TinyPNG
TinyPNG (by Tinify) is a free image optimization service built for developers and designers. It utilizes smart lossy compression to reduce the file sizes of JPEG, PNG, WebP, and AVIF files by up to 80% with no visible quality loss. That means faster load times, better SEO, and lower bandwidth.
You can compress, convert, and resize images via a clean web interface or integrate it into your workflow with the API. The platform also provides an image CDN for fast global delivery of optimized assets. SDKs are available for Python, Node.js, PHP, Java, Ruby, and .NET. WordPress plugin included, plus plenty of community-driven integrations.
No tuning, no noise, Tinify just works. Whether you're optimizing a handful of images or processing millions, it scales effortlessly. All plans include a generous free tier, and support is quick when you need it.
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Acuity PPM
Acuity PPM provides Project Management Teams (PMO's) with lightweight and easy-to-use software to manage the project portfolio. Acuity PPM provides a Work Intake module to support demand management and helps you create and evaluate new project requests through prioritization, financial planning and resource management (capacity planning).
Once a request is approved, project teams can track project progress with centralized status reports, track key milestones, risks, issues, financial plans, decisions, lessons learned, project and portfolio roadmaps, and resource plans in Acuity PPM. This helps leadership teams select the right projects for the organization.
Connect to common Project Management tools such as Jira, Smartsheet, Asana, Wrike, Monday.com, and others.
PMO's don't need complicated and cumbersome software, which is too complex for most users to use. Our modular approach allows PMO's to add functionality as they need it, since most Project Management Offices are at maturity level 1 or 2. This allows you to pay only for what you use and not for what you donât. That's fair.
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Google Cloud Vision AI
Harness the power of AutoML Vision or leverage pre-trained Vision API models to extract meaningful insights from images stored in the cloud or at the network's edge, allowing for emotion detection, text interpretation, and much more. Google Cloud presents two advanced computer vision solutions that utilize machine learning to provide top-notch prediction accuracy for image analysis. You can streamline the creation of bespoke machine learning models by simply uploading your images, using AutoML Vision's intuitive graphical interface to train these models, and fine-tuning them for optimal performance in terms of accuracy, latency, and size. Once perfected, these models can be seamlessly exported for use in cloud applications or on various edge devices. Additionally, Google Cloudâs Vision API grants access to robust pre-trained machine learning models via REST and RPC APIs. You can easily assign labels to images, categorize them into millions of pre-existing classifications, identify objects and faces, interpret both printed and handwritten text, and enhance your image catalog with rich metadata for deeper insights. This combination of tools not only simplifies the image analysis process but also empowers businesses to make data-driven decisions more effectively.
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Amazon Rekognition
Amazon Rekognition simplifies the integration of image and video analysis into applications by utilizing reliable, highly scalable deep learning technology that doesnât necessitate any machine learning knowledge from users. This powerful tool allows for the identification of various elements such as objects, individuals, text, scenes, and activities within images and videos, alongside the capability to flag inappropriate content. Moreover, Amazon Rekognition excels in delivering precise facial analysis and search functions, which can be employed for diverse applications including user authentication, crowd monitoring, and enhancing public safety.
Additionally, with the feature known as Amazon Rekognition Custom Labels, businesses can pinpoint specific objects and scenes in images tailored to their operational requirements. For instance, one could create a model designed to recognize particular machine components on a production line or to monitor the health of plants. The beauty of Amazon Rekognition Custom Labels lies in its ability to handle the complexities of model development, ensuring that users need not possess any background in machine learning to effectively utilize this technology. This makes it an accessible tool for a wide range of industries looking to harness the power of image analysis without the steep learning curve typically associated with machine learning.
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