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Releases: roboflow/roboflow-python

v1.1.2

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@SolomonLake SolomonLake released this 20 Jul 16:07
bbf5fa5

Fixed logging for the version deploy method.

v1.1.1

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@Jacobsolawetz Jacobsolawetz released this 11 Jul 21:33
781c553

In this release we add API support for search.

v1.1.0

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@Jacobsolawetz Jacobsolawetz released this 21 Jun 16:50
35f38a4

In this release we add a feature to upload VOC and YOLO formatted datasets to Roboflow

@SkalskiP will be excited about the supervisioninclusion` which made the YOLO uploads possible.

You can turn up the parallelism to speed up dataset upload speed, but there must be some limit to that.

v1.0.9

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@paulguerrie paulguerrie released this 17 May 15:29
8694dfe

Adding local param functionality to instance segmentation Versions.

v1.0.8

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@hansent hansent released this 03 May 20:10
605fd45

add prediction parameter to annotation upload
Adds a new optional is_prediction parameter to the upload functions on projects.
passing is_prediction=True to the upload function when uploading images with annotations allows you to indicate that the annotation data you are adding is a prediction (e.g. from another model or other active learning workflow).

If the annotation is added as a prediction the image will stay in the batch or annotation job it already is in, rather than being added to the dataset for training as part of uploading the annotation data.

bug fixes
minor bug fix for properly using the OBJECT_DETECTION_URL env variable to override inference endpoint to use for object-detection models

v1.0.7

v1.0.7 Pre-release
Pre-release

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@hansent hansent released this 03 May 20:00
1da9a6b

minor bug fix for properly using the OBJECT_DETECTION_URL env variable to override inference endpoint to use for object-detection models

add prediction parameter to annotation upload

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@hansent hansent released this 19 Apr 00:56
02b717f

Adds a new optional is_prediction parameter to the upload functions on projects.

passing is_prediction=True to the upload function when uploading images with annotations allows you to indicate that the annotation data you are adding is a prediction (e.g. from another model or other active learning workflow).

If the annotation is added as a prediction the image will stay in the batch or annotation job it already is in, rather than being added to the dataset for training as part of uploading the annotation data.

v1.0.5

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@tonylampada tonylampada released this 14 Apr 18:45
1c37df3

This moves and renames a single method.

Version.get_pt_weights is replaced by model.download(), which makes more sense: download a model's weights is an operation that should belong to the model (version already has a download() method to download images)

V1.0.4

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@tonylampada tonylampada released this 14 Apr 14:31
8c997ab

Adds the ability to download model weights via Version.get_pt_weights()

Fix Windows Config

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@Jacobsolawetz Jacobsolawetz released this 07 Apr 16:09
071bf45

In this release we support windows with new login saved configuration files.

Cheers!