Question: Can you suggest a solution that allows me to easily integrate face detection and pose detection into my application?

If you're looking for a way to build an app that combines face detection and pose detection, Raman Labs could be a good fit. It's got a collection of machine learning modules that are geared for real-time performance and are relatively easy to use. The modules can be used for a range of computer-vision tasks, including face detection and pose detection, and are designed to be fast, easy to use and robust. Its API is relatively low-level but works on Python 3 and Numpy, so it's adaptable to a lot of situations.

Another option is ezML, which offers a lightweight API and low-code interface for building your own computer vision apps. It can handle facial analysis, but also other more advanced prebuilt abilities like image classification and object detection. ezML is designed to scale, so your app will be able to handle a lot of load without suffering in performance, and it's a good option for a lot of different businesses.

If you want to run your facial recognition code in the cloud, Luxand offers a full-featured facial recognition API with abilities like age detection, emotion detection and face cropping. The service is geared for web and mobile apps and can handle a lot of photos. Luxand's cloud infrastructure is designed to scale to your needs, so it's a good option if you need a lot of facial recognition power.

Last, Imagga offers a broader range of image recognition abilities, including facial recognition, visual search and content moderation. It offers customizable machine learning technology and several integration options, so Imagga can be used by real estate and media companies, for example. Its tiered pricing plan means you can pay for what you need, so it's a good option for developers and businesses.