

『SM961-512GB』買蒞做下載機系統碟,健康得78%.比之前買『SM961-256GB』平一半. 『讀』3553MB/S『寫』1639MB/S. 比『SM961-256GB』讀寫仲快.
SAMSUNG SM961 | 叁數 |
型號 | SM961 |
SIZE | 512GB |
讀 | 3553mb/s |
寫 | 1639mb/s |
協議 | NVME |
插口 | M.2 PCIE3.0X4 |
顆粒 | MLC |
BOOKCARD
雜牌ITX機箱買蒞諗住做『影音機』,肆面密吾透氣.得『4020風扇』抽風.貪佢有3條槽.
『RYZEN5-1500X』+『原裝幽靈風扇』仲免强頂得住. 換左『XEON E5-2630LV3』+『纯銅散熱』+『猫頭鷹NF-A6x25』慶過辣雞.幾分鐘內超百度.两粒U都係功耗60w,睇蒞此類機箱CPU極限60w.
加裝两個『AVC 9025』疏風.冚辦闌COM口擋版拆蒞透氣.裝埋『AVC 12025』直吹CPU.
使Windows10作為『網盤』『BT』下載機, 再蒞用『Microsoft 遠端桌面』
遠程控制下載機.
『下載機』開啟遠端桌面
『下載機』設定電源與睡眠
利用TrueNAS虛擬機装Windows10, 作為『網盤』『BT』下載機, 再蒞用 『Microsoft 遠端桌面』遠程控制下載機.
首先借『MediaCreationTool_22H2.exe』下載『Windows10-x64.iso』鏡像.
https://www.microsoft.com/zh-hk/software-download/windows10 |
下載虛擬機驅動『Stable virtio-win.iso』
https://github.com/virtio-win/virtio-win-pkg-scripts/blob/master/README.md |
將『Windows10-x64.iso』同埋『virtio-win.iso』擺係NAS
/mnt/pool0/dataset/ |
分配Windows10磁碟
設置網路
電腦要兩wlan網口,兩條網線.壹個畀『TrueNAS』『enp6s0』, 壹個畀『Win10』『enp5s0』.
設置虛擬機
挂載虛擬機驅動『virtio-win.iso』
著『Win10』虛擬機
装網卡驅程
但系點解吾直接裝Windows10充份利用CPU同Memory, 再蒞『Microsoft 遠端桌面』遠程控制下載機.
CPU模式 | |
Custom | 虛擬 CPU,性能相对差 |
Host-model | |
Host-passthrough | 物理CPU暴露畀虛擬機,虛擬機睇到物理CPU型號 |
新買『SEAGATE-16TB』同之前剩低两個组成raid0,插两『SEAGATE-16TB』. 同舊版本『trueNAS』有小小吾同.
通過網络訪問NAS『Sharing共用』
Stripe | Raid0 |
Mirror鏡像 | Raid1 |
Raid-Z | Raid5 |
舊相掃描後微粒偏大.『Stable Diffusion』支持舊相冇損修复.
放大算法 | 效果 |
Lanczos | 冇損高質放大算法 |
Nearest | 傳統放大算法,去噪差,放大效果差, |
BSRGAN | 細節佳,速度快,色彩暗 |
ESRGAN_4x | 去噪差 |
LDSR | 放大效果差 |
R-ESRGAN 4x | 放大現實畫像效果佳 |
R-ESRGAN 4x Anime6B | 放大動畫畫像效果佳 |
ScuNET | 放大效果差 |
ScuNET PSNR | 放大效果差 |
SwinIR 4x | 放大效果差 |
『Stable Diffusion』繪畫動人興奮,玩真人改漫畫,用『ControlNet』『Canny』提取線稿,後重新上色.效果比手機,色彩轉真人改漫畫,高幾皮.
正向咒語Prompt | 簡述 |
Masterpiece, | 傑作 |
Ultra high res, | 超高解像 |
High quality, | 高品質 |
4k, | 4k |
(Photorealistic:1.2), | 真實感 |
Photo, | 相片 |
A beautiful girl, | 靚女 |
反向咒語Negative Prompt | 簡述 |
sketches, | 速寫,素描 |
( (monochrome) ), ( (greyscale) ), | 黑白,灰階 |
facing away,
looking away, |
人面避開,
眸目避開 |
text,error,extra digit,fewer digits, | 文字,錯字,額外數字,細數 |
cropped,jpeg artifacts,blurry, | 裁剪,壓縮痕跡,模糊, |
signature,watermark,username, | 簽名,水印,身份, |
(worst quality:2),(low quality:2),(normal quality:2), (lowers), (normal quality), | 低質內容 |
bad anatomy,
bad body, bad hands, extra limbs, extra legs, extra foot, extra arms, (too many fingers:2), malformed limbs, (fused fingers:2), long neck, bad proportions, missing arms, missing legs, missing fingers, |
歪身體構造,
歪身歪勢, 歪手, 多餘肢體, 多餘腳瓜瓤, 多餘腳掌, 額外武器, 手指太多, 畸形肢體, 融合手指, 長頸, 身體比例差, 缺手瓜, 缺腳瓜瓤, 缺手指, |
Bad-artist, | 衰明星 |
Bad-artist-anime, | 衰動漫明星 |
Bad-prompt_version, | 恶意版本2 |
Badhand, | 坏人 |
Easynegative, | 易阴性 |
Ng_deepnegative, | Ng_deepnegative |
Stable_Diffusion_share
Stable Diffusion外網訪問–share
之前利用『–listen』係內網訪問『Stable Diffusion』電腦,利用『–share』係外網訪問『Stable Diffusion』.
C:\stable-diffusion-webui\webui-user.bat |
set COMMANDLINE_ARGS=–share |
https://cdn-media.huggingface.co/frpc-gradio-0.2/frpc_windows_amd64.exe |
C:\stable-diffusion-webui\venv\lib\site-packages\gradio |
https://684da9579597aa77c4.gradio.live |
1. Download this file: https://cdn-media.huggingface.co/frpc-gradio-0.2/frpc_windows_amd64.exe |
2. Rename the downloaded file to: frpc_windows_amd64_v0.2 |
3. Move the file to this location: C:\stable-diffusion-webui\venv\lib\site-packages\gradio |
This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces) |
『ControlNet』含『插件』『模型』分開下載.
『Stable Diffusion』裝『插件』需編輯『webui-user.bat』,加入命令行参式『–enable-insecure-extension-access』啟用插件訪問.
C:\stable-diffusion-webui\webui-user.bat |
set COMMANDLINE_ARGS=–listen –enable-insecure-extension-access |
下載插件方式1:
https://github.com/Mikubill/sd-webui-controlnet.git |
下載插件方式2:
https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui-extensions/master/index.json |
C:\stable-diffusion-webui\extensions\sd-webui-controlnet |
C:\stable-diffusion-webui\tmp\sd-webui-controlnet |
『雙精度模型』『ControlNet-v1-1』
https://huggingface.co/lllyasviel/ControlNet-v1-1/tree/main |
下載『ControlNet』雙精度模型.
『單精度模型』
https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/tree/main |
下載『ControlNet』單精度模型.
下载支持SDXL1.0-ControlNet模型
https://huggingface.co/lllyasviel/sd_control_collection/tree/main |
下載『ControlNet』SDXL1.0模型
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/diffusers_xl_canny_full.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/diffusers_xl_depth_full.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/ioclab_sd15_recolor.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/ip-adapter_sd15.pth?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/ip-adapter_sd15_plus.pth?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/ip-adapter_xl.pth?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/kohya_controllllite_xl_blur.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/kohya_controllllite_xl_blur_anime.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/kohya_controllllite_xl_blur_anime_beta.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/kohya_controllllite_xl_canny.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/kohya_controllllite_xl_canny_anime.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/kohya_controllllite_xl_depth.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/kohya_controllllite_xl_depth_anime.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/kohya_controllllite_xl_openpose_anime.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/kohya_controllllite_xl_openpose_anime_v2.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/kohya_controllllite_xl_scribble_anime.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/sai_xl_canny_128lora.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/sai_xl_canny_256lora.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/sai_xl_depth_128lora.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/sai_xl_depth_256lora.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/sai_xl_recolor_128lora.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/sai_xl_recolor_256lora.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/sai_xl_sketch_128lora.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/sai_xl_sketch_256lora.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/sargezt_xl_depth.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/sargezt_xl_depth_faid_vidit.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/sargezt_xl_depth_zeed.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/sargezt_xl_softedge.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/t2i-adapter_diffusers_xl_canny.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/t2i-adapter_diffusers_xl_depth_midas.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/t2i-adapter_diffusers_xl_depth_zoe.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/t2i-adapter_diffusers_xl_lineart.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/t2i-adapter_diffusers_xl_openpose.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/t2i-adapter_diffusers_xl_sketch.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/t2i-adapter_xl_canny.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/t2i-adapter_xl_openpose.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/t2i-adapter_xl_sketch.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/thibaud_xl_openpose.safetensors?download=true |
https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/thibaud_xl_openpose_256lora.safetensors?download=true |
將下載『.pth模型』『.yaml描述』『.safetensors模型』复制至models檔䅁夾
『C:\stable-diffusion-webui\extensions\sd-webui-controlnet\models』
模型標記 | 模型版本 | 品質 | SD版本 | 預處理 | 文檔擴展名 |
control | v11-1.1版 | e實驗品 | sd15 | ip2p | .pth模型 |
v11f1修正版1 | p正品 | sd21 | .yaml描述 | ||
u半成品 | .safetensors模型 |
下载VAE模型
https://huggingface.co/stabilityai/sdxl-vae |
sdxl_vae.safetensors |
擺係
C:\stable-diffusion-webui\models\VAE |
係『txt2img』『img2img』下側『ControlNet』
Enable使能 | 勾選後撳『ControlNet』先啟用. |
Low VRAM低顯存 | 顯存細過4GB,勾選 |
Pixel Perfect完美像素 | 自動匹配解像,實現最佳效果 |
Allow Preview | 允許預覽 |
Effective Region Mask有效區遮擋 | |
Upload independent control image上傳獨立控制影畫 | |
Preprocessor預處理 | |
Model模型 | |
Control Weight權重 | ControlNet對影像影響值, 權重值設0.6~1.1 |
Starting Control Step | 開始介入時機,默認0,叢開始影響影像. |
Ending Control Step | 結束介入時機,默認1,對影像影響至結束 |
Annotator resolution | 影像解像 |
Canny-Low threshold | 值越低越細致 |
Canny-High threshold | 值越高越粗糙 |
Control類型 | |
all | 冚辦闌 |
Canny | 硬邊緣 |
Depth | 深度 |
IP-Adapter | 圖生圖 |
Inpaint | 局部重繪 |
Instant-ID | |
InstructP2P | 指導圖生圖 |
Lineart | 線稿 |
MLSD | 直線 |
NormalMAP | 法線貼圖 |
OpenPose | 姿勢 |
Recolor | 重新上色 |
Reference | 引用 |
Revision | 修正 |
Scribble | 涂鴉 |
Segmentation | 語義分割 |
Shuffle | |
SoftEdge | |
SparseCTRL | |
T2I-Adapter | 文生圖 |
Tile | 平鋪 |
撳『Extensions擴展』->『Install from URL网址安装』->裝『ControlNet』時報錯.
AssertionError:extension access disabled because of command line flags |
主因係『–listen』開啟監聲後,禁止安裝插件. 加入『–enable-insecure-extension-access』啟用危險擴展訪問.
編輯『C:\stable-diffusion-webui\webui-user.bat』
加入『set COMMANDLINE_ARGS=–xformers –listen –enable-insecure-extension-access』
『提示詞』亦呌『咒詞』.
『提示詞』分『正向提示詞Positive Prompt』『反向提示詞Negative Prompt』.
『正向提示詞』指定鐘意特征.
『反向提示詞』消除唔鐘意特征.
『提示詞』越多越符合指望. 『提示詞』以『,』分隔,排序越前權重越高,排序越後權重越低,忽略『吉格』『换行』.
『提示詞』權重默認係1. 可通過()改變權重
提示詞語法 | 描述 |
girl,silk, | 分隔提示詞 |
(girl:3), | 權重提升3倍, 權重=0.1~100 |
(girl), | 提升1.1倍 |
((girl)), | 提升1.1*1.1=1.21倍 |
(((girl))), | 提升1.1*1.1*1.1=1.331倍 |
[girl], | 下降1.1倍 |
[[girl]], | 下降1.1*1.1=1.21倍 |
[[[girl]]], | 下降1.1*1.1*1.1=1.331倍 |
Girl | cat, | 混合體 |
Girl And cat , | 元素混合 |
Lovely[cow|horse], |
反向提示詞Negative Prompt | 簡述 |
(nsfw), | Not Safe For Work,唔适宜係辦公場所睇. |
sketches, | 速寫,素描 |
(worst quality:2),(low quality:2),(normal quality:2), (lowers), (normal quality), | 低質內容 |
( (monochrome) ), ( (greyscale) ), | 黑白,灰階 |
facing away,
looking away, |
人面避開,
眸目避開 |
text,error,extra digit,fewer digits, | 文字,錯字,額外數字,細數 |
cropped,jpeg artifacts,blurry, | 裁剪,壓縮痕跡,模糊, |
signature,watermark,username, | 簽名,水印,身份, |
bad anatomy,
bad body, bad hands, extra limbs, extra legs, extra foot, extra arms, too many fingers, malformed limbs, fused fingers, long neck, bad proportions, missing arms, missing legs, missing fingers, |
歪身體構造,
歪身歪勢, 歪手, 多餘肢體, 多餘腳瓜瓤, 多餘腳掌, 額外武器, 手指太多, 畸形肢體, 融合手指, 長頸, 身體比例差, 缺手瓜, 缺腳瓜瓤, 缺手指, |
畫質 | 簡述 |
High quality, | 高畫質 |
Masterpiece, | 杰作 |
8k, | |
Hight definition, | 高清 |
HD | 高清 |
Highly realistic, | 超現實 |
山水場景 | 簡述 |
mountain, | 山 |
On a hill, | 山上 |
Valley, | 山谷 |
The top of the hill, | 山頂 |
Beautiful detailed sky,
Beautiful detailed water, |
天清水靚 |
On the beach, | 海滩 |
On the ocean, | 大海 |
In a meadow, | 草原 |
landscape, | 開闊風景 |
Night, | 晚黑 |
In the rain, | 雨中 |
Rainy days, | 兩天 |
cloudy, | 多雲 |
Full moon, | 圓月 |
cloud, | 雲 |
moon, | 月球 |
moonlight, | 月光 |
季節 | 簡述 |
In spring, | 春 |
In summer, | 夏 |
In autumn, | 秋 |
In winter, | 冬 |
畫風/風格 | 簡述 |
Contour deepening, | 輪廓加深 |
Flat color, | 纯色 |
Monochrome, | 單色 |
Partially colored, | 部分着色 |
Chromatic aberration, | 色差失焦 |
CG, | 提升畫質 |
Comic, | 動漫 |
Sketch, | 素描 |
Pixel art, | 像素 |
Photo, | 影相 |
Illustration, | 插畫 |
animation | 動漫 |
鏡頭 | 簡述 |
Pov, | 正面視角 |
Full body, | 正面冚身視角 |
Cowboy shot, | 正面上身視角 |
Dramatic angle | 戲劇視角 |
From below, | 45度俯視 |
Bust, | 半身像 |
Upper body, | 上身 |
From behind, | 後面 |
Back, | 背影 |
Profile, | 側身 |
Turning around, | 回眸 |
Multiple views, | 多視角 |
光效 | 簡述 |
God rays, | 神光 |
Glowing light, | 熒光 |
Sparkle, | 閃耀 |
Blurry, | 模糊 |
Lens flare, | 光暈 |
Overexposure, | 過曝 |
Ray tracing, | 光線追踪 |
Reflection light, | 反射光 |
Motion blur, | 動態模糊 |
Cinematic lighting, | 电影光效 |
Jpeg artifacts, | 壓縮失真 |
Colorful refraction, | 彩光折射 |
Golden hour lighting, | 暖金色光照 |
Strong rim light, | 輪廓光 |
Intense shadows, | 强陰影 |
色調 | 簡述 |
xx hue | xx色調 |
colorful | 彩色 |
Vivid colors | 鮮色 |
nostalgia | 怀舊 |
bright | 光亮 |
High contrast | 高對比 |
High saturation | 高飽和 |
greyscale | 灰色 |
髮色 | 簡述 |
Purple hair | 紫髮 |
Silver hair | 銀髮 |
Dark blue hair | 深藍髮 |
Light blue hair | 淺藍髮 |
Blonde hair | 金髮 |
Colored inner hair | 髮底彩 |
Streaked hair | 單株彩髮 |
Gradient hair | 漸變彩髮 |
髮形 | 簡述 |
Hair bun | 西瓜頭 |
Ponytail | 馬尾 |
Drill hair | 公主卷 |
Messy hair | 散髮 |
braid | 辫 |
Twin braids | 孖辫 |
Wavy hair | 波浪卷 |
bangs | 髮陰 |
表情 | 簡述 |
Glaring | 𥄫 |
embarrassed | 尷尬 |
Grimace | 古靈精怪 |
Teasing smile | 嘲笑 |
Evil smile | 邪笑 |
shy | 怕羞 |
unamused | 冇趣 |
Kind smile | 有善微笑 |
耳仔 | 簡述 |
Pointy ears | 尖耳 |
Fox ears | 狐耳 |
眼仔 | 簡述 |
Aqua eyes | 水汪汪 |
Tsurime | 眼角 |
Glowing eyes | 發光 |
Sclera | 眼白 |
Pupil | 瞳 |
Eyelashes | 睫毛 |
tareme | 垂眼 |
嘴仔 | 簡述 |
上剎 | 簡述 |
Jacket | 背心 |
Hoodie | 外套 |
Dress shirt | 衬衫 |
Tailcoat | 燕尾服 |
Sweater | 襴衫 |
下剎 | 簡述 |
Pants | 褲 |
bloomers | 燈籠褲 |
skirt | 裙 |
Pencil skirt | 窄脚褲 |
套装 | 簡述 |
Business suit | 西装 |
chemise | 連身裙 |
Ski clothes | 滑雪服 |
Collared dress | 有領連身裙 |
Sleeveless dress | 冇袖連身裙 |
鞋仔 | 簡述 |
slippers | 拖鞋 |
Mary janes | 瑪麗珍鞋 |
loafers | 樂樂福鞋 |
Knee boots | 過膝長靴 |
Ballet slippers | 芭蕾舞鞋 |
High heels | 高跟鞋 |
socks | 襪 |
朱耳繩 | 簡述 |
Earings | 耳環環 |
Hood | 兜兜帽 |
Crown | 后冠 |
Hair bow | 蝴蝶髮夹 |
Glowes | 手套 |
Hair pin | 髮夾 |
手勢 | 簡述 |
waving | 招手 |
Spread arms | 張臂 |
Spread fingers | 張指 |
shushing | 噓嘘 |
Arms up | 抬臂 |
Hands in hair | 撥頭 |
Hand on hip | 單手叉腰 |
姿勢 | 簡述 |
Stand | 企 |
Knees to chest | 膝頭頂胸 |
Knees up | 抬膝 |
sit | 坐 |
run | 跑 |
walk | 走 |
Lie down | 趴 |
kneel | 跪 |
材質 | 簡述 |
Paper style | 紙質 |
Wood | 木質 |
Grey conerete | 灰水泥 |
Marbel | 大理石 |
Gold | 金 |
Sliver | 銀 |
Metal | 金屬 |
Copper | 銅 |
plastic | 塑膠 |
metallic | 金屬質感 |
foam | 泡沬 |
nendoroid | 粘土 |
gemstones | 寶石 |
crystal | 水瞐 |
sculpture | 雕塑 |
crystal | 水晶 |
mural | 壁畫 |
textured | 紋理 |
Filigret-metal | 拉絲金屬 |
Armor | 盔甲 |
Warframe | 機甲 |
Skeletal | 屍體 |
silk | 絲綢 |
bone | 體 |
Filigree metal design | 花絲金屬設計 |
Plastic | 膠 |
Wax | 臘燭 |
ice | 冰 |
Dry ice | 干冰 |
自然景觀 | 簡述 |
Black smoke | 黑烟/黑雾 |
Smooth fog | 弱雾 |
Cloudy | 雲畫 |
Puffy clouds | 雲海 |
Dramatic clouds | 戲劇雲彩 |
Thunderstorms | 暴雨 |
Stormy ocean | 海面暴雨 |
Ocean backdrop | 海洋背景 |
lightning | 閃電 |
Dawn | 日落 |
Sunrise | 日出 |
rainbow | 彩虹 |
Ethereal fog | 薄雾 |
landscape | 地貌 |
halo | 光環環 |
waterfall | 瀑布 |
Frozen river | 冰川 |
Gloomy night | 陰天 |
Swirlying dust | 旋轉塵 |
Abyss | 深渊 |
Candoluminescence | 白冷光 |
Sea foam | 浪花 |
mist | 薄雾 |
vapor | 水滊 |
珠寶 | 簡述 |
Atmospheric | 氛圍 |
Beryl | 綠寶石 |
Carve | 雕刻 |
Chrysoberyl | 金綠石 |
Commercial photography | 商業摄影 |
Copper | 銅 |
Corundum | 剛玉 |
Diamond | 鉆石 |
Feldspar | 長石 |
Garnet | 石榴石 |
gold | 金 |
Hoolow out | 鏤空 |
hue | 色調 |
inlay | 鑲嵌 |
Intricated details | 細節複雜 |
jade | 翡翠 |
jewelry | 寶石 |
Lazurite | 青金石 |
Liquid | 液態 |
Mirror | 鏡面 |
Olivine | 橄欖石 |
Patterm | 花紋 |
Perfect lighting | 燈光 |
relief | 浮雕 |
Rose quartz | 玫瑰石英 |
Ruby | 紅寶石 |
喫 | 簡述 |
A stick of sugar-coated haws | 冰糖葫蘆 |
Roast duck | 燒鴨 |
Box lunch | 盒仔飯 |
Eight-treasure rice pudding | 八寶飯 |
Glass noodles | 粉絲 |
guotie | 鍋餅 |
Hot pot | 火鍋 |
Jellied bean curd | 豆腐腦 |
Konjak tofu | 魔芋豆腐 |
Lotus root | 蓮藕 |
Rice noodles | 米粉 |
Rice tofu | 米豆腐 |
Set meal | 套餐 |
Spring roll(s) | 春卷 |
Steamed twisted rolls | 花卷 |
Tangyuan/Sweet rice dumpling(soup) | 元宵 |
wonton | 雲吞 |
係舊時對畫像改頭换面,非資深畫家吾得,『Stable Diffusion』局部重繪-今改頭换面變得容易.
中古『NETGEAR® GS108』得8網口,諗住買16口『NETGEAR® GS116EV2』.两百幾紋.
『NETGEAR』網口左右各壹眼LED燈.左燈著『100m/bps』带寬,右燈著『10m/bps』带寬, 左右燈著『1000m/bps』带寬.
電腦網卡左燈著係『通電』燈,右燈係信號指示燈.
點知『GS116EV2』有壹個網口得『100m/bps』带寬,可熊係網線造成,重新夾CAT8頭.也可能另壹邊網卡『100m/bps』带寬造成,『JBL-L75MS』係『100m/bps』带寬.
本蒞諗住買『惠威M-80W』,聽講質量麻麻一直冇落手.
睇中『JBL-L75MS』, 兩個5.25寸低音, 兩個1寸高音, 壹個4寸中音. 總合係單壹箱內.搞特價4798果斷落手.
順風寄蒞,三重紙箱, 『音箱』長790MM摆吾入書架.
附件有『電池』『摇控』『勾』『指南書』『電線』. 冇畀『3.5MM音頻線』, 好在支持『RJ45網線』『WIFI』『USB線』『藍牙』
『藍牙』連線
『AUX3.5MM』音箱線
Windows10藍牙連線-吾知係咪藍牙驅動造成,間歇冇聲斷聲,後蒞買两頭3.5MM插頭連線.
『WLAN』網口
插網線後,通過手機電腦連線『192.168.1.5』,有可能係其它ip,登錄『音箱』後台. 可以連『wifi』.
『USB』口
插USB線冇反應,事因佢插USB磁碟.
連『WIFI』
插網線後,通過手機電腦連線『192.168.1.5』
『SFX』聲場增強
摇控『SFX』鍵-加强室內立體聲寬廣聲場,冇效果.
『接地』
有獨立接地口,閉環接地線,屋企接地係邊?
『低音』BASS CONTOUR
『低音調節』撥『-3DB』加重低音輸出. 聽人聲吾使撥.
Stable Diffusion2.1係指v2.1模型
cd C:\stable-diffusion-webui |
git pull |
下載768*768模型『v2-1_768-ema-pruned.ckpt』. 配置檔『v2-inference-v.yaml』改名為『v2-1_768-ema-pruned.yaml』
有舊『ATX火牛』230W, 諗住用係『B450-ITX』配『RYZEN5-1500X』得60W岩岩够. 但係舊『ATX火牛』20pin. 冇左4pin插係『B450-ITX』照樣著機.多出4pin分别係『3.3v』『5V』『12V』『地』. 理論蒞講通過係飛線增加『4PIN』.網有20PIN轉24PIN線,直頭吾著機,好彩冇燒底板.
新買ITX機箱諗住用翻『益衡FLEX-600W火牛』, 點知装得『atx』同『sfx』火牛, 唯有買『益衡SFX火牛』總功率750瓦,『SFX』同係為『itx』細機箱設計, 方體更适合係細機箱.
配線齊但係主板24PIN偏短,後蒞買30CM長24PIN駁線.且功耗下火牛風轉减小噪聲.
㸃知雜牌『X99-itx』掉失『M.2-SSD』, 以為係火牛引起.又再買『EVGA SFX 650W』㸃知仲衰. 後蒞换左amphenol-sata線先搞掂.
壹臺『Stable Diffusion』電腦,可以有多塊『NVIDIA-GPU顯卡』,發熱噪聲犀利, 唯有擺係機房仔,係內網用『手機』『平板』『電腦』訪問『Stable Diffusion』.
C:\stable-diffusion-webui\webui-user.bat |
set COMMANDLINE_ARGS=–listen |
係win10仲要防火牆加網埠監聽.
更新『AMI-BIOS』有『AFUWIN』同埋『AFUDOS』, 但係『AFUWIN』吾支緩『win10』, 得翻『AFUDOS』 .
示例 | |
AFUDOS.EXE BIOS.BIN /0 | 導出BIOS |
AFUDOS.EXE BIOS.BIN /P | 寫入MAIN BIOS |
AFUDOS.EXE BIOS.BIN /B | 寫入啟動块Boot Block |
AFUDOS.EXE BIOS.BIN /santa | 强制寫BIOS |
AFUDOS.EXE F BIOS.BIN | 强制寫BIOS |
『華南X99-F8D Plus』開機蓝屏『TeeDriverW8x64.sys』, 可禁節能模式『CPU C3/C6』修复,但系冇左『睡眠模式』.諗住試更新BIOS修复.但系雜牌主板『Q-FLASH』冇『BIOS』更新程式.更新『AMI-BIOS』用『AFUDOS.EXE』,係Win10冇DOS啟動磁碟,利用『Rufus』制『MS-DOS』開機磁碟. 同『Etcher』壹樣, 但係『Rufus』內含『MS-DOS』同『FreeDOS』映像.
登入『http://rufus.ie』下載『rufus-4.5.exe』.
http://rufus.ie |
https://github.com/pbatard/rufus/releases/download/v4.5/rufus-4.5.exe |
當睇到下面信息『Stable Diffusion』已装掂,但係缺『基礎模型』.
No checkpoints found. When searching for checkpoints, looked at: |
– file C:\stable-diffusion-webui\model.ckpt |
– directory C:\stable-diffusion-webui\models\Stable-diffusion |
Can’t run without a checkpoint. Find and place a .ckpt file into any of those locations. The program will exit. |
先去『civitai.com』下載模型
https://civitai.com/ |
https://huggingface.co/ |
係『Stable Diffusion』左上角揀基礎模型.擴展名『.safetensors』『.ckpt』, 大細係6GB~4GB之間. 『基礎模型』吾可叠加.
『基礎模型』擺係指定檔案夾.
Model模型 | 檔案夾位置 |
Checkpoint『.ckpt』 | C:\stable-diffusion-webui\models\Stable-diffusion |
.safetensors | C:\stable-diffusion-webui\models\Stable-diffusion |
『基礎模型』添加封面,圖檔名與模型名壹致,同『基礎模型』模型擺係壹起,之後撳『refresh page』刷新.
基礎模型 | model.safetensors |
封面圖 | model.png |
『Stable Diffusion』開源AI划畫畵程式. 輕易係網络下載,部署係電腦行.
https://github.com/AUTOMATIC1111/stable-diffusion-webui |
『提示詞』畀『Clip』解讀, 『Diffusion』逐步生成圖像.
『提示詞』->『Clip』->『Diffusion』->『VAE』->『畵』 |
硬件要求
部署運行環境.
部署Stable Diffusion
git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui |
“C:\Program Files\Python310\python.exe” |
@echo off |
set PYTHON=”C:\Program Files\Python310\python.exe” |
set GIT= |
set VENV_DIR= |
set COMMANDLINE_ARGS=–xformers |
call webui.bat |
ERROR:Could not find a version that satisfies the requirement torch |
ERROR:NO matching distribution found for torch |
WARNING:There was an error checking the latest version of pip. |
python -m pip install –upgrade pip |
C:\stable-diffusion-webui\venv\Scripts\python.exe -m pip install –upgrade pip |
RuntimeError: Torch is not able to use GPU; add –skip-torch-cude-test to COMMANDLINE_ARGS variable to disable this check |
set COMMANDLINE_ARGS=–xformers –skip-torch-cuda-test |
RuntimeError: Couldn’t install gfpgan. |
RuntimeError: Couldn’t install clip. |
RuntimeError: Couldn’t install open_clip. |
OSError: Can’t load tokenizer for ‘openai/clip-vit-large-patch14’. If you were trying to load it from ‘https://huggingface.co/models’, make sure you don’t have a local directory with the same name. Otherwise, make sure ‘openai/clip-vit-large-patch14’ is the correct path to a directory containing all relevant files for a CLIPTokenizer tokenizer. |
TypeError: AsyncConnectionPool.__init__() got an unexpected keyword argument ‘socket_options’ |
ImportError: cannot import name ‘_compare_version’ from ‘torchmetrics.utilities.imports’ (C:\stable-diffusion-webui\venv\lib\site-packages\torchmetrics\utilities\imports.py) |
Downloading: “https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors” to C:\stable-diffusion-webui\models\Stable-diffusion\v1-5-pruned-emaonly.safetensors |
C:\stable-diffusion-webui\venv |
Running on local URL: http://127.0.0.1:7860 |
安裝『Stable Diffusion』時未有安裝『open-clip-torch』
changing setting sd_model_checkpoint to v1-5-pruned-emaonly.safetensors [6ce0161689]: AttributeError
Traceback (most recent call last): |
AttributeError: ‘NoneType’ object has no attribute ‘lowvram’ |
pip install open-clip-torch==2.20.0 |
C:\stable-diffusion-webui\venv\Scripts\python.exe -m pip install open-clip-torch==2.20.0 |
『Stable Diffusion』冇自带模型,需自行下載,當妳睇到下面信息,下載『v1-5-pruned-emaonly.safetensors』, 之后擺係『C:\stable-diffusion-webui\models\Stable-diffusion\』資料夾.
Downloading: “https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors” to C:\stable-diffusion-webui\models\Stable-diffusion\v1-5-pruned-emaonly.safetensors |
https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors | Sour |
C:\stable-diffusion-webui\models\Stable-diffusion\v1-5-pruned-emaonly.safetensors | dest |
當妳『Stable Diffusion』睇到下面信息,未有裝『transformers』模型分詞器.或版本舊.
OSError: Can’t load tokenizer for ‘openai/clip-vit-large-patch14’. If you were trying to load it from ‘https://huggingface.co/models’, make sure you don’t have a local directory with the same name. Otherwise, make sure ‘openai/clip-vit-large-patch14’ is the correct path to a directory containing all relevant files for a CLIPTokenizer tokenizer. |
pip install transformers |
C:\stable-diffusion-webui\venv\Scripts\python.exe -m pip install transformers |
pip install –upgrade transformers |
C:\stable-diffusion-webui\venv\Scripts\python.exe -m pip install –upgrade transformers |
安裝『Stable Diffusion』時未有裝『torchmetrics』.
ImportError: cannot import name ‘_compare_version’ from ‘torchmetrics.utilities.imports’ (C:\stable-diffusion-webui\venv\lib\site-packages\torchmetrics\utilities\imports.py) |
進入『命令行模式CMD』
查版本號
pip show torchmetrics |
缷載
pip uninstall torchmetrics |
下載0.11.4版本
C:\stable-diffusion-webui\venv\Scripts\python.exe -m pip install torchmetrics==0.11.4 |
安裝『Stable Diffusion』時報錯
TypeError: AsyncConnectionPool.__init__() got an unexpected keyword argument ‘socket_options’ |
C:\stable-diffusion-webui\venv\Scripts\python.exe -m pip install httpx==0.24.1 -force-reinstall |
python.exe -m pip install httpx==0.24.1 -force-reinstall |
安裝『Stable Diffusion』時未裝『open_clip』. 其實亦係『clip』
RuntimeError: Couldn’t install open_clip. |
進入『open_clip』
https://github.com/mlfoundations/open_clip |
或者下載『open_clip』落『C:』碟
git clone https://github.com/openai/open_clip.git |
下載『open_clip-main.zip』後解壓本地安裝
https://codeload.github.com/mlfoundations/open_clip/zip/refs/heads/main |
复制『C:\open_clip』到『C:\stable-diffusion-webui\venv\Scripts』
C:\open_clip | Sour |
C:\stable-diffusion-webui\venv\Scripts | dest |
進入『命令行模式CMD』
CD去『CLIP』檔䅁夾, 作為本地路徑
cd C:\stable-diffusion-webui\venv\Scripts\open_clip |
执行下列安裝指令
C:\stable-diffusion-webui\venv\Scripts\python.exe setup.py build install |
常試通過pip指令安裝
pip install open_clip_torch |
諗住買3090Ti點知連成萬,孖2080Ti送NVLink先陸千有找.
登入NVIDIA官網下載嘉時至新驅動
https://www.nvidia.com/Download/index.aspx?lang=en-us |
填NVIDIA Driver Downloads | |
NVIDIA Driver Downloads | 揀 |
Product Type | GeForce |
Product Series | GeForce RTX 40 Series |
Product | GeForce RTX 4090 Ti |
Operating System | Windows 10 64-bit |
Download Type | NVIDIA Studio Driver |
撳Search下載驅動
https://us.download.nvidia.com/Windows/552.22/552.22-desktop-win10-win11-64bit-international-nsd-dch-whql.exe |
新顯卡NVLINK金手指有封膜,撕左插入NVLINK桥即掂.冇使搞BIOS.
下載『NVLinkTestCUDA11』測試NVLINK桥造總線带寛
https://www.pugetsystems.com/support/guides/how-to-enable-and-test-nvidia-nvlink-on-quadro-and-geforce-rtx-cards-in-windows-10-1266/ |
https://puget.systems/go/NVLinkTestCUDA11 |
孖『NVIDIA GeForce RTX 2080 Ti』都插係PCIEx16,鋪頭送『GeForce NVLINK』桥造總線带寛得『48.08GB/S』, 可能要『Quadro Nvlink』先有『100GB/S』带寛.
『clip』建构圖像文字之間連系模型,安裝『Stable Diffusion』時未有安裝『clip』.
RuntimeError: Couldn’t install clip. |
進入『clip』
https://github.com/openai/clip/ |
下載『clip』落『C:』碟
git clone https://github.com/openai/CLIP.git |
或者下載『CLIP-main.zip』後解壓
https://codeload.github.com/openai/CLIP/zip/refs/heads/main |
复制『C:\CLIP』到『C:\stable-diffusion-webui\venv\Scripts』
C:\CLIP | Sour |
C:\stable-diffusion-webui\venv\Scripts | dest |
進入『命令行模式CMD』
CD去『CLIP』檔䅁夾, 作為本地路徑
cd C:\stable-diffusion-webui\venv\Scripts\CLIP |
执行下列安裝指令
C:\stable-diffusion-webui\venv\Scripts\python.exe setup.py build install |
安裝『Stable Diffusion』時未有安裝『gfpgan』人樣修复.
RuntimeError: Couldn’t install gfpgan. |
進入『GFPGAN』
https://github.com/TencentARC/GFPGAN |
下載『GFPGAN』落『C:』碟
git clone https://github.com/TencentARC/GFPGAN.git |
复制『C:\GFPGAN』到『C:\stable-diffusion-webui\venv\Scripts』
C:\GFPGAN | Sour |
C:\stable-diffusion-webui\venv\Scripts | dest |
進入『命令行模式CMD』
CD去『GFPGAN』檔䅁夾, 作為本地路徑
cd C:\stable-diffusion-webui\venv\Scripts\GFPGAN |
执行下列安裝指令
C:\stable-diffusion-webui\venv\Scripts\python.exe -m pip install basicsr |
C:\stable-diffusion-webui\venv\Scripts\python.exe -m pip install facexlib |
C:\stable-diffusion-webui\venv\Scripts\python.exe -m pip install -r requirements.txt |
C:\stable-diffusion-webui\venv\Scripts\python.exe setup.py develop |
C:\stable-diffusion-webui\venv\Scripts\python.exe -m pip install realesrgan |
『Torch』基於神經網络人工智慧輵, 『PyTorch』係『Python』版本
首先确認NVIDIA顯卡支持CUDA版本. 下載最新顯卡驅動『552.22-desktop-win10-win11-64bit-international-nsd-dch-whql.exe』
網络安装『PyTorch』
pip3 install torch torchvision torchaudio –index-url https://download.pytorch.org/whl/cu121 |
本地安装『PyTorch』
https://download.pytorch.org/whl/torch/ |
https://download.pytorch.org/whl/cu121/torch-2.3.0%2Bcu121-cp310-cp310-win_amd64.whl#sha256=002027d18a9c054f08fe9cf7a729e041229e783e065a71349015dcccc9a7137e |
WARNING:There was an error checking the latest version of pip. |
Defaulting to user installation because normal site-packages is not writeable |
python -m pip install –upgrade pip |
測試『Pytorch』返回true,表示可調用GPU-CUDA指令, 進入『Pytho3.10』.
import torch |
print(torch.__version__) |
torch.cuda.is_available() |
缷載tcrch
Pip uninstall torch |
Pip uninstall torchaudio torchvision |
Pip uninstall torch-geometric torch-scatter torch-sparse torch-cluster torch-spline-conv |
https://pytorch.org/get-started/locally/ |
https://pytorch.org/get-started/previous-versions/ |
睇人AI繪畫,諗住買NVIDIA顯卡,中古RTX3060都要兩千幾,
可能係機房大批淘汰,Tesla P40-24GB係網大量焦拋售,柒百伍包郵,成色麻麻.配NVIDIA-8pin專用供電線,睇佢散熱槽,應該係風道式散熱. 係屎窟裝涡輪風扇, 點知電流大噪䡰大,再加30%降壓線壓低風.
使能PCIE-Above 4G
驅動下載
填NVIDIA Driver Downloads | |
NVIDIA Driver Downloads | 揀 |
Product Type | Data Center Tesla |
Product Series | P-Series |
Product | Tesla P40 |
Operating System | Windows 10 64-bit |
『Tesla P40』裝驅動 默認係『TCC計算模式』, 需改為『WDDM圖形模式』.
Computer \HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\Class\{4d36e968-e325-11ce-bfc1-08002be10318} |
DriverDesc | |
0000 | NVIDIA Tesla P40 |
0001 | NVIDIA Quadro K6000 |
NAME | TYPE | VALUE |
AdapterType | REG_DWORD | 1 – DELETE |
FeatureScore | REG_DWORD | 0Xcf->0Xd1 |
GridLicensedFeatures | REG_DWORD | 7 (强制開啟GRID圖形模式) |
EnableMsHybrid | REG_DWORD | 1 |
NAME | TYPE | VALUE |
EnableMsHybrid | REG_DWORD | 2 |
圖形設定指定-GPU: NVIDIA Tesla P40
NVIDIA GPU指定『Tesla P40』
『nvidia-smi.exe』, 係nvidia公司開發蒞睇gpu. 基於命令行界面, 而非圖形界面. 可能考慮兼容同稳定.随nvidia顯卡驅動安裝自動复制,路徑如下.
C:\Windows\System32\nvidia-smi.exe |
講解 | |
Nvidia-smi | 程式版本號 |
Driver version | 顯卡驅動版本號 |
CUDA Version | CUDA至高支援版本號 |
GPU | 顯卡編號, 0開如始編址, |
FAN | 風扇轉速(0~100%),冇風扇(N/A) |
NAME | 顯卡型號 |
Temp | GPU温度,0C ~ 100C |
Perf | 性能, 至高p0級~至低p12級 |
Pwr: Usage/Cap | 顯卡能耗, 『usage』 使用率,『Cap』能耗牆 |
Bus-ID | 顯卡總線地埗 |
Disp.A | 圖像顯示輸出,OFF閂, ON著 |
Memory-Usage | 顯存使用率 |
GPU-Util | GPU使用率 |
Compute M. | 計算模式DEFAULT/EXCLUSIVE_PROCESS/PROHIBITED |
ECC | 顯存校驗糾錯 |
CUDA係NVIDIA為GPU并行運算而開發,用C語言調用GPU-CUDA指令集進行大規模并行運行.
虽然上世紀以經有『INTEL-SEE』并行運算指令集,但係『NVIDIA-CUDA』青出於蓝.
『PyTorch』暫時至高支持『CUDA 12.1』.
登入『CUDA官網』, 下載『CUDA Toolkit 12.1.1』
https://developer.nvidia.com/cuda-toolkit-archive/ |
github
gitHub攻略
git系統等於『檔案伺服』外加『版本管理』,
『Linux』安裝git
通過SSH登入
ssh username@ubuntu |
root@ubuntu’s password: 填密碼. 冇字符顯示, 撳Enter鍵.
安裝git架撑
sudo apt update |
sudo apt install git |
sudo apt update git |
下載『Quectel_MHI』
sudo git clone https://github.com/ChaingTsung/Quectel_MHI/ |
『OpenWRT』安装『git』從缺小http傳輸支
git: ‘remote-https’ is not a git command. See ‘git –help’. |
安装『git-http』修复
sudo apt install git-http |
sudo apt install curl |
sudo apt install libcurl4 |
git –version | 版本號 |
『windows10』下載祗安裝『Git-2.45.0-64-bit.exe』,家時最新2.45.0版.
Additional icons on the Desktop | 桌面捷徑 |
Windows Explorer integration Git Bash Here | 右鍵菜單 |
Windows Explorer integration Git GUI Here | 右鍵菜單 |
Git LFS (Large File Support) | 支援大檔䅁 |
Associate .git* configuration files with the default text edito | 配置檔䅁.git關聯edito |
Associate .sh files to be run with Bash | 關聯.sh檔䅁 |
Check daily for Git for Windows updates | 日日檢查更新 |
Add a Git Bash Profile to Windows Terminal | 將Git Bash設定檔新增到Windows終端 |
Scalar(Git add-on to manage large-scale repositories) | 管理大型儲存庫 |
注册GitHub賬戶
賬戶信息 | |
EMAIL電郵 | 電子郵箱, 用蒞收驗證電郵. |
Username | 字母+字符 混合, 唯壹未被利用. |
PASSWORD密碼 | 字母+數字+字符混合 |
下載GitHub卓面版『GitHubDesktopSetup-x64.exe』
『Python』其實係『虛擬機』, 先裝『.py』源碼編譯為字節碼『.pyc』. 『Python虛擬機』再執行『Python字節碼』. 同『java』壹樣.
登入『Python』官網『https://www.python.org/』.
Documentation | 文檔 |
Pip | (必揀)下載和管理python包 |
Tcl/tk and IDLE | 裝IDLE包 |
Python test suite | 裝測試包 |
Py launcher For all users(requires admin privileges) | 裝‘py’啟動程式 |
Install python 3.12 for all users | 冚辦闌帳號裝python程式 |
Associate files with python(requires the ‘py’ launcher) | 關聯‘py’文檔 |
Create shortcuts for installed applications | 制作python捷徑檔 |
Add Python to environment variables | 將Python路徑添加到環境變量 |
Precompile standard library | 預編譯標準庫 |
Download debugging symbols | 下載調試符號 |
Download debug binaries(requires VS 2017 or later) | 下載調試庫 |
C:\Users\bookc\AppData\Roaming\Python\Python310\ |
C:\Users\bookc\AppData\Roaming\Python\Python310\Scripts\ |
C:\Users\bookc\AppData\Roaming\Python\Python310\site-packages\ |
C:\Program Files\Python310\Scripts\ |
C:\Program Files\Python310\ |
檢查最新版pip時出錯.
WARNING:There was an error checking the latest version of pip. |
需手動升級pip至最新版.
python -m pip install –upgrade pip |
https://www.python.org/ |
https://www.python.org/downloads/windows/ |
https://www.python.org/ftp/python/3.10.6/python-3.10.6-amd64.exe |
買雜牌『B450-ITX』配『RYZEN5-1500X』砌臺ITX,摆係老竇屋企睇片.點知『BE200』WIFI吾認識. 早期版本,篮牙要更新BIOS.
壹年後……
平時冇點用,拎翻蒞諗住插支咪試下,壹插塊主板烧左,前后寄翻去3次,先肯换塊新RGBA版本,前後各壹條m.2磁碟,插4pin小喇叭著機BOOT.
以雜牌蒞講都算好,保养3年,壹年後烧左换新. 祗係記憶體吾兼容,間隙輕機. AID64記憶體測試報錯.舊版本返宜兼容記憶體.唯有降低頻率加大時序.
用『Ryzen DRAM Calculator』睇時序配置.
記憶體 | 默認值 | 修定後 |
MEM FREQUENCY(Mhz) 頻率 | 2400 | 2133 |
主時序配置 | ||
Tcl | 15 | 20 |
Trcdrd | 15 | 20 |
Trcdwr | 15 | 20 |
Trp | 15 | 20 |
Tras | 35 | 38 |
副時序配置 | ||
Trc | 0 | |
Trrds | 4 | |
Trrdl | 6 | |
Tfaw | 23 | |
Twtrs | 3 |
休眠喚醒後顯示器黑屏,要撳『power』鍵重啟.BIOS 已UPADAE.『Win10/Linux』皆係.
B450-ITX | RGBA版 |
m.2磁碟 | 2 |
BOOT-4pin | 1 |
rgba燈 | 2 |
4pin風扇 | 2 |
3pin風扇 | 2 |
DEBUG | 1 |
之前係老竇屋企砌臺ITX電腦愛蒞睇片,『BE200』新出買蒞試試, 點知係係『b450-itx』可以認藍牙,唔認WIFI.反而係『x99-itx』藍牙WIFI都認.
唯有『AX210』配『b450-itx』, 『BE200』配『x99-itx』.
下載最新Intel WiFi驅動.
係電腦發展初時定義左套『ASCII碼』,得128字符,英文加數字用單字節BYTE. 後蒞各國皆自定『字符編碼』,『Shift-JIS/EUC-KR/BIG5/GB2312』皆占两字節WORD,结果係編碼重叠.所以先有亂碼.
字 | Low 8bit | Height 8bit |
ASCII-128 | 0 ~ 0x7F | N/A |
BIG5漢字 | 0xA1 ~ 0xF9 | 0x40 ~ 0x7E
0xA1 ~ 0xFE |
SHIFT-JIS日字 | 0x81~0x9f
0xe0~0xef |
0x40~0x7e
0x80~0xfc |
EUC-KR韓字 | 0xA1~0xFE | 0xA1~0xFE |
GB2312中字 | 0xA1 ~ 0xF7 | 0xA1 ~ 0xFE |
GBK中字 | 0x81 ~ 0xFE | 0x40 ~ 0xFE |
『UTF-8』係Unicode『萬國碼』變體,首byte前缀標記字符長度.前缀0長度1, 前缀110長度2, 前缀1110長度3.以此类推.尾随byte前缀皆標記01.
『UTF-8』bin | 長度 |
bin:0xxxxxxx | 1 |
bin:110xxxxx 10xxxxxx | 2 |
bin:1110xxxx 10xxxxxx 10xxxxxx | 3 |
bin:11110xxx 10xxxxxx 10xxxxxx 10xxxxxx | 4 |
bin:111110xx 10xxxxxx 10xxxxxx 10xxxxxx 10xxxxxx | 5 |
bin:1111110x 10xxxxxx 10xxxxxx 10xxxxxx 10xxxxxx 10xxxxxx | 6 |
UTF-8判定
if ((utf8[0] & 0x80) == 0x00)
return 1; |
值小於0x80的ASCII字元 |
if ((utf8[0] & 0xE0) == 0xC0 &&
(utf8[1] & 0xC0) == 0x80) return 2; |
2字節UTF-8字符 |
if ((utf8[0] & 0xF0) == 0xE0 &&
(utf8[1] & 0xC0) == 0x80 && (utf8[2] & 0xC0) == 0x80) return 3; |
3字節UTF-8字符 |
if ((utf8[0] & 0xF8) == 0xF0 &&
(utf8[1] & 0xC0) == 0x80 && (utf8[2] & 0xC0) == 0x80 && (utf8[3] & 0xC0) == 0x80) return 4; |
4字節UTF-8字符 |
if ((utf8[0] & 0xFC) == 0xF8 &&
(utf8[1] & 0xC0) == 0x80 && (utf8[2] & 0xC0) == 0x80 && (utf8[3] & 0xC0) == 0x80 && (utf8[4] & 0xC0) == 0x80) return 5; |
5字節UTF-8字符 |
if ((utf8[0] & 0xFE) == 0xFC &&
(utf8[1] & 0xC0) == 0x80 && (utf8[2] & 0xC0) == 0x80 && (utf8[3] & 0xC0) == 0x80 && (utf8[4] & 0xC0) == 0x80 && (utf8[5] & 0xC0) == 0x80) return 6; |
6字节UTF-8字符 |
值小於0x80係ASCII字符集
if ((string[0] & 0x80) == 0x00)
return 1; |
BIG5漢字符集編碼范圍
if ((string[0] >= 0xA1 && string[0] <= 0xF9) &&
(string[1] >= 0x40 && string[1] <= 0x7E || string[1] >= 0xA1 && string[1] <= 0xFE) ) return 2; |
SHIFT-JIS日字符集編碼范圍
if ((string[0] >= 0x81 && string[0] <= 0xF9 ||
string[0] >= 0xe0 && string[0] <= 0xef) && (string[1] >= 0x40 && string[1] <= 0x7E || string[1] >= 0xA1 && string[1] <= 0xFE) ) return 2; |
EUC-KR韓字符集編碼范圍
if ((string[0] >= 0xA1 && string[0] <= 0xFE) &&
(string[1] >= 0xA1 && string[1] <= 0xFE)) return 2; |
GB2312中字符集編碼范圍
if ((string[0] >= 0xA1 && string[0] <= 0xF7) &&
(string[1] >= 0XA1 && string[1] <= 0XFE) ) return 2; |
GBK中字符集編碼范圍
if ((string[0] >= 0x81 && string[0] <= 0xFE) &&
(string[1] >= 0XA0 && string[1] <= 0XFE) ) return 2; |
係電腦發展初時.定義左套『ASCII碼』,得128字符,英文加數字用單字節BYTE. 後蒞各國皆自定『字符編碼』,『BIG5/GB2312』皆占两字節WORD,结果係編碼重叠.所以先有亂碼.
UNICODE『萬國碼』,各國各自有獨立編碼段,吾重叠,同『ASCII碼』兼容.
『UNICODE』係設計之初每字符占『2 BYTE』即『USC2』字符集. 但係『2 BYTE』够支持65535字符.所以後蒞有『USC4』占『4 BYTE』.
係同壹字符串USC2同USC4會混合出現.
但係『ASCII碼』只需單字節『1 BYTE』. 所以發明左『UTF-8』以節約地方.
『UTF-8』同『UNICODE』按照下表互為轉换.
Unicode『USC2』字符集HEX | 『UTF-8』bin |
0x0000~0x007F | 0xxxxxxx |
0x0080~0x07FF | 110xxxxx 10xxxxxx |
0x0800~0xFFFF | 1110xxxx 10xxxxxx 10xxxxxx |
為左係同壹字符串『USC2』同『USC4』混合出現.係『USC4』字符『低16bit』同『高16bit』分別加前缀標記.
『低16bit』加『0xD800』,『高16bit』加『0xDC00』,再加壹區域0x10000.
前缀標記『0xD800』『0xDC00』各占6bit,各净低10bit加埋有『20bit』.够支持 『1048576』字符
USC4-低16bit前缀標記 | 0xD800 | BIN:110110 00000 00000 |
USC4-高16bit前缀標記 | 0xDC00 | BIN:110111 00000 00000 |
USC4 | 前缀標記 | USC4=前缀標記+字符 |
低16bit | 0xD800 | BIN:110110 00000 00000 + BIN:xxxxxxxxxx |
高16bit | 0xDC00 | BIN:110111 00000 00000 + BIN:xxxxxxxxxx |
utf8 轉 usc4
首字節 | value = utf8[sour] & (0xFF >> (bytes + 1));
++sour; |
尾随字節 | for (int i = 1; i < bytes; ++i) {
value = value << 6; value = value | (utf8[sour] & 0x3f);// 提低6bit ++sour; } |
减壹區域 | value = value – 0x10000 |
低16bit | unicode[dest] = 0xD800 | ((value >> 10) & 0x3ff ); |
高16bit | unicode[dest+1] = 0xDC00 | ((value) & 0x3ff);
dest = dest + 2; |
utf8 轉 usc2
首字節 | value = utf8[sour] & (0xFF >> (bytes + 1));
++sour; |
尾随字節 | for (int i = 1; i < bytes; ++i) {
value = value << 6; value = value | (utf8[sour] & 0x3f); ++sour; } |
反轉字節 | v = (value >> 24) & 0xFF;
unicode[dest] = v; v = (value >> 16) & 0xFF; if (v != 0) { unicode[dest] = (unicode[dest] << 8) + v; ++dest; } |
反轉字節 | v = (value >> 8) & 0xFF;
unicode[dest] = v; v = value & 0xFF; if (v != 0) { unicode[dest] = (unicode[dest] << 8) + v; ++dest; } |
Usc4轉utf8
提取字符 | value = (unicode[sour] – 0xD800) << 10 | (unicode[sour + 1] – 0xDC00); |
加壹區域 | value = value + 0x10000; |
Usc2轉utf8
提取字符 | value = unicode[sour]; |
首字節 | utf8[dest] = (0xFF << (8 – bytes)) | (value >> ((bytes – 1) * 6));
++dest; |
尾随字節 | for (int i = 1; i < bytes; ++i) {
utf8[dest] = 0x80 | (value >> ((bytes – i – 1) * 6) & 0x3F); ++dest; } ++sour; |
『UTF-8』首byte,前缀標記字符長度. 前缀0長度1, 前缀110長度2, 前缀1110長度3. 以此类推.尾随byte前缀皆標記01.
『UTF-8』bin | 長度 |
bin:0xxxxxxx | 1 |
bin:110xxxxx 10xxxxxx | 2 |
bin:1110xxxx 10xxxxxx 10xxxxxx | 3 |
bin:11110xxx 10xxxxxx 10xxxxxx 10xxxxxx | 4 |
bin:111110xx 10xxxxxx 10xxxxxx 10xxxxxx 10xxxxxx | 5 |
bin:1111110x 10xxxxxx 10xxxxxx 10xxxxxx 10xxxxxx 10xxxxxx | 6 |
按首BIT符號,計算UTF8字符長度,返回0非UFT8字符.
『UTF-8』字符 | |
if ((utf8[0] & 0x80) == 0x00)
return 1; |
0xxxxxxx |
if ((utf8[0] & 0xE0) == 0xC0 &&
(utf8[1] & 0xC0) == 0x80) return 2; |
110xxxxx 10xxxxxx |
if ((utf8[0] & 0xF0) == 0xE0 &&
(utf8[1] & 0xC0) == 0x80 && (utf8[2] & 0xC0) == 0x80) return 3; |
1110xxxx
10xxxxxx 10xxxxxx |
if ((utf8[0] & 0xF8) == 0xF0 &&
(utf8[1] & 0xC0) == 0x80 && (utf8[2] & 0xC0) == 0x80 && (utf8[3] & 0xC0) == 0x80) return 4; |
11110xxx
10xxxxxx 10xxxxxx 10xxxxxx |
if ((utf8[0] & 0xFC) == 0xF8 &&
(utf8[1] & 0xC0) == 0x80 && (utf8[2] & 0xC0) == 0x80 && (utf8[3] & 0xC0) == 0x80 && (utf8[4] & 0xC0) == 0x80) return 5; |
111110xx
10xxxxxx 10xxxxxx 10xxxxxx 10xxxxxx |
if ((utf8[0] & 0xFE) == 0xFC &&
(utf8[1] & 0xC0) == 0x80 && (utf8[2] & 0xC0) == 0x80 && (utf8[3] & 0xC0) == 0x80 && (utf8[4] & 0xC0) == 0x80 && (utf8[5] & 0xC0) == 0x80) return 6; |
1111110x
10xxxxxx 10xxxxxx 10xxxxxx 10xxxxxx 10xxxxxx |
unicode轉utf8 , ASCII碼相等.
int UnicodeToUTF8(char * utf8, const wchar_t * unicode)
{ int unicodeLength = 0; int bytes; int dest, sour; DWORD value; unicodeLength = Unicode_Length(unicode) ; sour = dest = 0; while (sour < unicodeLength) { bytes = 1; if (unicode[sour] >= 0xD800 && unicode[sour + 1] >= 0xDC00) bytes = 4; else if (unicode[sour] >= 0x00 && unicode[sour] <= 0x7F) bytes = 1; else if (unicode[sour] >= 0x80 && unicode[sour] <= 0x7FF) bytes = 2; else if (unicode[sour] >= 0x800 && unicode[sour] <= 0xFFFF) bytes = 3; else if (((unicode[sour + 1] << 16) | unicode[sour]) >= 0x10000 && ((unicode[sour + 1] << 16) | unicode[sour]) <= 0x1FFFFF) bytes = 4; else if (((unicode[sour + 1] << 16) | unicode[sour]) >= 0x200000 && ((unicode[sour + 1] << 16) | unicode[sour]) <= 0x3FFFFFF) bytes = 5; else if (((unicode[sour + 1] << 16) | unicode[sour]) >= 0x4000000 && ((unicode[sour + 1] << 16) | unicode[sour]) <= 0x7FFFFFFF) bytes = 6; else if (((unicode[sour + 1] << 16) | unicode[sour]) >= 0x80000000) bytes = 7;
if (bytes == 1) { utf8[dest] = unicode[sour]; ++dest; ++sour; } else if (unicode[sour] >= 0xD800 && unicode[sour + 1] >= 0xDC00) { value = (unicode[sour] – 0xD800) << 10 | (unicode[sour + 1] – 0xDC00); value = value + 0x10000; utf8[dest] = (0xFF << (8 – bytes)) | (value >> ((bytes – 1) * 6)); ++dest; for (int i = 1; i < bytes; ++i) { utf8[dest] = 0x80 | (value >> ((bytes – i – 1) * 6) & 0x3F); ++dest; } sour = sour + 2; } else if (bytes == 2 || bytes == 3) { value = unicode[sour]; utf8[dest] = (0xFF << (8 – bytes)) | (value >> ((bytes – 1) * 6)); ++dest; for (int i = 1; i < bytes; ++i) { utf8[dest] = 0x80 | (value >> ((bytes – i – 1) * 6) & 0x3F); ++dest; } ++sour; } else if (bytes >= 4) { value = (unicode[sour + 1] << 16) | unicode[sour]; utf8[dest] = (0xFF << (8 – bytes)) | (value >> ((bytes – 1) * 6)); ++dest; for (int i = 1; i < bytes; ++i) { utf8[dest] = 0x80 | (value >> ((bytes – i – 1) * 6) & 0x3F); ++dest; } sour = sour + 2; } } utf8[dest] = NULL; return dest; } |
utf8 轉 unicode
int UTF8ToUnicode(wchar_t * unicode, const char* utf8)
{ int utf8Length; int sour, dest; int bytes; dest = sour = 0; DWORD value; BYTE v; utf8Length = strlen(utf8); while (sour < utf8Length) { if ((utf8[sour] & 0x80) == 0x00) bytes = 1; else if ((utf8[sour] & 0xE0) == 0xC0) bytes = 2; else if ((utf8[sour] & 0xF0) == 0xE0) bytes = 3; else if ((utf8[sour] & 0xF8) == 0xF0) bytes = 4; else if ((utf8[sour] & 0xFC) == 0xF8) bytes = 5; else if ((utf8[sour] & 0xFE) == 0xFC) bytes = 6; else bytes = 7; if (bytes == 1) { unicode[dest] = utf8[sour]; ++dest; ++sour; } else if (bytes == 2 || bytes == 3) { value = utf8[sour] & (0xFF >> (bytes + 1)); ++sour; for (int i = 1; i < bytes; ++i) { value = value << 6; value = value | (utf8[sour] & 0x3f); ++sour; }
v = (value >> 24) & 0xFF; unicode[dest] = v; v = (value >> 16) & 0xFF; if (v != 0) { unicode[dest] = (unicode[dest] << 8) + v; ++dest; }
v = (value >> 8) & 0xFF; unicode[dest] = v; v = value & 0xFF; if (v != 0) { unicode[dest] = (unicode[dest] << 8) + v; ++dest; } } else if (bytes >= 4 ) { value = utf8[sour] & (0xFF >> (bytes + 1)); ++sour; for (int i = 1; i < bytes; ++i) { value = value << 6; value = value | (utf8[sour] & 0x3f); ++sour; } value = value – 0x10000; unicode[dest] = 0xD800 | ((value >> 10) & 0x3ff ); unicode[dest+1] = 0xDC00 | ((value) & 0x3ff); dest = dest + 2; } }
unicode[dest] = NULL; return dest; } |
『Android Studio』默認utf8編碼. 而『Visual Studio』按『地區設定』,轉本地字符編碼.
要强轉utf8可以係字加『u8』前缀
char utf8[MAX_CHAR] = u8″abcdef屌㞗𡳞杘屄”; |
加『u8』前缀後,代碼移稙『Android Studio』繁鎖.可以加編譯詣令.
#pragma execution_character_set(“utf-8”) |
适宜字符寫死係代碼. 若将字符保存係外部文檔,存為utf8即軟代碼.唔使諗編碼.
要强轉unicode係字加『L』前缀.USC2同USC4混埋.
wchar_t unicode[MAX_CHAR] = L”屌㞗𡳞杘屄”; |
經緯度座標有叄種格式,『度分秒』『度分』『度』.
『度分秒』等於『時分秒』, 『1度=60分=3600秒』『1分=60秒』
經緯度座標 | |
度分秒DMS | DDD°MM’SS” |
度分DM | DDD°MM.MMM’ |
度D | DDD.DDDDD° |
度分秒 | 轉换 |
分轉度 | 除60 |
秒轉度 | 除3600 |
秒轉分 | 除60 |
度轉分 | 度小數乘60 |
分轉秒 | 分小數乘60 |
『度分秒』轉『度』
例『35°41′37.5″』即係『35度41分37.5秒』 |
41分轉度= 41/60 |
37.5秒轉度=37.5/3600 |
35 + 41/60 + 37.5/3600=35.69375度 |
void DMS_TO_DD(float D,float M,float S,double * DD)
{ *DD = D + M/60.0f + S/3600.0f; } |
『度分』轉『度』
例『35°41.625』即係『35度41.625分』 |
41.625分轉度= 41/60 |
35 + 41.625/60 =35.69375度 |
void DM_TO_DD(float D, float M, double* DD)
{ *DD = D + M / 60.0f; // 除60 } |
『度』轉『度分』
例『35.6937632°』即係『35度41.625792分』 |
『0.6937632°』度轉分 0.6937632*60=41.625792′ |
35 + 0.6937632*60=『35°41.625792’』=『35度41.625792分』 |
void DD_TO_DM(double DD,int * D,float * M)
{ *D = (int)DD; // 度取整 *M = (DD – *D) * 60; // 度小數乘60 } |
『度』轉『度分秒』
例『35.6937632°』度即係『35度, 41分, 37.54秒』 |
取度小數『0.6937632°』度轉分 0.6937632°*60=41.625792′ |
取分小數『0.625792’』分轉秒 0.625792’*60=37.54752″ |
35°+ 0.6937632°*60 + 0.625792’*60=『35°41′37.5″』=『35度, 41分, 37.54秒』 |
void DD_TO_DMS(double DD, float* D, float* M, float* S)
{ float MM; *D = (int)DD; // 度取整 MM = (DD – *D) * 60; // 度小數乘60 *M = (int)MM;// 分 *S = (*M – MM) * 60;// 分小數乘60 } |
1日 | 360度 |
1度 | 60分=3600秒 |
1分 | 60秒 |
係Windows拖拽或者縮放窗口, 會造成窗體閃爍, 啟用象筋拖放, 即係非實時拖放,可避免窗體閃爍.
進入像筋拖放 |
SystemParametersInfo(SPI_SETDRAGFULLWINDOWS, true, &drag_full_windows, NULL); |
退出像筋拖放 |
SystemParametersInfo(SPI_SETDRAGFULLWINDOWS, false, &drag_full_windows, NULL); |
通過監聽『WM_ENTERSIZEMOVE』進入拖拽, 『WM_EXITSIZEMOVE』退出像筋拖拽, 實施像筋象筋拖放
LRESULT CALLBACK WindowProc(HWND hWnd,UINT msg,WPARAM wParam,LPARAM lParam){ |
if (msg == WM_ENTERSIZEMOVE)
SystemParametersInfo(SPI_SETDRAGFULLWINDOWS, true, &drag_full_windows, NULL);// 進入像筋拖放 else |
if (msg == WM_EXITSIZEMOVE)
SystemParametersInfo(SPI_SETDRAGFULLWINDOWS, false, &drag_full_windows, NULL);// 退出像筋拖放 |
return(DefWindowProc(hWnd, msg, wParam, lParam));
} |
WD BLACK AN1500原配两條SN730仲有ARGB燈,有人拆出蒞䶒賣殼.睇中佢自動组建Raid0,讀寫至高達『6500MB/S』,諗住買翻『SN730-1TB』, 睇到『PC300-1TB』特價,仲係『MLC SSD』. 1TB仲係1024GB.
打孖插入『PC300-1TB』自建Raid0. 温度高達65℃. 讀『3800 MB/S』,寫『2194MB/S』. 比『SN730』慢.
WD BLACK AN1500-Raid0 | PC300 NVMe SK Hynix 1TB*2 |
CrystalDiskMark讀 | 2800 MB/S |
CrystalDiskMark寫 | 2194MB/S |
CrystalDiskInfo | 69℃. |
MLC SSD | SK Hynix H2702T8C0B3A |
WD AN1500 | |
上行 | 6500MB/S |
下行 | 6500MB/S |
總線 | PCIe Gen3*4 SSD |
『ZLIB』係開源『壓縮』同『解壓』程式庫, 支持『DEFLATE』冇損壓縮算法,混合『LZ77算法』同『霍夫曼編碼』.
『Visual studio』冇內置『ZLIB』,下載『zlib-1.2.13.tar.gz』再編譯.
http://www.zlib.net/ |
http://www.zlib.net/zlib-1.2.13.tar.gz |
路徑 | 版本 |
C:\Program Files (x86)\zlib-1.2.13\build\Debug | Debug |
C:\Program Files (x86)\zlib-1.2.13\build\Release | Release |
Debug調試版 | Release發行版 | |
zlibstaticd.lib | zlibstatic.lib | 静態庫, 唔使dll |
zlibd.lib | zlib.lib | 動態庫, 要dll |
zlibd.dll | zlib.dll | 動態連结 |
C:\Program Files\zlib\include\zconf.h | Zlib-API |
C:\Program Files\zlib\include\zlib.h |
#include <zlib.h> | Zlib-api |
#include <zconf.h> |
#if _DEBUG | |
#pragma comment(lib, “..\\ZLIB\\zlibstaticd.lib”)
#else |
|
#pragma comment(lib, “..\\ZLIB\\zlibstatic.lib”)
#endif |
『CMake』愛蒞生成makefile或project文件, 畀Visual studio編譯代碼.
登入『CMake官網』下載『cmake-3.27.7-windows-x86_64.msi』安装包.
驗証CMake安装
https://cmake.org/ |
https://cmake.org/download/ |
cmake-3.28.0-rc3-windows-x86_64.msi |
cmake-3.27.7-windows-x86_64.msi |
上次『USB3.0壹拆貳』插『SD讀卡機』冇反應,改買臺彎汤銘TERMINUS-FE2.1芯片,『USB2.0 壹拆肆』.聽講兼容冚辦闌USB2.0機體.
冇定位窿, 3D打印磁吸底座,吸係機槓壁.配線够長.
部『SD讀卡機』係USB3.0-19PIN,要轉9PIN.好彩識認.
華南X99-F8D Plus
臺X570冇定時輕機,睇翻佢本天書,要用『1R8/2R8-DDR4』記憶體,買两條32GB成千幾紋,索性買雜牌X99玩,開機慢到以為吾著. 壹分鐘先睇到bios logo
配置如下
雜牌X99-F8D Plus有捌條DDR4槽, 單條支持至高64GB.捌條槽最高512GB.DDR4-64GB依然偏貴.块X99話支持肆通道.買两條用住先.
買左雜牌『X99-F8D PLUS』, 睇岩『E5-2637 V4』支持雙U,頻率至高.『基頻3.5GHZ』畀『E5-1630V4』低200HZ.
用CPU-Z測單線程相若. 多線程跑分接近壹倍. 可能同雙CPU有關.
INTEL XEON | E5-2637V4 | E5-1630V4 | E5-2630LV3 |
CPU-Z單線程 | 462.4 | 470.7 | 233.2 |
CPU-Z多線程 | 4368.2 | 2350.2 | 2136.7 |
主頻 | 3.5GHZ | 3.7GHZ | 1.8GHZ |
核心 | 4核 | 4核 | 8核 |
線程 | 8線程 | 8線程 | 16線程 |
TDW | 140W | 140W | 55W |
買左雜牌『x99-EATX』,舊式ATX機槓要拆左光驅位支架.冇臺鉆拆拉釘驚拆爛.索性新買EATX機槓W100,分左右腔.10條PCIE槽位,有主板要11條PCIE槽位.
左腔裝主板同風扇,為左装『23030風扇』要移有機玻璃去門板外側.
右腔得86mm寬,装3.5寸機體同埋atx火牛都掹水,早知買W200吾使搞甘耐.
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