changelog updated version bump from `0.20.0rc2` to `0.20.0`
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### 0.20.0 <small>April 24, 2024</small>
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- Added [#1128](https://github.com/roboflow/supervision/pull/1128): [`sv.KeyPoints`](/0.20.0/keypoint/core/#supervision.keypoint.core.KeyPoints) to provide initial support for pose estimation and broader keypoint detection models.
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- Added [#1128](https://github.com/roboflow/supervision/pull/1128): [`sv.EdgeAnnotator`](/0.20.0/keypoint/annotators/#supervision.keypoint.annotators.EdgeAnnotator) and [`sv.VertexAnnotator`](/0.20.0/keypoint/annotators/#supervision.keypoint.annotators.VertexAnnotator) to enable rendering of results from keypoint detection models.
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```python
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import cv2
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import supervision as sv
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from ultralytics import YOLO
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image = cv2.imread(<SOURCE_IMAGE_PATH>)
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model = YOLO('yolov8l-pose')
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result = model(image, verbose=False)[0]
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keypoints = sv.KeyPoints.from_ultralytics(result)
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edge_annotators = sv.EdgeAnnotator(color=sv.Color.GREEN, thickness=5)
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annotated_image = edge_annotators.annotate(image.copy(), keypoints)
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```
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- Changed [#1037](https://github.com/roboflow/supervision/pull/1037): [`sv.LabelAnnotator`](/0.20.0/annotators/#supervision.annotators.core.LabelAnnotator) by adding an additional `corner_radius` argument that allows for rounding the corners of the bounding box.
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- Changed [#1109](https://github.com/roboflow/supervision/pull/1109): [`sv.PolygonZone`](/0.20.0/detection/tools/polygon_zone/#supervision.detection.tools.polygon_zone.PolygonZone) such that the `frame_resolution_wh` argument is no longer required to initialize `sv.PolygonZone`.
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!!! failure "Deprecated"
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The `frame_resolution_wh` parameter in `sv.PolygonZone` is deprecated and will be removed in `supervision-0.24.0`.
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- Changed [#1084](https://github.com/roboflow/supervision/pull/1084): [`sv.get_polygon_center`](/0.20.0/utils/geometry/#supervision.geometry.core.utils.get_polygon_center) to calculate a more accurate polygon centroid.
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- Changed [#1069](https://github.com/roboflow/supervision/pull/1069): [`sv.Detections.from_transformers`](/0.20.0/detection/core/#supervision.detection.core.Detections.from_transformers) by adding support for Transformers segmentation models and extract class names values.
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```python
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import torch
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import supervision as sv
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from PIL import Image
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from transformers import DetrImageProcessor, DetrForSegmentation
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processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50-panoptic")
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model = DetrForSegmentation.from_pretrained("facebook/detr-resnet-50-panoptic")
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image = Image.open(<SOURCE_IMAGE_PATH>)
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inputs = processor(images=image, return_tensors="pt")
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with torch.no_grad():
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outputs = model(**inputs)
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width, height = image.size
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target_size = torch.tensor([[height, width]])
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results = processor.post_process_segmentation(
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outputs=outputs, target_sizes=target_size)[0]
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detections = sv.Detections.from_transformers(results, id2label=model.config.id2label)
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mask_annotator = sv.MaskAnnotator()
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label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
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annotated_image = mask_annotator.annotate(
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scene=image, detections=detections)
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annotated_image = label_annotator.annotate(
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scene=annotated_image, detections=detections)
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```
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- Fixed [#787](https://github.com/roboflow/supervision/pull/787): [`sv.ByteTrack.update_with_detections`](/0.20.0/trackers/#supervision.tracker.byte_tracker.core.ByteTrack.update_with_detections) which was removing segmentation masks while tracking. Now, `ByteTrack` can be used alongside segmentation models.
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### 0.19.0 <small>March 15, 2024</small>
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- Added [#818](https://github.com/roboflow/supervision/pull/818): [`sv.CSVSink`](/0.19.0/detection/tools/save_detections/#supervision.detection.tools.csv_sink.CSVSink) allowing for the straightforward saving of image, video, or stream inference results in a `.csv` file.
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@ -16,3 +16,4 @@ These features are phased out due to better alternatives or potential issues in
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- The method [`FPSMonitor.__call__`](utils/video.md/#supervision.utils.video.FPSMonitor.__call__) is deprecated and will be removed in `supervision-0.22.0`. Use the attribute [`FPSMonitor.fps`](utils/video.md/#supervision.utils.video.FPSMonitor.fps) instead.
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- The `track_buffer`, `track_thresh`, and `match_thresh` parameters in [`ByterTrack`](trackers.md/#supervision.tracker.byte_tracker.core.ByteTrack) are deprecated and will be removed in `supervision-0.23.0`. Use `lost_track_buffer,` `track_activation_threshold`, and `minimum_matching_threshold` instead.
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- The `triggering_position ` parameter in [`sv.PolygonZone`](detection/tools/polygon_zone.md/#supervision.detection.tools.polygon_zone.PolygonZone) is deprecated and will be removed in `supervision-0.23.0`. Use `triggering_anchors ` instead.
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- The `frame_resolution_wh ` parameter in [`sv.PolygonZone`](detection/tools/polygon_zone.md/#supervision.detection.tools.polygon_zone.PolygonZone) is deprecated and will be removed in `supervision-0.24.0`.
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comments: true
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---
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<div class="md-typeset">
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<h2><a href="#supervision.geometry.core.utils.get_polygon_center">get_polygon_center</a></h2>
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</div>
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:::supervision.geometry.utils.get_polygon_center
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<div class="md-typeset">
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<h2><a href="#supervision.geometry.core.Position">Position</a></h2>
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</div>
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@ -1,6 +1,6 @@
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[tool.poetry]
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name = "supervision"
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version = "0.20.0rc2"
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version = "0.20.0"
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description = "A set of easy-to-use utils that will come in handy in any Computer Vision project"
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authors = ["Piotr Skalski <piotr.skalski92@gmail.com>"]
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maintainers = ["Piotr Skalski <piotr.skalski92@gmail.com>"]
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@ -9,10 +9,6 @@ from supervision.utils.conversion import convert_for_annotation_method
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from supervision.utils.internal import deprecated
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@deprecated(
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"`BoxAnnotator` is deprecated and will be removed in "
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"`supervision-0.22.0`. Use `BoundingBoxAnnotator` and `LabelAnnotator` instead"
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)
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class BoxAnnotator:
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"""
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A class for drawing bounding boxes on an image using detections provided.
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@ -46,6 +42,10 @@ class BoxAnnotator:
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self.text_thickness: int = text_thickness
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self.text_padding: int = text_padding
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@deprecated(
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"`BoxAnnotator` is deprecated and will be removed in "
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"`supervision-0.22.0`. Use `BoundingBoxAnnotator` and `LabelAnnotator` instead"
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)
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@convert_for_annotation_method
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def annotate(
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self,
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@ -5,12 +5,7 @@ from supervision.geometry.core import Point
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def get_polygon_center(polygon: np.ndarray) -> Point:
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"""
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Calculate the center of a polygon.
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This function takes in a polygon as a 2-dimensional numpy ndarray and
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returns the center of the polygon as a Point object.
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The center is calculated as the center
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Calculate the center of a polygon. The center is calculated as the center
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of the solid figure formed by the points of the polygon
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Parameters:
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@ -23,12 +18,12 @@ def get_polygon_center(polygon: np.ndarray) -> Point:
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Examples:
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```python
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from supervision.geometry.utils import get_polygon_center
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import numpy as np
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import supervision as sv
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vertices = np.array([[0, 0], [0, 2], [2, 2], [2, 0]])
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get_polygon_center(vertices)
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Point(x=1, y=1)
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polygon = np.array([[0, 0], [0, 2], [2, 2], [2, 0]])
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sv.get_polygon_center(polygon=polygon)
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# Point(x=1, y=1)
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```
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"""
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