Merge pull request #115 from fastlabel/842-import-pose-estimation-annotation

update pose anno convert COCO to fastlabel

Author: qoone

README.md

@@ -1797,14 +1797,16 @@ dataset
 
 ### COCO
 
-Supported bbox or polygon annotation type.
+Supported bbox , polygon or pose_estimation annotation type.
 
 Convert annotation file of [COCO format](https://cocodataset.org/#format-data) as a Fastlabel format and create task.
 
 file_path: COCO annotation json file path
 
 ```python
-annotations_map = client.convert_coco_to_fastlabel(file_path="./sample.json")
+annotations_map = client.convert_coco_to_fastlabel(file_path="./sample.json", annotation_type="bbox")
+# annotation_type = "bbox", "polygon" or "pose_estimation 
+
 task_id = client.create_image_task(
     project="YOUR_PROJECT_SLUG",
     name="sample.jpg",

fastlabel/__init__.py

@@ -1610,7 +1610,7 @@ def find_integrated_audio_task_by_prefix(
 
     # Convert to Fastlabel
 
-    def convert_coco_to_fastlabel(self, file_path: str) -> dict:
+    def convert_coco_to_fastlabel(self, file_path: str, annotation_type: str) -> dict:
         """
         Convert COCO format to FastLabel format as annotation file.
 
@@ -1647,9 +1647,7 @@ def convert_coco_to_fastlabel(self, file_path: str) -> dict:
             ]
         }
         """
-        with open(file_path, "r") as f:
-            file = f.read()
-            return converters.execute_coco_to_fastlabel(eval(file))
+        return converters.execute_coco_to_fastlabel(json.load(open(file_path)), annotation_type)
 
     def convert_labelme_to_fastlabel(self, folder_path: str) -> dict:
         """

fastlabel/converters.py

@@ -1,4 +1,5 @@
 from concurrent.futures import ThreadPoolExecutor
+from curses import keyname
 from datetime import datetime
 from decimal import Decimal
 from typing import List
@@ -10,6 +11,8 @@
 from fastlabel.const import AnnotationType
 import os
 
+from fastlabel.exceptions import FastLabelInvalidException
+
 # COCO
 
 
@@ -656,14 +659,16 @@ def __get_pixel_coordinates(points: List[int or float]) -> List[int]:
     return new_points
 
 
-def execute_coco_to_fastlabel(coco: dict) -> dict:
+def execute_coco_to_fastlabel(coco: dict ,annotation_type:str) -> dict:
     coco_images = {}
     for c in coco["images"]:
         coco_images[c["id"]] = c["file_name"]
 
     coco_categories = {}
+    coco_categories_keypoints={}
     for c in coco["categories"]:
         coco_categories[c["id"]] = c["name"]
+        coco_categories_keypoints[c["id"]] = c["keypoints"]
 
     coco_annotations = coco["annotations"]
 
@@ -682,19 +687,51 @@ def execute_coco_to_fastlabel(coco: dict) -> dict:
             if not category_name:
                 return
 
-            segmentation = target_coco_annotation["segmentation"][0]
-            annotation_type = ""
-            if len(segmentation) == 4:
-                annotation_type = AnnotationType.bbox.value
-            if len(segmentation) > 4:
-                annotation_type = AnnotationType.polygon.value
-            annotations.append(
-                {
-                    "value": category_name,
-                    "points": segmentation,
-                    "type": annotation_type,
-                }
-            )
+            if annotation_type in [AnnotationType.bbox.value, AnnotationType.polygon.value]:
+                segmentation = target_coco_annotation["segmentation"][0]
+                annotation_type = ""
+                if len(segmentation) == 4:
+                    annotation_type = AnnotationType.bbox.value
+                if len(segmentation) > 4:
+                    annotation_type = AnnotationType.polygon.value
+                annotations.append(
+                    {
+                        "value": category_name,
+                        "points": segmentation,
+                        "type": annotation_type,
+                    }
+                )
+            elif annotation_type == AnnotationType.pose_estimation.value:
+                keypoints = []
+                target_coco_annotation_keypoints = target_coco_annotation["keypoints"]
+                keypoint_keys = coco_categories_keypoints[target_coco_annotation["category_id"]]
+                # coco keypoint style [100,200,1,300,400,1,500,600,2] convert to [[100,200,1],[300,400,1],[500,600,2]]
+                keypoint_values = [target_coco_annotation_keypoints[i:i + 3] for i in range(0, len(target_coco_annotation_keypoints), 3)]
+                for index, keypoint_key in enumerate(keypoint_keys):
+                    keypoint_value = keypoint_values[index]
+                    if keypoint_value[2] == 0:
+                        continue
+                    if not keypoint_value[2] in [1, 2]: 
+                        raise FastLabelInvalidException(f"Visibility flag must be 0 or 1, 2 . annotation_id: {target_coco_annotation['id']}", 422)
+                    # fastlabel occulusion is 0 or 1 . coco occulusion is 1 or 2. 
+                    keypoint_value[2] = keypoint_value[2] - 1
+                    keypoints.append({
+                        "key": keypoint_key,
+                        "value": keypoint_value
+                    })
+
+                annotations.append(
+                    {
+                        "value": category_name,
+                        "type": annotation_type,
+                        "keypoints": keypoints
+                    }
+                )
+            else:
+                raise FastLabelInvalidException(
+                "Annotation type must be bbox or polygon ,pose_estimation.", 422
+                )
+
         results[coco_images[coco_image_key]] = annotations
     return results