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Which is more popular?
Based on our record, Zeplin
seems to be more popular. It has been mentioned
23 times
since March 2021.
social mentions
23 vs 0
Design Tools popularity
100% vs 0%
Base details
Website, pricing, platforms and company facts side by side.
Ease of Collaboration Zeplin facilitates seamless collaboration between designers and developers by providing a shared space where they can access design specifications, assets, and resources.
Design Consistency By offering detailed design specifications and exportable assets, Zeplin ensures consistency across different development platforms and helps maintain a unified design system.
Automated Asset Export Zeplin automatically generates assets in various formats and resolutions, which saves time and reduces the likelihood of errors during the handoff process.
Integration with Design Tools Zeplin integrates seamlessly with popular design tools like Sketch, Adobe XD, Figma, and Photoshop, making it easy for designers to upload and manage their projects.
Version Control The platform offers version control for design projects, enabling teams to track changes, revert to previous versions, and ensure they're always working with the most up-to-date designs.
Possible disadvantages
Pricing Zeplin's subscription model can be costly for smaller teams or individual freelancers, especially when compared to other design handoff tools available in the market.
Limited Prototyping Features Unlike some other design collaboration tools, Zeplin lacks advanced prototyping features, which might necessitate the use of additional tools for complete design validation.
Learning Curve New users may require some time to learn Zeplin’s interface and features, which could be a challenge for teams that need to quickly onboard and get up to speed.
Dependency on Design Tools Zeplin relies heavily on imported designs from other tools rather than allowing for direct design creation within its platform. This dependency could be a limitation for teams looking for an all-in-one solution.
Limited Free Tier The free version of Zeplin is quite limited in terms of the number of projects and collaborators, which might not be sufficient for larger teams or complex projects.
Efficient Data Curation Lightly uses active learning and self-supervised learning techniques to help teams select the most valuable and diverse subset of data for labeling, reducing the amount of data needed for training while maintaining model performance.
Reduces Labeling Costs By intelligently selecting which images or videos to label, Lightly can significantly cut down on the manual annotation costs and time required for building computer vision datasets.
Self-Supervised Learning Integration The platform leverages self-supervised learning methods to extract meaningful embeddings from unlabeled data, enabling better understanding of dataset structure and redundancy before labeling.
Scalable for Large Datasets Lightly is designed to handle large-scale image and video datasets, making it suitable for enterprises dealing with massive amounts of visual data in computer vision projects.
Integration with ML Workflows Lightly offers APIs and integrations that allow it to fit into existing machine learning pipelines, working alongside popular annotation tools and cloud storage solutions.
Possible disadvantages
Learning Curve Teams new to active learning and self-supervised learning concepts may face a learning curve in understanding how to best utilize Lightly's data curation capabilities.
Narrow Use Case Focus Lightly is primarily focused on computer vision data curation, which may limit its usefulness for teams working with other data types such as text, audio, or tabular data.
Dependency on Data Quality The effectiveness of Lightly's curation algorithms depends heavily on the quality and representativeness of the initial dataset, which can limit results if the source data is poor.
Pricing for Smaller Teams Depending on the pricing tier, smaller teams or individual developers might find the cost of enterprise-level data curation features less accessible compared to open-source alternatives.
Requires Technical Expertise Effectively leveraging Lightly's advanced features like self-supervised learning models may require a certain level of machine learning expertise, which could be a barrier for less technical teams.
Analysis
An editorial look at what each product does well and who it suits.
ZeplinLightly
Overall verdict
Zeplin is generally considered a good tool, especially for teams seeking better collaboration between designers and developers. Its features are highly appreciated for accuracy and efficiency in implementing design visions. However, its usefulness might depend on specific team needs and workflows.
Why this product is good
Zeplin is a popular tool among designers and developers for its ability to bridge the gap between design and development processes. It excels in organizing design files, annotations, and specifications, making it easier for development teams to implement designs accurately. It integrates seamlessly with design tools like Figma, Sketch, and Adobe XD, and provides features like automated design specs, style guides, and assets that streamline the workflow. Its collaborative features allow for efficient communication and feedback loops between team members.
Recommended for
Zeplin is best suited for designers and developers working in teams where clear design specifications and organized collaboration are critical. It's particularly beneficial for teams using Figma, Sketch, or Adobe XD who want to ensure precise design implementation and reduce misunderstandings between design and development departments.
Overall verdict
Lightly is a solid, well-regarded platform for data curation and active learning in computer vision, offering strong tooling for selecting the most valuable images/frames to label, which helps teams reduce annotation costs and improve model performance efficiently.
Why this product is good
Focuses on smart data selection and curation, helping avoid wasted labeling budget on redundant data
Offers both open-source (Lightly SSL) and commercial (Lightly Worker/Platform) options for flexibility
Uses self-supervised learning techniques to find diverse, representative, or edge-case samples
Integrates with common MLOps and labeling tools, fitting into existing computer vision pipelines
Scales to large unlabeled datasets, making it useful for teams with massive raw data but limited labeling resources
Provides visualization and embedding tools to explore dataset distribution and detect biases or gaps
Recommended for
Computer vision teams looking to reduce labeling costs through smarter data selection
ML engineers building active learning pipelines
Companies with large volumes of unlabeled image or video data
Teams wanting to improve model performance by curating more diverse or representative training sets
Organizations needing to detect dataset bias, redundancy, or edge cases before annotation
As aforementioned, Zeplin suffers some inherent drawbacks that may dent designers’ hopes for faster, easy, and reliable UI design. To avert such scenarios, you don’t have to get stuck with Zeplin as there are numerous...
Zeplin is super affordable. It offers 2 plans: Team, which costs $8.00 per user per month, and Establishment, which costs $16.00 monthly. Zeplin also provides a feature-limited Free Plan and Enterprise Plan.
Zeplin is a workspace collaboration tool to document what to build and how designs should behave in a central collaborative place for the entire dev team.
Tools like Zeplin's AI layer, Supernova, and the emerging generation of Figma plugins with AI backends do this today. The output is not a PDF full of screenshots. It is structured data: exact values, token references, and context — the...
- Source: dev.to
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8 months ago
Additionally, thank you to all our community launch partners across the frontend ecosystem for helping us bring Storybook 8 to the world! Thanks to Chromatic, Figma, ViteConf, Omlet, DivRiots, story.to.design, StackBlitz, UXpin, Nx, Mock...
- Source: dev.to
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over 2 years ago
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