27 @@ def main():
     model = runner.model.to(device=args.device)
     loader = runner.val_dataloader
 
+    failed_targets = []
     for target in args.targets:
-        if target == 'tflite':
-            export_tflite(args, model, loader)
-        elif target == 'onnx':
-            export_onnx(args, model)
-        elif target == 'pnnx':
-            export_pnnx(args, model)
+        # Export targets are independent: a failure in one (e.g. pnnx, whose
+        # upstream package changed its API) must not discard the artifacts
+        # already produced by the others (e.g. tflite/vela).
+        try:
+            if target == 'tflite':
+                export_tflite(args, model, loader)
+            elif target == 'onnx':
+                export_onnx(args, model)
+            elif target == 'pnnx':
+                export_pnnx(args, model)
+        except Exception as exc:
+            failed_targets.append(target)
+            print(f'ERROR: exporting target "{target}" failed: {exc}')
+
+    if failed_targets:
+        raise RuntimeError(
+            f'Export failed for target(s): {failed_targets}. '
+            'Artifacts for the remaining targets were exported successfully.'
+        )
 
 
 if __name__ == '__main__':
diff --git a/tools/inference.py b/tools/inference.py
index 00430aba..5638dedc 100644
--- a/tools/inference.py
+++ b/tools/inference.py
@@ -7,6 +7,12 @@
 
 import torch
 
+# PyTorch >= 2.6 changed the default of `torch.load` to `weights_only=True`,
+# which rejects checkpoints containing non-tensor objects (e.g. NumPy arrays
+# in `meta`) and breaks mmengine's checkpoint loading. Restore the previous
+# behavior for our trusted checkpoints; can be overridden from outside.
+os.environ.setdefault('TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD', '1')
+
 current_path = osp.dirname(osp.abspath(__file__))
 sys.path.append(osp.dirname(current_path))
 
diff --git a/tools/train.py b/tools/train.py
index 8d755b7b..33e4b4f3 100644
--- a/tools/train.py
+++ b/tools/train.py
@@ -7,6 +7,12 @@
 
 import torch
 
+# PyTorch >= 2.6 changed the default of `torch.load` to `weights_only=True`,
+# which rejects checkpoints containing non-tensor objects (e.g. NumPy arrays
+# in `meta`) and breaks mmengine's checkpoint loading. Restore the previous
+# behavior for our trusted checkpoints; can be overridden from outside.
+os.environ.setdefault('TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD', '1')
+
 current_path = osp.dirname(osp.abspath(__file__))
 sys.path.append(osp.dirname(current_path))
 
diff --git a/tools/utils/quant_read.py b/tools/utils/quant_read.py
index 883ec781..813f2596 100644
--- a/tools/utils/quant_read.py
+++ b/tools/utils/quant_read.py
@@ -1,12 +1,45 @@
 # Copyright (c) Seeed Technology Co.,Ltd. All rights reserved.
 import os
+import random
 
 import numpy as np
 from onnxruntime.quantization import CalibrationDataReader
 from PIL import Image
 from torchvision.transforms import Compose, Grayscale, Resize, ToTensor
 
-img_format = ['.JPG', '.PNG', '.JPEG']
+IMG_EXTENSIONS = ('.jpg', '.jpeg', '.png', '.gif', '.bmp', '.tiff', '.webp')
+
+
+def find_and_sample_images(folder_path, limit=10000, sample_size=100):
+    """Recursively find images in ``folder_path`` and randomly sample them.
+
+    Backported from main (dea366b, issue #294): a flat ``os.listdir`` with a
+    narrow extension filter silently finds zero images when the calibration
+    folder contains subdirectories or other image formats, which then
+    produces a broken quantized model without any error.
+    """
+    image_files = []
+
+    if not os.path.isdir(folder_path):
+        raise ValueError(f"The provided image path '{folder_path}' is not a valid directory.")
+
+    for root, _, files in os.walk(folder_path):
+        for file in files:
+            if os.path.splitext(file)[1].lower() in IMG_EXTENSIONS:
+                image_files.append(os.path.join(root, file))
+                if len(image_files) >= limit:
+                    break
+        if len(image_files) >= limit:
+            break
+
+    found = len(image_files)
+    if found < sample_size:
+        if found == 0:
+            raise ValueError(f"No images found in the directory '{folder_path}'.")
+        print(f"Warning: Found only {found} images, which is less than the requested sample size of {sample_size}.")
+        sample_size = found
+
+    return random.sample(image_files, sample_size)
 
 
 class Quan_Reader(CalibrationDataReader):
@@ -22,10 +55,7 @@ def __init__(self, images_folder, size, input_name, batch_size=1) -> None:
         self.init()
 
     def init(self):
-        file_ls = os.listdir(self.images_folder)
-        self.file_ls = iter(
-            [os.path.join(self.images_folder, i) for i in file_ls if os.path.splitext(i)[-1].upper() in img_format]
-        )
+        self.file_ls = iter(find_and_sample_images(self.images_folder, limit=10000, sample_size=10000))
 
     def get_next(self) -> dict:
         try: