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Monotone - BnW Film Emulation

Monotone - BnW Film Emulation

talonsodev

Photo & Video免费v1.80
App Store
评分

4.0

24 条评分

星级

★★★★☆

最近更新

2026年4月22日

发布日期

2020年8月5日

更新内容

v1.80

Solves a problem with camera presets

应用信息

开发者
talonsodev
分类
Photo & Video
价格
免费
版本
1.80
App ID
1497664944

简介

Turn Your Photos and Videos into Timeless Black & White Masterpieces with Monotone! Monotone is the ultimate black-and-white editor for photos and videos — crafted for creators who want their visuals to stand out with style, depth, and emotion. With over 300 premium black-and-white filters, including rich duotones and authentic vintage presets, Monotone lets you instantly transform any image or video into a stunning monochrome work of art. • Powerful Editing Tools at Your Fingertips: • Advanced Controls: Fine-tune every detail with curves, vignettes (Classic & Natural), overlays, and custom film grain for both photos and videos. • Creative Flexibility: Use HSL sliders tailored for black & white conversion, or dive deep with pro-level tools like Photoshop-style Calculations. • Preset Sharing Made Easy: Import filters instantly by scanning QR codes. Real Film Emulation – No Filters Feel This Real: Get the unmistakable feel of classic analog film. Monotone includes a wide range of carefully profiled film stocks to bring depth and texture to your work. Included film looks: • Agfa: APX 25, APX 100, APX 400, Scala 200 • Fomapan: 100, 200 • Fuji: FP 3000b, Neopan 100 Acros, Neopan 400, Neopan 1600 • Ilford: Delta 100, 400, 800, 3200, FP4 Plus 125, HP5 Plus, Ortho 80, Pan F, SFX 200, XP2 • Kodak: T-MAX 100, 400, P3200, TRI-X 200, TRI-X 400 • Others: Konica 750, Polaroid 664/667/672, Rollei 25, Rollei IR 400 Whether you're a photographer, filmmaker, or someone who loves monochrome's timeless look, Monotone gives you total creative control. Download Monotone today and discover how stunning black & white can be.

下载量预测

专业 · 预览

预估总下载量

2K1K3K
保守估计乐观估计

17

低 / 月

24

预估 / 月

43

高 / 月

基于24 条评分
假设评分率1.4%
应用年龄70 个月

基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。