All content for semantic segmentation

Deploy Development MP Wiki


Deep learning optimizer literature starts with Gradient Descent and the Stochastic Gradient Descent (SGD) is one very widely used version of it. The …

Development Deploy MP Wiki

Shift Scale Rotate

Parameters Probability It is the probability of applying the transformation to the sample images. Higher probability means that the expected number …

Development Deploy MP Wiki

Smallest max size

Parameters Minimum size of smallest side The parameter that specifies the length of the maximum size that is to be used to resize minimum side of the …

Development User documentation

Split Results

What will you see after splits? After creating a split for a particular machine learning task with given sets of data, the user is able to see the …

Deploy Development MP Wiki


StepLR decays the initial learning rate with some multiplicative factor. The decaying happens every N epochs or every N eval period (in case …

Development MP Wiki


Some classification problems do not have a balanced number of examples for each class label. For example, for a simple classification task, there …

Deploy User documentation

TorchScript Sample Inference Scripts

In the following pages we provide sample scripts which can be used to run TorchScript models in python. Please keep in mind that these models can …

Development Deploy MP Wiki


Architecture The architecture in UNET consists of two paths. Contracting path (encoder network) followed by an expansive path (decoder network). …

Development Deploy MP Wiki


UNet++ is a new versatile image segmentation architecture designed to improve image segmentation accuracy. UNet++ consists of U-Nets of varying …

Development User documentation

Upload images

On this screen, you can create and remove datasets in a project. Datasets are collections of images, not unlike folders in your operating system, …

Development User documentation

Users and Roles

On this screen, you can control who can do what in your project. It consists of two parts. At the top, we have Users where you can invite a user and …

Deploy Development MP Wiki


Warm-up is a way to reduce the primacy effect for adaptive schedulers like Adam or AdamW of the early training examples. It allows them to compute …

Previous Next

Get AI confident. Start using Hasty today.

Our platform is completely free to try. Sign up today to start your two-month trial.

Tuple helped us improve our ML workflow by 40%, which is fantastic. It reduced our overall investment by 90% to get high-quality annotations and an initial model.