gimini: 初學者，使用限制: 4張/天，輸出圖片1K
Google AI Studio: 進階使用者，輸出圖片4K，顯示比例設定16:9，須付費綁定API Key
LMArena: 免費，初學者，使用限制: 4張/小時
Gemini炸裂更新，Nano banana Pro 20個瘋狂應用，YouTube縮圖、IP形象、知識圖解、簡報，中文友好，4K高清（內附免費使用方法）
- 11月 28 週五 202510:11
Gemini API Key 低成本 Nano Banana Pro作圖
- 11月 28 週五 202509:15
DMK 37AUX226
37U 系列
- 37U 系列 黑白工業相機
- USB 3.1 介面, USB供電
- 1/1.7 inch Sony CMOS STARVIS IMX226 感測器規格
- 4,000×3,000 (12 MP), 最高 30 fps
- 畫素: 水平: 1.85 µm, 垂直: 1.85 µm
- 捲簾快門
- 僅 36×36×25 mm
設備驅動程式 5.3.0.2793
- Intel Core i3或相同等级以上,記憶體4GB
- USB 3.0控制器
- 24或32位元顯示卡
- Windows 7 (32 & 64 bit), Windows 8 (32 & 64 bit), Windows 10 (32 & 64 bit), Windows 11
- 微軟DirectX 9.0c或以上
數據傳輸線
- 11月 17 週一 202508:42
wafer基礎術語
Load Port
在半導體製造流程中，Load Port 安裝在設備前端（EFEM）外，
作為晶圓載體（如 FOUP 或 FOSB）進出設備的接口，確保晶圓的潔淨度和安全。
兼容多種晶圓載體規格，如 8 吋和 12 吋的晶圓載具。
- 10月 14 週二 202510:51
將資料夾中多個mp4影片合併成一個mp4檔案
- 10月 13 週一 202508:16
如何用沙子制造芯片：从冶炼硅锭到晶圆打磨｜芯片工艺合集
- 10月 09 週四 202509:38
yolov9安裝
List all environments:
> conda env list
(yolov8) E:\yolov9>conda env list
# conda environments:
#
base C:\Users\me123\anaconda3
yolov8 * C:\Users\me123\anaconda3\envs\yolov8
yolov9 C:\Users\me123\anaconda3\envs\yolov9
yolov8 c:\Users\me123\anaconda3\envs\yolov8
Remove an environment:
> c
onda remove --name yolov9 --allRemove all packages in environment C:\Users\me123\anaconda3\envs\yolov9:
## Package Plan ##
environment location: C:\Users\me123\anaconda3\envs\yolov9
The following packages will be REMOVED:
_openmp_mutex-4.5-4_kmp_llvm
anyio-4.2.0-py311haa95532_0
argon2-cffi-21.3.0-pyhd3eb1b0_0
argon2-cffi-bindings-21.2.0-py311h2bbff1b_0
asttokens-2.4.1-pyhd8ed1ab_0
async-lru-2.0.4-py311haa95532_0
attrs-23.1.0-py311haa95532_0
babel-2.11.0-py311haa95532_0
beautifulsoup4-4.12.2-py311haa95532_0
blas-1.0-mkl
bleach-4.1.0-pyhd3eb1b0_0
brotli-python-1.0.9-py311hd77b12b_7
bzip2-1.0.8-he774522_0
ca-certificates-2025.10.5-h4c7d964_0
certifi-2025.10.5-pyhd8ed1ab_0
cffi-1.16.0-py311h2bbff1b_0
charset-normalizer-2.0.4-pyhd3eb1b0_0
colorama-0.4.6-pyhd8ed1ab_0
comm-0.2.1-pyhd8ed1ab_0
debugpy-1.6.7-py311hd77b12b_0
decorator-5.1.1-pyhd8ed1ab_0
defusedxml-0.7.1-pyhd3eb1b0_0
exceptiongroup-1.2.0-pyhd8ed1ab_2
executing-2.0.1-pyhd8ed1ab_0
idna-3.4-py311haa95532_0
importlib-metadata-7.0.1-pyha770c72_0
importlib_metadata-7.0.1-hd8ed1ab_0
ipykernel-6.29.2-pyha63f2e9_0
ipython-8.21.0-pyh7428d3b_0
jedi-0.19.1-pyhd8ed1ab_0
jinja2-3.1.3-py311haa95532_0
json5-0.9.6-pyhd3eb1b0_0
jsonschema-4.19.2-py311haa95532_0
jsonschema-specifications-2023.7.1-py311haa95532_0
jupyter-lsp-2.2.0-py311haa95532_0
jupyter_client-8.6.0-pyhd8ed1ab_0
jupyter_core-5.7.1-py311h1ea47a8_0
jupyter_events-0.8.0-py311haa95532_0
jupyter_server-2.10.0-py311haa95532_0
jupyter_server_terminals-0.4.4-py311haa95532_1
jupyterlab-4.0.11-py311haa95532_0
jupyterlab_pygments-0.1.2-py_0
jupyterlab_server-2.25.1-py311haa95532_0
libffi-3.4.4-hd77b12b_0
libsodium-1.0.18-h8d14728_1
llvm-openmp-14.0.4-h2d74725_0
markupsafe-2.1.3-py311h2bbff1b_0
matplotlib-inline-0.1.6-pyhd8ed1ab_0
mistune-2.0.4-py311haa95532_0
mkl-2023.2.0-h57928b3_50499
mkl-service-2.4.0-py311h2bbff1b_1
mkl_fft-1.3.8-py311h2bbff1b_0
mkl_random-1.2.4-py311h59b6b97_0
nbclient-0.8.0-py311haa95532_0
nbconvert-7.10.0-py311haa95532_0
nbformat-5.9.2-py311haa95532_0
nest-asyncio-1.6.0-pyhd8ed1ab_0
notebook-7.0.8-py311haa95532_0
notebook-shim-0.2.3-py311haa95532_0
numpy-1.26.4-py311hdab7c0b_0
openssl-3.0.13-h2bbff1b_0
overrides-7.4.0-py311haa95532_0
packaging-23.2-pyhd8ed1ab_0
pandocfilters-1.5.0-pyhd3eb1b0_0
parso-0.8.3-pyhd3eb1b0_0
pickleshare-0.7.5-py_1003
platformdirs-4.2.0-pyhd8ed1ab_0
prometheus_client-0.14.1-py311haa95532_0
prompt-toolkit-3.0.42-pyha770c72_0
psutil-5.9.0-py311h2bbff1b_0
pure_eval-0.2.2-pyhd8ed1ab_0
pycparser-2.21-pyhd3eb1b0_0
pygments-2.17.2-pyhd8ed1ab_0
pysocks-1.7.1-py311haa95532_0
python-3.11.4-he1021f5_0
python-dateutil-2.8.2-pyhd8ed1ab_0
python-fastjsonschema-2.16.2-py311haa95532_0
python-json-logger-2.0.7-py311haa95532_0
python-tzdata-2025.2-pyhd8ed1ab_0
python_abi-3.11-2_cp311
pytz-2023.3.post1-py311haa95532_0
pywin32-305-py311h2bbff1b_0
pywinpty-2.0.10-py311h5da7b33_0
pyyaml-6.0.1-py311h2bbff1b_0
pyzmq-25.1.2-py311hd77b12b_0
referencing-0.30.2-py311haa95532_0
requests-2.31.0-py311haa95532_1
rfc3339-validator-0.1.4-py311haa95532_0
rfc3986-validator-0.1.1-py311haa95532_0
rpds-py-0.10.6-py311h062c2fa_0
send2trash-1.8.2-py311haa95532_0
six-1.16.0-pyh6c4a22f_0
sniffio-1.3.0-py311haa95532_0
soupsieve-2.5-py311haa95532_0
sqlite-3.41.2-h2bbff1b_0
stack_data-0.6.2-pyhd8ed1ab_0
tbb-2021.5.0-h2d74725_1
terminado-0.17.1-py311haa95532_0
tinycss2-1.2.1-py311haa95532_0
tk-8.6.12-h2bbff1b_0
tornado-6.3.3-py311h2bbff1b_0
traitlets-5.14.1-pyhd8ed1ab_0
typing-extensions-4.9.0-py311haa95532_1
typing_extensions-4.9.0-py311haa95532_1
tzdata-2023c-h04d1e81_0
urllib3-2.1.0-py311haa95532_1
vc-14.2-h21ff451_1
vs2015_runtime-14.27.29016-h5e58377_2
wcwidth-0.2.13-pyhd8ed1ab_0
webencodings-0.5.1-py311haa95532_1
websocket-client-0.58.0-py311haa95532_4
win_inet_pton-1.1.0-py311haa95532_0
winpty-0.4.3-4
xz-5.4.2-h8cc25b3_0
yaml-0.2.5-he774522_0
zeromq-4.3.5-hd77b12b_0
zipp-3.17.0-pyhd8ed1ab_0
zlib-1.2.13-h8cc25b3_0
Proceed ([y]/n)? y
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
Everything found within the environment (C:\Users\me123\anaconda3\envs\yolov9), including any conda environment configurations and any non-conda files, will be deleted. Do you wish to continue?
(y/[n])? y
>conda env list
# conda environments:
#
base C:\Users\me123\anaconda3
yolov8 * C:\Users\me123\anaconda3\envs\yolov8
yolov8 c:\Users\me123\anaconda3\envs\yolov8
Clone an environment:
>
conda create --name newenv --clone oldenvCreate a new environment:
> conda create --name yolov9 python=3.12.7
> conda create --name yolov9 python=3.12.7
Retrieving notices: ...working... done
Channels:
- defaults
Platform: win-64
Collecting package metadata (repodata.json): done
Solving environment: done
## Package Plan ##
environment location: C:\Users\me123\anaconda3\envs\yolov9
added / updated specs:
- python=3.12.7
The following packages will be downloaded:
package | build
---------------------------|-----------------
bzip2-1.0.8 | h2bbff1b_6 90 KB
ca-certificates-2025.9.9 | haa95532_0 127 KB
expat-2.7.1 | h8ddb27b_0 259 KB
libffi-3.4.4 | hd77b12b_1 122 KB
libzlib-1.3.1 | h02ab6af_0 64 KB
openssl-3.0.18 | h543e019_0 6.8 MB
pip-25.2 | pyhc872135_0 1.2 MB
python-3.12.7 | h14ffc60_0 16.4 MB
setuptools-78.1.1 | py312haa95532_0 2.2 MB
sqlite-3.50.2 | hda9a48d_1 1017 KB
tk-8.6.15 | hf199647_0 3.5 MB
tzdata-2025b | h04d1e81_0 116 KB
ucrt-10.0.22621.0 | haa95532_0 620 KB
vc-14.3 | h2df5915_10 19 KB
vc14_runtime-14.44.35208 | h4927774_10 825 KB
vs2015_runtime-14.44.35208 | ha6b5a95_10 19 KB
wheel-0.45.1 | py312haa95532_0 177 KB
xz-5.6.4 | h4754444_1 280 KB
zlib-1.3.1 | h02ab6af_0 113 KB
------------------------------------------------------------
Total: 34.0 MB
The following NEW packages will be INSTALLED:
bzip2 pkgs/main/win-64::bzip2-1.0.8-h2bbff1b_6
ca-certificates pkgs/main/win-64::ca-certificates-2025.9.9-haa95532_0
expat pkgs/main/win-64::expat-2.7.1-h8ddb27b_0
libffi pkgs/main/win-64::libffi-3.4.4-hd77b12b_1
libzlib pkgs/main/win-64::libzlib-1.3.1-h02ab6af_0
openssl pkgs/main/win-64::openssl-3.0.18-h543e019_0
pip pkgs/main/noarch::pip-25.2-pyhc872135_0
python pkgs/main/win-64::python-3.12.7-h14ffc60_0
setuptools pkgs/main/win-64::setuptools-78.1.1-py312haa95532_0
sqlite pkgs/main/win-64::sqlite-3.50.2-hda9a48d_1
tk pkgs/main/win-64::tk-8.6.15-hf199647_0
tzdata pkgs/main/noarch::tzdata-2025b-h04d1e81_0
ucrt pkgs/main/win-64::ucrt-10.0.22621.0-haa95532_0
vc pkgs/main/win-64::vc-14.3-h2df5915_10
vc14_runtime pkgs/main/win-64::vc14_runtime-14.44.35208-h4927774_10
vs2015_runtime pkgs/main/win-64::vs2015_runtime-14.44.35208-ha6b5a95_10
wheel pkgs/main/win-64::wheel-0.45.1-py312haa95532_0
xz pkgs/main/win-64::xz-5.6.4-h4754444_1
zlib pkgs/main/win-64::zlib-1.3.1-h02ab6af_0
Proceed ([y]/n)? y
> conda activate yolov9
>pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu128
Looking in indexes: https://download.pytorch.org/whl/cu128
Collecting torch
Downloading https://download.pytorch.org/whl/cu128/torch-2.8.0%2Bcu128-cp312-cp312-win_amd64.whl.metadata (29 kB)
Collecting torchvision
Downloading https://download.pytorch.org/whl/cu128/torchvision-0.23.0%2Bcu128-cp312-cp312-win_amd64.whl.metadata (6.3 kB)
Requirement already satisfied: filelock in c:\users\me123\anaconda3\envs\yolov9\lib\site-packages (from torch) (3.20.0)
Requirement already satisfied: typing-extensions>=4.10.0 in c:\users\me123\anaconda3\envs\yolov9\lib\site-packages (from torch) (4.15.0)
Requirement already satisfied: sympy>=1.13.3 in c:\users\me123\anaconda3\envs\yolov9\lib\site-packages (from torch) (1.14.0)
Requirement already satisfied: networkx in c:\users\me123\anaconda3\envs\yolov9\lib\site-packages (from torch) (3.5)
Requirement already satisfied: jinja2 in c:\users\me123\anaconda3\envs\yolov9\lib\site-packages (from torch) (3.1.6)
Requirement already satisfied: fsspec in c:\users\me123\anaconda3\envs\yolov9\lib\site-packages (from torch) (2025.9.0)
Requirement already satisfied: setuptools in c:\users\me123\anaconda3\envs\yolov9\lib\site-packages (from torch) (78.1.1)
Collecting numpy (from torchvision)
Downloading https://download.pytorch.org/whl/numpy-2.1.2-cp312-cp312-win_amd64.whl.metadata (59 kB)
Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in c:\users\me123\anaconda3\envs\yolov9\lib\site-packages (from torchvision) (11.3.0)
Requirement already satisfied: mpmath<1.4,>=1.1.0 in c:\users\me123\anaconda3\envs\yolov9\lib\site-packages (from sympy>=1.13.3->torch) (1.3.0)
Requirement already satisfied: MarkupSafe>=2.0 in c:\users\me123\anaconda3\envs\yolov9\lib\site-packages (from jinja2->torch) (3.0.3)
Downloading https://download.pytorch.org/whl/cu128/torch-2.8.0%2Bcu128-cp312-cp312-win_amd64.whl (3461.4 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.5/3.5 GB 797.6 kB/s 0:13:53
Downloading https://download.pytorch.org/whl/cu128/torchvision-0.23.0%2Bcu128-cp312-cp312-win_amd64.whl (7.5 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 7.5/7.5 MB 3.8 MB/s 0:00:02
Downloading https://download.pytorch.org/whl/numpy-2.1.2-cp312-cp312-win_amd64.whl (12.6 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.6/12.6 MB 4.4 MB/s 0:00:02
Installing collected packages: numpy, torch, torchvision
Successfully installed numpy-2.1.2 torch-2.8.0+cu128 torchvision-0.23.0+cu128
>python
Python 3.12.7 | packaged by Anaconda, Inc. | (main, Oct 4 2024, 13:17:27) [MSC v.1929 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.cuda.is_available()
True
>>> exit()
切換至e槽
>e:
(yolov9) E:\>git clone https://github.com/me1237guy/yolov9.git
Cloning into 'yolov9'...
remote: Enumerating objects: 499, done.
Receiving objects: 88% (440/499), 2.45 MiB | 4.88 MiB/sused 499 (from 1)
Receiving objects: 100% (499/499), 2.59 MiB | 4.28 MiB/s, done.
Resolving deltas: 100% (274/274), done.
=====================================================
(yolov9) E:\>cd yolov9
(yolov9) E:\yolov9>pip install -r requirements.txt
(yolov9) E:\yolov9>pip install -r requirements.txt
Collecting gitpython (from -r requirements.txt (line 5))
Using cached gitpython-3.1.45-py3-none-any.whl.metadata (13 kB)
Collecting ipython (from -r requirements.txt (line 6))
Using cached ipython-9.6.0-py3-none-any.whl.metadata (4.4 kB)
Collecting matplotlib>=3.2.2 (from -r requirements.txt (line 7))
Using cached matplotlib-3.10.7-cp312-cp312-win_amd64.whl.metadata (11 kB)
Requirement already satisfied: numpy>=1.18.5 in c:\users\me123\anaconda3\envs\yolov9\lib\site-packages (from -r requirements.txt (line 8)) (2.1.2)
Collecting opencv-python>=4.1.1 (from -r requirements.txt (line 9))
Using cached opencv_python-4.12.0.88-cp37-abi3-win_amd64.whl.metadata (19 kB)
Requirement already satisfied: Pillow>=7.1.2 in c:\users\me123\anaconda3\envs\yolov9\lib\site-packages (from -r requirements.txt (line 10)) (11.0.0)
Collecting psutil (from -r requirements.txt (line 11))
Using cached psutil-7.1.0-cp37-abi3-win_amd64.whl.metadata (23 kB)
Collecting PyYAML>=5.3.1 (from -r requirements.txt (line 12))
Using cached pyyaml-6.0.3-cp312-cp312-win_amd64.whl.metadata (2.4 kB)
Collecting requests>=2.23.0 (from -r requirements.txt (line 13))
Using cached requests-2.32.5-py3-none-any.whl.metadata (4.9 kB)
Collecting scipy>=1.4.1 (from -r requirements.txt (line 14))
Using cached scipy-1.16.2-cp312-cp312-win_amd64.whl.metadata (60 kB)
Collecting thop>=0.1.1 (from -r requirements.txt (line 15))
Using cached thop-0.1.1.post2209072238-py3-none-any.whl.metadata (2.7 kB)
Requirement already satisfied: torch>=1.7.0 in c:\users\me123\anaconda3\envs\yolov9\lib\site-packages (from -r requirements.txt (line 16)) (2.8.0+cu128)
Requirement already satisfied: torchvision>=0.8.1 in c:\users\me123\anaconda3\envs\yolov9\lib\site-packages (from -r requirements.txt (line 17)) (0.23.0+cu128)
Collecting tqdm>=4.64.0 (from -r requirements.txt (line 18))
Using cached tqdm-4.67.1-py3-none-any.whl.metadata (57 kB)
Collecting tensorboard>=2.4.1 (from -r requirements.txt (line 22))
Using cached tensorboard-2.20.0-py3-none-any.whl.metadata (1.8 kB)
Collecting pandas>=1.1.4 (from -r requirements.txt (line 27))
Using cached pandas-2.3.3-cp312-cp312-win_amd64.whl.metadata (19 kB)
Collecting seaborn>=0.11.0 (from -r requirements.txt (line 28))
Using cached seaborn-0.13.2-py3-none-any.whl.metadata (5.4 kB)
Collecting albumentations>=1.0.3 (from -r requirements.txt (line 46))
Using cached albumentations-2.0.8-py3-none-any.whl.metadata (43 kB)
Collecting pycocotools>=2.0 (from -r requirements.txt (line 47))
Using cached pycocotools-2.0.10-cp312-abi3-win_amd64.whl.metadata (1.3 kB)
Collecting gitdb<5,>=4.0.1 (from gitpython->-r requirements.txt (line 5))
Using cached gitdb-4.0.12-py3-none-any.whl.metadata (1.2 kB)
Collecting smmap<6,>=3.0.1 (from gitdb<5,>=4.0.1->gitpython->-r requirements.txt (line 5))
Using cached smmap-5.0.2-py3-none-any.whl.metadata (4.3 kB)
Collecting colorama (from ipython->-r requirements.txt (line 6))
Using cached colorama-0.4.6-py2.py3-none-any.whl.metadata (17 kB)
Collecting decorator (from ipython->-r requirements.txt (line 6))
Using cached decorator-5.2.1-py3-none-any.whl.metadata (3.9 kB)
Collecting ipython-pygments-lexers (from ipython->-r requirements.txt (line 6))
Using cached ipython_pygments_lexers-1.1.1-py3-none-any.whl.metadata (1.1 kB)
Collecting jedi>=0.16 (from ipython->-r requirements.txt (line 6))
Using cached jedi-0.19.2-py2.py3-none-any.whl.metadata (22 kB)
Collecting matplotlib-inline (from ipython->-r requirements.txt (line 6))
Using cached matplotlib_inline-0.1.7-py3-none-any.whl.metadata (3.9 kB)
Collecting prompt_toolkit<3.1.0,>=3.0.41 (from ipython->-r requirements.txt (line 6))
Using cached prompt_toolkit-3.0.52-py3-none-any.whl.metadata (6.4 kB)
Collecting pygments>=2.4.0 (from ipython->-r requirements.txt (line 6))
Using cached pygments-2.19.2-py3-none-any.whl.metadata (2.5 kB)
Collecting stack_data (from ipython->-r requirements.txt (line 6))
Using cached stack_data-0.6.3-py3-none-any.whl.metadata (18 kB)
Collecting traitlets>=5.13.0 (from ipython->-r requirements.txt (line 6))
Using cached traitlets-5.14.3-py3-none-any.whl.metadata (10 kB)
Collecting wcwidth (from prompt_toolkit<3.1.0,>=3.0.41->ipython->-r requirements.txt (line 6))
Using cached wcwidth-0.2.14-py2.py3-none-any.whl.metadata (15 kB)
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Installing collected packages: simsimd, pytz, pure-eval, werkzeug, wcwidth, urllib3, tzdata, typing-extensions, traitlets, tensorboard-data-server, stringzilla, smmap, six, scipy, PyYAML, pyparsing, pygments, pycocotools, psutil, protobuf, parso, packaging, opencv-python-headless, opencv-python, markdown, kiwisolver, idna, fonttools, executing, decorator, cycler, contourpy, colorama, charset_normalizer, certifi, asttokens, annotated-types, absl-py, typing-inspection, tqdm, stack_data, requests, python-dateutil, pydantic-core, prompt_toolkit, matplotlib-inline, jedi, ipython-pygments-lexers, grpcio, gitdb, albucore, thop, tensorboard, pydantic, pandas, matplotlib, ipython, gitpython, seaborn, albumentations
Attempting uninstall: typing-extensions
Found existing installation: typing_extensions 4.12.2
Uninstalling typing_extensions-4.12.2:
Successfully uninstalled typing_extensions-4.12.2
Successfully installed PyYAML-6.0.3 absl-py-2.3.1 albucore-0.0.24 albumentations-2.0.8 annotated-types-0.7.0 asttokens-3.0.0 certifi-2025.10.5 charset_normalizer-3.4.3 colorama-0.4.6 contourpy-1.3.3 cycler-0.12.1 decorator-5.2.1 executing-2.2.1 fonttools-4.60.1 gitdb-4.0.12 gitpython-3.1.45 grpcio-1.75.1 idna-3.10 ipython-9.6.0 ipython-pygments-lexers-1.1.1 jedi-0.19.2 kiwisolver-1.4.9 markdown-3.9 matplotlib-3.10.7 matplotlib-inline-0.1.7 opencv-python-4.12.0.88 opencv-python-headless-4.12.0.88 packaging-25.0 pandas-2.3.3 parso-0.8.5 prompt_toolkit-3.0.52 protobuf-6.32.1 psutil-7.1.0 pure-eval-0.2.3 pycocotools-2.0.10 pydantic-2.12.0 pydantic-core-2.41.1 pygments-2.19.2 pyparsing-3.2.5 python-dateutil-2.9.0.post0 pytz-2025.2 requests-2.32.5 scipy-1.16.2 seaborn-0.13.2 simsimd-6.5.3 six-1.17.0 smmap-5.0.2 stack_data-0.6.3 stringzilla-4.2.0 tensorboard-2.20.0 tensorboard-data-server-0.7.2 thop-0.1.1.post2209072238 tqdm-4.67.1 traitlets-5.14.3 typing-extensions-4.15.0 typing-inspection-0.4.2 tzdata-2025.2 urllib3-2.5.0 wcwidth-0.2.14 werkzeug-3.1.3
- 9月 11 週四 202516:53
ActionEngine, ActionTask and ActionWorker
Actions.json
(1) 物件偵測到"重試"，信心門檻必須>=0.4 5秒內不能重複動作(避免連續Action)
Action: 移動滑鼠至物件中間位置，然後按下滑鼠左鍵
(2) 物件偵測到"取消"，信心門檻必須>=0.4 5秒內不能重複動作(避免連續Action)
dwell_ms:該物件必須連續出現停留畫面超過5秒(只要有一次沒偵測到會重新歸零)
- 9月 07 週日 202511:13
@dataclass裝飾子
自訂義類別FramePacket:
為了方便了解每一frame是由哪一個攝影機編號或影片編號(source_id)所產生，
frame_index表示第幾張影格，frame為單張影像內容，ts:時間標籤(time-stamp)
__repr__ 顯示字串
import time
import numpy as np
class FramePacket:
def __init__(self, source_id, frame_idex, frame, ts):
self.source_id = source_id
self.frame_index = frame_idex
self.frame = frame
self.ts = ts
def __repr__(self):
"""__repr__ → nice string representation"""
return f"FramePacket(source_id={self.source_id}, frame_index={self.frame_index}, ts={self.ts})"
if __name__ == "__main__":
frame = np.zeros(shape=(10,10))
pkt = FramePacket(0, 12, frame, time.time())
print(pkt)
time.sleep(0.03)
pkt = FramePacket(0, 13, frame, time.time())
print(pkt)
- 9月 03 週三 202519:19
IO控制卡安裝驅動器後無法在此裝置載入驅動程式
- 9月 02 週二 202509:52
How you put and then get items from a queue.Queue
1. 基本操作
blocking mode
import queue
q = queue.Queue()
# Put something in
q.put({"type": "PRINT", "payload": "Hello"})
# Get it back (blocking by default)
item = q.get()
print(item) # {'type': 'PRINT', 'payload': 'Hello'}
# Tell the queue we're done with this item
q.task_done()
2. Non-blocking or timeout
import queue
q = queue.Queue()
# Put something in
q.put({"type": "PRINT", "payload": "Hello"})
# Get it back (blocking by default)
item = q.get()
print(item) # {'type': 'PRINT', 'payload': 'Hello'}
try:
item = q.get(timeout=2) # wait up to 2 second
print(item)
except queue.Empty:
print("No item available")
# Tell the queue we're done with this item
q.task_done()
