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Presenter webcam

ライブラリのうち42フレームがPresenter webcamに一致し、9ブランドの動画9本にまたがっています。どれも動画そのものから計測したもので、説明文から読み取ったものではありません。つまりこれは、スタイルガイドが説くあるべき姿ではなく、実際にどう使われているかです。

このページにレンダリング画像も機材リストもありません。下にあるのはどれも実際に見に行ける動画の本物の1秒であり、どの数値もサンプルからの推定ではなく実フレームを数えたものです。

フレーム
42
動画
9
ブランド
9
カット間隔の中央値
15.8秒

最も多く撮っているのは

各ブランドがこの切り口にどれだけフレームを出しているかの順です。

Farza 7フレームWispr Flow 6フレームThings Inc 6フレームAmmaar Reshi 6フレームLobe 6フレームProduct Fit 6フレーム
Mobbin I Gave Claude 600,000 UI Screens… Then This Happened at 2:02corner inset
MobbinI Gave Claude 600,000 UI Screens… Then This Happened
2:02
Mobbin I Gave Claude 600,000 UI Screens… Then This Happened at 2:18corner inset
MobbinI Gave Claude 600,000 UI Screens… Then This Happened
2:18
Mobbin I Gave Claude 600,000 UI Screens… Then This Happened at 2:22corner inset
MobbinI Gave Claude 600,000 UI Screens… Then This Happened
2:22
Things Inc New features on desktop web at 1:30wide presenter
Things IncNew features on desktop web
1:30
Things Inc New features on desktop web at 1:34medium presenter
Things IncNew features on desktop web
1:34
Things Inc New features on desktop web at 1:38wide presenter
Things IncNew features on desktop web
1:38
Things Inc New features on desktop web at 1:42wide presenter
Things IncNew features on desktop web
1:42
Things Inc New features on desktop web at 1:46wide presenter
Things IncNew features on desktop web
1:46
Things Inc New features on desktop web at 1:50wide presenter
Things IncNew features on desktop web
1:50
Ammaar Reshi Introducing Gemini 3.5 Transcribe 🚀 Our most precise speech to text... at 1:34corner inset
Ammaar ReshiIntroducing Gemini 3.5 Transcribe 🚀 Our most precise speech to text...
1:34
Ammaar Reshi Introducing Gemini 3.5 Transcribe 🚀 Our most precise speech to text... at 1:38corner inset
Ammaar ReshiIntroducing Gemini 3.5 Transcribe 🚀 Our most precise speech to text...
1:38
Ammaar Reshi Introducing Gemini 3.5 Transcribe 🚀 Our most precise speech to text... at 1:42corner inset
Ammaar ReshiIntroducing Gemini 3.5 Transcribe 🚀 Our most precise speech to text...
1:42
Ammaar Reshi Introducing Gemini 3.5 Transcribe 🚀 Our most precise speech to text... at 1:46corner inset
Ammaar ReshiIntroducing Gemini 3.5 Transcribe 🚀 Our most precise speech to text...
1:46
Ammaar Reshi Introducing Gemini 3.5 Transcribe 🚀 Our most precise speech to text... at 1:50corner inset
Ammaar ReshiIntroducing Gemini 3.5 Transcribe 🚀 Our most precise speech to text...
1:50
Ammaar Reshi Introducing Gemini 3.5 Transcribe 🚀 Our most precise speech to text... at 1:54corner inset
Ammaar ReshiIntroducing Gemini 3.5 Transcribe 🚀 Our most precise speech to text...
1:54
Product Fit Quick introduction at 0:42corner inset
Product FitQuick introduction
0:42
Product Fit Quick introduction at 0:46corner inset
Product FitQuick introduction
0:46
Product Fit Quick introduction at 0:50corner inset
Product FitQuick introduction
0:50
Product Fit Quick introduction at 0:54corner inset
Product FitQuick introduction
0:54
Product Fit Quick introduction at 0:58corner inset
Product FitQuick introduction
0:58
Product Fit Quick introduction at 1:02corner inset
Product FitQuick introduction
1:02
Lobe Introducing Lobe | Build your first machine learning model in ten minutes. at 8:44corner inset
LobeIntroducing Lobe | Build your first machine learning model in ten minutes.
8:44
Lobe Introducing Lobe | Build your first machine learning model in ten minutes. at 8:52corner inset
LobeIntroducing Lobe | Build your first machine learning model in ten minutes.
8:52
Lobe Introducing Lobe | Build your first machine learning model in ten minutes. at 9:00corner inset
LobeIntroducing Lobe | Build your first machine learning model in ten minutes.
9:00
Lobe Introducing Lobe | Build your first machine learning model in ten minutes. at 9:08corner inset
LobeIntroducing Lobe | Build your first machine learning model in ten minutes.
9:08
Lobe Introducing Lobe | Build your first machine learning model in ten minutes. at 9:16corner inset
LobeIntroducing Lobe | Build your first machine learning model in ten minutes.
9:16
Lobe Introducing Lobe | Build your first machine learning model in ten minutes. at 9:24corner inset
LobeIntroducing Lobe | Build your first machine learning model in ten minutes.
9:24
Farza Pretty insane usage on this rn. > 80,000 messages sent. > 10,0... at 2:49corner inset
FarzaPretty insane usage on this rn. > 80,000 messages sent. > 10,0...
2:49
Farza Pretty insane usage on this rn. > 80,000 messages sent. > 10,0... at 2:53corner inset
FarzaPretty insane usage on this rn. > 80,000 messages sent. > 10,0...
2:53
Farza Pretty insane usage on this rn. > 80,000 messages sent. > 10,0... at 2:57wide presenter
FarzaPretty insane usage on this rn. > 80,000 messages sent. > 10,0...
2:57
Farza Pretty insane usage on this rn. > 80,000 messages sent. > 10,0... at 3:01wide presenter
FarzaPretty insane usage on this rn. > 80,000 messages sent. > 10,0...
3:01
Farza Pretty insane usage on this rn. > 80,000 messages sent. > 10,0... at 3:25corner inset
FarzaPretty insane usage on this rn. > 80,000 messages sent. > 10,0...
3:25
Farza Pretty insane usage on this rn. > 80,000 messages sent. > 10,0... at 3:29wide presenter
FarzaPretty insane usage on this rn. > 80,000 messages sent. > 10,0...
3:29
Farza Pretty insane usage on this rn. > 80,000 messages sent. > 10,0... at 3:33wide presenter
FarzaPretty insane usage on this rn. > 80,000 messages sent. > 10,0...
3:33
Wispr Flow Watch Flow in Action at 0:10corner inset
Wispr FlowWatch Flow in Action
0:10
Wispr Flow Watch Flow in Action at 0:13corner inset
Wispr FlowWatch Flow in Action
0:13
Wispr Flow Watch Flow in Action at 0:16corner inset
Wispr FlowWatch Flow in Action
0:16
Wispr Flow Watch Flow in Action at 0:19corner inset
Wispr FlowWatch Flow in Action
0:19
Wispr Flow Watch Flow in Action at 0:22corner inset
Wispr FlowWatch Flow in Action
0:22
Wispr Flow Watch Flow in Action at 0:25corner inset
Wispr FlowWatch Flow in Action
0:25
Loops How to get design feedback from any audience in under 30 mins at 0:34
LoopsHow to get design feedback from any audience in under 30 mins
0:34
37signals How does Basecamp work? at 2:22corner inset
37signalsHow does Basecamp work?
2:22
これで全 42 枚です。

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