Best Emotion Recognition Software for Mac of 2024

Find and compare the best Emotion Recognition software for Mac in 2024

Use the comparison tool below to compare the top Emotion Recognition software for Mac on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    MorphCast Reviews
    MorphCast AI Interactive Video Platform allows creatives to create highly engaging interactive videos in just minutes. Our Facial Emotion AI integrated into the platform allows for the latest interaction options. The video content can also be triggered by viewers facial expressions while they are watching it. MorphCast, a dynamic tool for professionals, is available. It is available for free at Microsoft and Mac App Store. The minutes of views to your videos are all that you pay. The first 2.000 minutes per month are free. MorphCast also provides an analytics dashboard that allows you to evaluate the performance and effectiveness of your interactive videos. You can track how your contents perform, and adjust your audience's experience based on their interaction and emotional response.
  • 2
    alwaysAI Reviews
    AlwaysAI offers developers a simple and flexible way for them to create, train, and deploy computer-vision applications to a wide range of IoT devices. You can choose from a variety of deep learning models, or upload your own. Our flexible and customizable APIs make it easy to quickly enable core computer vision services. You can quickly prototype, test, and iterate using a variety camera-enabled ARM32, ARM64, and x86 devices. Identify objects in an image using their names or classifications. Identify and count objects in real-time video feeds. Follow the same object through a series of frames. To count or track faces or complete bodies in a scene, locate them. Identify and draw borders around objects. You can separate the key objects from the background visuals in an image. Determine human body postures, fall detection, and emotions. To train an object detection model, use our model training toolkit. You can create a model that is tailored to your particular use-case.
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