Feature/LABIMP 7887

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.6.0
+    rev: v6.0.0
     hooks:
       - id: check-added-large-files
       - id: check-merge-conflict
@@ -11,25 +11,25 @@ repos:
       - id: mixed-line-ending
 
   - repo: https://github.com/psf/black
-    rev: 24.8.0
+    rev: 25.9.0
     hooks:
       - id: black
         args: ["--line-length=88"]
 
   - repo: https://github.com/pycqa/isort
-    rev: 5.13.2
+    rev: 7.0.0
     hooks:
       - id: isort
         args: ["--profile=black", "--line-length=88"]
 
   - repo: https://github.com/pycqa/flake8
-    rev: 7.1.1
+    rev: 7.3.0
     hooks:
       - id: flake8
         additional_dependencies: []
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.11.2
+    rev: v1.18.2
     hooks:
       - id: mypy
         args: ["--config=pyproject.toml"]

labellerr/config.py

@@ -1,4 +1,3 @@
-"""This is to be removed, should be in constants.py
-"""
+"""This is to be removed, should be in constants.py"""
 
 cdn_server_address = "cdn-951134552678.us-central1.run.app:443"

labellerr/core/autolabel/__init__.py

@@ -1,2 +1 @@
-"""Inference core wrappers go here.
-"""
+"""Inference core wrappers go here."""

labellerr/core/datasets/__init__.py

@@ -1,7 +1,5 @@
-"""This module will contain all CRUD for datasets. Example, create, list datasets, get dataset, delete dataset, update dataset, etc.
-"""
-# from labellerr.core.datasets.base import LabellerrDataset
+"""This module will contain all CRUD for datasets. Example, create, list datasets, get dataset, delete dataset, update dataset, etc."""
 
-# __all__ = [
-#     'LabellerrDataset'
-#     ]
+from labellerr.core.datasets.base import LabellerrDataset
+
+__all__ = ["LabellerrDataset"]

labellerr/core/datasets/base.py

@@ -177,4 +177,4 @@ def download(self):
 #     results = dataset.download()
 
 #     # Print summary
-#     pprint.pprint(results)
+#     pprint.pprint(results)

labellerr/core/files/__init__.py

@@ -11,4 +11,4 @@
     'LabellerrImageFile', 
     'LabellerrVideoFile',
     'LabellerrFileMeta'
-]
+]

labellerr/core/files/image_file.py

@@ -1,4 +1,4 @@
 from labellerr.core.files.base import LabellerrFile
 
 class LabellerrImageFile(LabellerrFile):
-    pass
+    pass

labellerr/core/files/video_file.py

@@ -308,4 +308,4 @@ def download_create_video_auto_cleanup(self, output_folder: str = "./Labellerr_d
             raise LabellerrError(f"Failed in video processing: {str(e)}")
 
 
-LabellerrFileMeta.register('video', LabellerrVideoFile)
+LabellerrFileMeta.register('video', LabellerrVideoFile)

labellerr/services/autolabel/__init__.py

@@ -1,2 +1 @@
-"""This module will have API handling for triggering SAM, SAM2 jobs.
-"""
+"""This module will have API handling for triggering SAM, SAM2 jobs."""

labellerr/services/labellerr_files/client_utils.py

@@ -383,23 +383,23 @@ def fetch_files(self, limit: int | None = None, page_size: int = 10):
             raise LabellerrError(f"Failed to fetch dataset files: {str(e)}")
 
 # Example usage
-if __name__ == "__main__":
+# if __name__ == "__main__":
 
-    api_key = "66f4d8.9f402742f58a89568f5bcc0f86"
-    api_secret = "1e2478b930d4a842a526beb585e60d2a9ee6a6f1e3aa89cb3c8ead751f418215"
-    client_id = "14078"
-    dataset_id = "16257fd6-b91b-4d00-a680-9ece9f3f241c"
-    project_id = "gabrila_artificial_duck_74237"
-    file_id = "c44f38f6-0186-436f-8c2d-ffb50a539c76"
+#     api_key = ""
+#     api_secret = ""
+#     client_id = "14078"
+#     dataset_id = "16257fd6-b91b-4d00-a680-9ece9f3f241c"
+#     project_id = "gabrila_artificial_duck_74237"
+#     file_id = "c44f38f6-0186-436f-8c2d-ffb50a539c76"
 
-    client = LabellerrClient(api_key=api_key, api_secret=api_secret, client_id=client_id)
+#     client = LabellerrClient(api_key=api_key, api_secret=api_secret, client_id=client_id)
 
-    lb_file = LabellerrFile(
-        client=client,
-        file_id=file_id,
-        project_id=project_id,
-        dataset_id=dataset_id
-    )
+#     lb_file = LabellerrFile(
+#         client=client,
+#         file_id=file_id,
+#         project_id=project_id,
+#         dataset_id=dataset_id
+#     )
 
 
     # print(f"File type: {type(lb_file).__name__}")
@@ -417,8 +417,8 @@ def fetch_files(self, limit: int | None = None, page_size: int = 10):
         # frames_path = f"./output/{file_id}"
         # lb_file.create_video(frames_folder=frames_path, output_file="final_video.mp4", framerate=30)
 
-    lb_dataset = LabellerrVideoDataset(client=client, dataset_id=dataset_id, project_id=project_id)
-    lb_dataset.fetch_files()
+#     lb_dataset = LabellerrVideoDataset(client=client, dataset_id=dataset_id, project_id=project_id)
+#     lb_dataset.fetch_files()
     # print(f"Fetched {len(video_files)} video files from dataset {dataset_id}")
     # print(video_files)
-
+

labellerr/services/video_sampling/ffmpeg.py

@@ -148,4 +148,4 @@ def _save_json_mapping(self, result: DetectionResult, output_folder: str, file_i
 
     # Get singleton instance
     detector = FFMPEGSceneDetect()
-    result = detector.detect_and_extract(video_path)
+    result = detector.detect_and_extract(video_path)

labellerr/services/video_sampling/gemini.py

@@ -260,4 +260,4 @@ def _save_json_mapping(
 
 
     except Exception as e:
-        print(f"Error: {e}")
+        print(f"Error: {e}")

labellerr/services/video_sampling/pyscene_detect.py

@@ -132,4 +132,4 @@ def _save_json_mapping(self, result: DetectionResult, output_folder: str, file_i
 #     video_path = r"D:\professional\LABELLERR\Task\Repos\SDKPython\labellerr\notebooks\c44f38f6-0186-436f-8c2d-ffb50a539c76.mp4"
 
 #     detector = PySceneDetect()
-#     result = detector.detect_and_extract(video_path)
+#     result = detector.detect_and_extract(video_path)

labellerr/services/video_sampling/requirements.txt

@@ -1,3 +1,3 @@
 scenedetect 
 google-cloud-videointelligence
-scikit-image
+scikit-image

labellerr/services/video_sampling/ssim.py

@@ -222,4 +222,4 @@ def _save_json_mapping(
 
     print(f"\nDetection complete!")
     print(f"Total frames extracted: {len(result.selected_frames)}")
-    print(f"Output folder: {result.output_folder}")
+    print(f"Output folder: {result.output_folder}")