Merge pull request #237 from fastlabel/fix/236

自動アノテーション実行時のモデル特定のためalgorithm_typeパラメータを追加

Author: ryoKaz

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

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,