The tool utilizes state-of-the-art Dreambooth technology, which is an open-source deep learning generation model developed in 2022 that allows users to train AI models on their own photos to generate any type of image they desire. See yourself as never before with AI. No Strings Attached. Make a One-Time Payment Starting at Just $11.99. No Subscriptions.
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Based on our record, Datature should be more popular than TheDream.AI. It has been mentiond 7 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I checked thedream.ai, but its expensive and also looks like it can convert only to limited options. Source: about 1 year ago
Of course, you can write your own code, in that case, think of it as an interactive matplotlib then! Also, it helps to mention we run a startup Datature, that is a no-code MLOps platform, hence explaining why we are focusing on removing the coding portion of this process :P. Source: almost 3 years ago
A while ago, we announced here that we built Datature and a bunch of users gave feedback and even built MaskRCNN models on our platform! However, we were sending collab updates back and forth - it was a mess. Hence we made Portal for any TensorFlow users to load TF2.0 models (any models off TF2 Model Hub works) and inspect your model visually on your dataset. Source: almost 3 years ago
If you'd like to train a tensorflow object detection model, you can check out https://datature.io - theres about 30 different models you can select from and you can add augmentation to your pipeline. Source: about 3 years ago
If you will be training an object detection model at the end, you can check out https://datature.io - you can annotate your data in browser (no installation) and train an object detection model + deploy when you are done for free! Source: about 3 years ago
Feel free to try it out at https://datature.io - additionally, we are always looking out for feedback and feature requests. We are working more MLOps feature to support teams, so let us know of your thoughts :). Source: about 3 years ago
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