From d51ac8035c5697fc724ce5c0979eca5105c7d73f Mon Sep 17 00:00:00 2001 From: kmkkiii Date: Wed, 11 Dec 2024 16:36:58 +0900 Subject: [PATCH] =?UTF-8?q?=E3=83=A2=E3=83=87=E3=83=AB=E7=89=B9=E5=AE=9A?= =?UTF-8?q?=E3=81=AE=E3=81=9F=E3=82=81=E3=81=AEalgorithm=5Ftype=E3=83=91?= =?UTF-8?q?=E3=83=A9=E3=83=A1=E3=83=BC=E3=82=BF=E8=BF=BD=E5=8A=A0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 3 +++ fastlabel/__init__.py | 3 +++ 2 files changed, 6 insertions(+) diff --git a/README.md b/README.md index 1d691d3..c35895e 100644 --- a/README.md +++ b/README.md @@ -2203,6 +2203,7 @@ The folder structure inside the ZIP file is as follows ``` ### Export Camera Calibration and Image + ```python appendix_data = client.get_appendix_data( project="YOUR_PROJECT_SLUG" @@ -2217,6 +2218,7 @@ appendix_data = client.get_appendix_data( ``` Result data + ``` [{ id: uuid @@ -3496,6 +3498,7 @@ auto_annotation_job = client.execute_auto_annotation_job( // Other built-in models require annotation class mapping. // See: https://fastlabel.notion.site/cf3f006766d742d5ae25ca4200fa19b4 // If you want to use the custom model, please fill out model name. + algorithm_type: "object_detection", // optional, "object_detection", "ocr" or "image_classification" update_existing: False, // optional, default: False confidence_threshold: 0.4, // optional, default: 0.4 use_tta: False, // optional, default: False diff --git a/fastlabel/__init__.py b/fastlabel/__init__.py index 8fa40b5..b1cbf82 100644 --- a/fastlabel/__init__.py +++ b/fastlabel/__init__.py @@ -4731,6 +4731,7 @@ def execute_auto_annotation_job( self, project: str, model_name: str, + algorithm_type: str = None, update_existing: bool = False, confidence_threshold: float = 0.4, use_tta: bool = False, @@ -4743,6 +4744,7 @@ def execute_auto_annotation_job( project is slug of your project (Required). model_name is name of the model (Required). You can choose Japanese or English name. + algorithm_type is used to identify the model. algorithm_type can be 'object_detection' or 'ocr' or 'image_classification'(Optional). update_existing is whether to update existing annotations (Optional). confidence_threshold is a threshold of confidence (Optional). use_tta is whether to use test time augmentation (Optional). @@ -4754,6 +4756,7 @@ def execute_auto_annotation_job( payload = { "project": project, "modelName": model_name, + "algorithmType": algorithm_type, "updateExisting": update_existing, "confidenceThreshold": confidence_threshold, "useTTA": use_tta,