v4.1.2 🌈

• 100x search time improvement with MAXSIM for ColPali using pooling
• Fixed deadlock issues with multiprocessing
• Improved core engine stability and performance

v4.1 adds the following major features

• Ability to add linked rows for images, segment masks and binary masks
• Ability to save query views through tagging
• Integration with MMDetection and MMSegmentation
• Autocommit the data at the session exit
• Ability to create dynamic arrays
• Ability to create structures with known schema

v4.1.1 🌈

• Bug fixes in deeplake.convert and performance improvements in data ingestion.
• Fixed TQL UNION expression for the same source.
• Better support for multiprocessing.

v4.1 adds the following major features

• Ability to add linked rows for images, segment masks and binary masks
• Ability to save query views through tagging
• Integration with MMDetection and MMSegmentation
• Autocommit the data at the session exit
• Ability to create dynamic arrays
• Ability to create structures with known schema

v3.9.34 🌈

🧭 What's Changed

• Updated versions for 3.9.34 release (#3005) @activesoull
• V3 labelbox api export improvements (#3007) @tyesayan
• fix azure view loading (#3006) @activesoull
• Update version for the next release (#3002) @activesoull
• make libdeeplake dependency to always download the latest release (#3004) @activesoull

⚙️ Who Contributes

@activesoull and @tyesayan

v3.9.33 🌈

🧭 What's Changed

• Update version for the next release (#3002) @activesoull
• Fixed query result datatests merged class_label tensor's class_names consistent @activesoull
• Make libdeeplake dependency to always download the latest release (#3004) @activesoull

⚙️ Who Contributes

@activesoull

v4.1.0🌈

First major release since v4 announcements. Here's the highlights of what's included:

New Features:

• Ability to add linked rows for images, segment masks and binary masks
• Ability to save query views through tagging
• Integration with MMDetection and MMSegmentation
• Autocommit the data at the session exit
• Ability to create dynamic arrays
• Ability to create structures with known schema

Improvements and fixes:

• Significantly improved dataset load time for large datasets
• Flushing the data in background during ingestion
• Reduced memory usage during ingestion
• Ability to slice the dataset and column by slices, lists and tuples
• Fixed various bugs in query engine, v3-to-v4 conversion flow and data ingestion flow

v3.9.32 🌈

🧭 What's Changed

• LabelBox integration (#2995) @tyesayan
• fixed optimize for image.rgb and image.gray htypes (#3001) @activesoull
• View schedule fix (#3000) @activesoull
• [DEEP-454] fixed ds.summary with new json implementation (#2999) @activesoull
• Class label test fix (#2998) @activesoull

⚙️ Who Contributes

@activesoull, @artgish, @nvoxland-al, @tyesayan, @zaaram and Tigran Yesayan

v3.9.31 🌈

🧭 What's Changed

• Fixed class_label's inconsistency issue on Unioned dataset (#2996) @activesoull

⚙️ Who Contributes

@activesoull and @nvoxland-al

v3.9.30 🌈

🧭 What's Changed

• Fix decode_ method = data methods behavior in data loader (#2993) @activesoull

⚙️ Who Contributes

@activesoull and @nvoxland-al

v4.0.3

• Fixed issue with non-contiguous numpy array #2988
• Fixed issue with deeplake.copy on azure storage
• Stability improvements on vector search
• Added deeplake.push and deeplake.pull to synchronize dataset copies

v3.9.29 🌈

🧭 What's Changed

• bump libdeeplake version to 0.0.149 (#2989) @activesoull

⚙️ Who Contributes

@activesoull