bump version from 0.21.0rc1 to 0.21.0rc2

pin inference version in examples

examples/count_people_in_zone/inference_example.py

@@ -38,15 +38,15 @@ def initiate_annotators(
 ) -> Tuple[
     List[sv.PolygonZone], List[sv.PolygonZoneAnnotator], List[sv.BoundingBoxAnnotator]
 ]:
-    line_thickness = sv.calculate_dynamic_line_thickness(resolution_wh=resolution_wh)
-    text_scale = sv.calculate_dynamic_text_scale(resolution_wh=resolution_wh)
+    line_thickness = sv.calculate_optimal_line_thickness(resolution_wh=resolution_wh)
+    text_scale = sv.calculate_optimal_text_scale(resolution_wh=resolution_wh)
 
     zones = []
     zone_annotators = []
     box_annotators = []
 
     for index, polygon in enumerate(polygons):
-        zone = sv.PolygonZone(polygon=polygon, frame_resolution_wh=resolution_wh)
+        zone = sv.PolygonZone(polygon=polygon)
         zone_annotator = sv.PolygonZoneAnnotator(
             zone=zone,
             color=COLORS.by_idx(index),

examples/count_people_in_zone/requirements.txt

@@ -1,5 +1,5 @@
 gdown
 inference
-supervision==0.19.0
+supervision>=0.20.0
 tqdm
 ultralytics

examples/count_people_in_zone/ultralytics_example.py

@@ -36,15 +36,15 @@ def initiate_annotators(
 ) -> Tuple[
     List[sv.PolygonZone], List[sv.PolygonZoneAnnotator], List[sv.BoundingBoxAnnotator]
 ]:
-    line_thickness = sv.calculate_dynamic_line_thickness(resolution_wh=resolution_wh)
-    text_scale = sv.calculate_dynamic_text_scale(resolution_wh=resolution_wh)
+    line_thickness = sv.calculate_optimal_line_thickness(resolution_wh=resolution_wh)
+    text_scale = sv.calculate_optimal_text_scale(resolution_wh=resolution_wh)
 
     zones = []
     zone_annotators = []
     box_annotators = []
 
     for index, polygon in enumerate(polygons):
-        zone = sv.PolygonZone(polygon=polygon, frame_resolution_wh=resolution_wh)
+        zone = sv.PolygonZone(polygon=polygon)
         zone_annotator = sv.PolygonZoneAnnotator(
             zone=zone,
             color=COLORS.by_idx(index),

examples/speed_estimation/inference_example.py

@@ -98,10 +98,10 @@ if __name__ == "__main__":
         frame_rate=video_info.fps, track_thresh=args.confidence_threshold
     )
 
-    thickness = sv.calculate_dynamic_line_thickness(
+    thickness = sv.calculate_optimal_line_thickness(
         resolution_wh=video_info.resolution_wh
     )
-    text_scale = sv.calculate_dynamic_text_scale(resolution_wh=video_info.resolution_wh)
+    text_scale = sv.calculate_optimal_text_scale(resolution_wh=video_info.resolution_wh)
     bounding_box_annotator = sv.BoundingBoxAnnotator(thickness=thickness)
     label_annotator = sv.LabelAnnotator(
         text_scale=text_scale,
@@ -116,9 +116,7 @@ if __name__ == "__main__":
 
     frame_generator = sv.get_video_frames_generator(source_path=args.source_video_path)
 
-    polygon_zone = sv.PolygonZone(
-        polygon=SOURCE, frame_resolution_wh=video_info.resolution_wh
-    )
+    polygon_zone = sv.PolygonZone(polygon=SOURCE)
     view_transformer = ViewTransformer(source=SOURCE, target=TARGET)
 
     coordinates = defaultdict(lambda: deque(maxlen=video_info.fps))

examples/speed_estimation/requirements.txt

@@ -1,6 +1,6 @@
-supervision==0.19.0
+supervision>=0.20.0
 tqdm==4.66.1
 requests
 ultralytics==8.0.237
 super-gradients==3.5.0
-inference==0.9.8
+inference<=0.9.21

examples/speed_estimation/ultralytics_example.py

@@ -76,10 +76,10 @@ if __name__ == "__main__":
         frame_rate=video_info.fps, track_thresh=args.confidence_threshold
     )
 
-    thickness = sv.calculate_dynamic_line_thickness(
+    thickness = sv.calculate_optimal_line_thickness(
         resolution_wh=video_info.resolution_wh
     )
-    text_scale = sv.calculate_dynamic_text_scale(resolution_wh=video_info.resolution_wh)
+    text_scale = sv.calculate_optimal_text_scale(resolution_wh=video_info.resolution_wh)
     bounding_box_annotator = sv.BoundingBoxAnnotator(thickness=thickness)
     label_annotator = sv.LabelAnnotator(
         text_scale=text_scale,
@@ -94,9 +94,7 @@ if __name__ == "__main__":
 
     frame_generator = sv.get_video_frames_generator(source_path=args.source_video_path)
 
-    polygon_zone = sv.PolygonZone(
-        polygon=SOURCE, frame_resolution_wh=video_info.resolution_wh
-    )
+    polygon_zone = sv.PolygonZone(polygon=SOURCE)
     view_transformer = ViewTransformer(source=SOURCE, target=TARGET)
 
     coordinates = defaultdict(lambda: deque(maxlen=video_info.fps))

examples/speed_estimation/yolo_nas_example.py

@@ -77,10 +77,10 @@ if __name__ == "__main__":
         frame_rate=video_info.fps, track_thresh=args.confidence_threshold
     )
 
-    thickness = sv.calculate_dynamic_line_thickness(
+    thickness = sv.calculate_optimal_line_thickness(
         resolution_wh=video_info.resolution_wh
     )
-    text_scale = sv.calculate_dynamic_text_scale(resolution_wh=video_info.resolution_wh)
+    text_scale = sv.calculate_optimal_text_scale(resolution_wh=video_info.resolution_wh)
     bounding_box_annotator = sv.BoundingBoxAnnotator(thickness=thickness)
     label_annotator = sv.LabelAnnotator(
         text_scale=text_scale,
@@ -95,9 +95,7 @@ if __name__ == "__main__":
 
     frame_generator = sv.get_video_frames_generator(source_path=args.source_video_path)
 
-    polygon_zone = sv.PolygonZone(
-        polygon=SOURCE, frame_resolution_wh=video_info.resolution_wh
-    )
+    polygon_zone = sv.PolygonZone(polygon=SOURCE)
     view_transformer = ViewTransformer(source=SOURCE, target=TARGET)
 
     coordinates = defaultdict(lambda: deque(maxlen=video_info.fps))

examples/time_in_zone/inference_file_example.py

@@ -29,14 +29,10 @@ def main(
     video_info = sv.VideoInfo.from_video_path(video_path=source_video_path)
     frames_generator = sv.get_video_frames_generator(source_video_path)
 
-    frame = next(frames_generator)
-    resolution_wh = frame.shape[1], frame.shape[0]
-
     polygons = load_zones_config(file_path=zone_configuration_path)
     zones = [
         sv.PolygonZone(
             polygon=polygon,
-            frame_resolution_wh=resolution_wh,
             triggering_anchors=(sv.Position.CENTER,),
         )
         for polygon in polygons

examples/time_in_zone/inference_naive_stream_example.py

@@ -29,14 +29,10 @@ def main(
     frames_generator = get_stream_frames_generator(rtsp_url=rtsp_url)
     fps_monitor = sv.FPSMonitor()
 
-    frame = next(frames_generator)
-    resolution_wh = frame.shape[1], frame.shape[0]
-
     polygons = load_zones_config(file_path=zone_configuration_path)
     zones = [
         sv.PolygonZone(
             polygon=polygon,
-            frame_resolution_wh=resolution_wh,
             triggering_anchors=(sv.Position.CENTER,),
         )
         for polygon in polygons

examples/time_in_zone/inference_stream_example.py

@@ -24,20 +24,15 @@ class CustomSink:
         self.fps_monitor = sv.FPSMonitor()
         self.polygons = load_zones_config(file_path=zone_configuration_path)
         self.timers = [ClockBasedTimer() for _ in self.polygons]
-        self.zones = None
+        self.zones = [
+            sv.PolygonZone(
+                polygon=polygon,
+                triggering_anchors=(sv.Position.CENTER,),
+            )
+            for polygon in self.polygons
+        ]
 
     def on_prediction(self, result: dict, frame: VideoFrame) -> None:
-        if self.zones is None:
-            resolution_wh = frame.image.shape[1], frame.image.shape[0]
-            self.zones = [
-                sv.PolygonZone(
-                    polygon=polygon,
-                    frame_resolution_wh=resolution_wh,
-                    triggering_anchors=(sv.Position.CENTER,),
-                )
-                for polygon in self.polygons
-            ]
-
         self.fps_monitor.tick()
         fps = self.fps_monitor.fps
 

examples/time_in_zone/requirements.txt

@@ -1,5 +1,5 @@
 opencv-python
-supervision
+supervision>=0.20.0
 ultralytics
-inference
+inference<=0.9.21
 pytube

examples/time_in_zone/ultralytics_file_example.py

@@ -30,14 +30,10 @@ def main(
     video_info = sv.VideoInfo.from_video_path(video_path=source_video_path)
     frames_generator = sv.get_video_frames_generator(source_video_path)
 
-    frame = next(frames_generator)
-    resolution_wh = frame.shape[1], frame.shape[0]
-
     polygons = load_zones_config(file_path=zone_configuration_path)
     zones = [
         sv.PolygonZone(
             polygon=polygon,
-            frame_resolution_wh=resolution_wh,
             triggering_anchors=(sv.Position.CENTER,),
         )
         for polygon in polygons

examples/time_in_zone/ultralytics_naive_stream_example.py

@@ -30,14 +30,10 @@ def main(
     frames_generator = get_stream_frames_generator(rtsp_url=rtsp_url)
     fps_monitor = sv.FPSMonitor()
 
-    frame = next(frames_generator)
-    resolution_wh = frame.shape[1], frame.shape[0]
-
     polygons = load_zones_config(file_path=zone_configuration_path)
     zones = [
         sv.PolygonZone(
             polygon=polygon,
-            frame_resolution_wh=resolution_wh,
             triggering_anchors=(sv.Position.CENTER,),
         )
         for polygon in polygons

examples/time_in_zone/ultralytics_stream_example.py

@@ -25,20 +25,15 @@ class CustomSink:
         self.fps_monitor = sv.FPSMonitor()
         self.polygons = load_zones_config(file_path=zone_configuration_path)
         self.timers = [ClockBasedTimer() for _ in self.polygons]
-        self.zones = None
+        self.zones = [
+            sv.PolygonZone(
+                polygon=polygon,
+                triggering_anchors=(sv.Position.CENTER,),
+            )
+            for polygon in self.polygons
+        ]
 
     def on_prediction(self, detections: sv.Detections, frame: VideoFrame) -> None:
-        if self.zones is None:
-            resolution_wh = frame.image.shape[1], frame.image.shape[0]
-            self.zones = [
-                sv.PolygonZone(
-                    polygon=polygon,
-                    frame_resolution_wh=resolution_wh,
-                    triggering_anchors=(sv.Position.CENTER,),
-                )
-                for polygon in self.polygons
-            ]
-
         self.fps_monitor.tick()
         fps = self.fps_monitor.fps
 

examples/traffic_analysis/inference_example.py

@@ -1,6 +1,6 @@
 import argparse
 import os
-from typing import Dict, Iterable, List, Set, Tuple
+from typing import Dict, Iterable, List, Set
 
 import cv2
 import numpy as np
@@ -60,13 +60,11 @@ class DetectionsManager:
 
 def initiate_polygon_zones(
     polygons: List[np.ndarray],
-    frame_resolution_wh: Tuple[int, int],
     triggering_anchors: Iterable[sv.Position] = [sv.Position.CENTER],
 ) -> List[sv.PolygonZone]:
     return [
         sv.PolygonZone(
             polygon=polygon,
-            frame_resolution_wh=frame_resolution_wh,
             triggering_anchors=triggering_anchors,
         )
         for polygon in polygons
@@ -92,12 +90,8 @@ class VideoProcessor:
         self.tracker = sv.ByteTrack()
 
         self.video_info = sv.VideoInfo.from_video_path(source_video_path)
-        self.zones_in = initiate_polygon_zones(
-            ZONE_IN_POLYGONS, self.video_info.resolution_wh, [sv.Position.CENTER]
-        )
-        self.zones_out = initiate_polygon_zones(
-            ZONE_OUT_POLYGONS, self.video_info.resolution_wh, [sv.Position.CENTER]
-        )
+        self.zones_in = initiate_polygon_zones(ZONE_IN_POLYGONS, [sv.Position.CENTER])
+        self.zones_out = initiate_polygon_zones(ZONE_OUT_POLYGONS, [sv.Position.CENTER])
 
         self.bounding_box_annotator = sv.BoundingBoxAnnotator(color=COLORS)
         self.label_annotator = sv.LabelAnnotator(

examples/traffic_analysis/requirements.txt

@@ -1,5 +1,5 @@
 gdown
-inference
-supervision>=0.19.0
+inference<=0.9.21
+supervision>=0.20.0
 tqdm
 ultralytics

examples/traffic_analysis/ultralytics_example.py

@@ -1,5 +1,5 @@
 import argparse
-from typing import Dict, Iterable, List, Set, Tuple
+from typing import Dict, Iterable, List, Set
 
 import cv2
 import numpy as np
@@ -58,13 +58,11 @@ class DetectionsManager:
 
 def initiate_polygon_zones(
     polygons: List[np.ndarray],
-    frame_resolution_wh: Tuple[int, int],
     triggering_anchors: Iterable[sv.Position] = [sv.Position.CENTER],
 ) -> List[sv.PolygonZone]:
     return [
         sv.PolygonZone(
             polygon=polygon,
-            frame_resolution_wh=frame_resolution_wh,
             triggering_anchors=triggering_anchors,
         )
         for polygon in polygons
@@ -89,12 +87,8 @@ class VideoProcessor:
         self.tracker = sv.ByteTrack()
 
         self.video_info = sv.VideoInfo.from_video_path(source_video_path)
-        self.zones_in = initiate_polygon_zones(
-            ZONE_IN_POLYGONS, self.video_info.resolution_wh, [sv.Position.CENTER]
-        )
-        self.zones_out = initiate_polygon_zones(
-            ZONE_OUT_POLYGONS, self.video_info.resolution_wh, [sv.Position.CENTER]
-        )
+        self.zones_in = initiate_polygon_zones(ZONE_IN_POLYGONS, [sv.Position.CENTER])
+        self.zones_out = initiate_polygon_zones(ZONE_OUT_POLYGONS, [sv.Position.CENTER])
 
         self.bounding_box_annotator = sv.BoundingBoxAnnotator(color=COLORS)
         self.label_annotator = sv.LabelAnnotator(

poetry.lock

@@ -2083,34 +2083,34 @@ files = [
 
 [[package]]
 name = "mkdocs"
-version = "1.5.3"
+version = "1.6.0"
 description = "Project documentation with Markdown."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "mkdocs-1.5.3-py3-none-any.whl", hash = "sha256:3b3a78e736b31158d64dbb2f8ba29bd46a379d0c6e324c2246c3bc3d2189cfc1"},
-    {file = "mkdocs-1.5.3.tar.gz", hash = "sha256:eb7c99214dcb945313ba30426c2451b735992c73c2e10838f76d09e39ff4d0e2"},
+    {file = "mkdocs-1.6.0-py3-none-any.whl", hash = "sha256:1eb5cb7676b7d89323e62b56235010216319217d4af5ddc543a91beb8d125ea7"},
+    {file = "mkdocs-1.6.0.tar.gz", hash = "sha256:a73f735824ef83a4f3bcb7a231dcab23f5a838f88b7efc54a0eef5fbdbc3c512"},
 ]
 
 [package.dependencies]
 click = ">=7.0"
 colorama = {version = ">=0.4", markers = "platform_system == \"Windows\""}
 ghp-import = ">=1.0"
-importlib-metadata = {version = ">=4.3", markers = "python_version < \"3.10\""}
+importlib-metadata = {version = ">=4.4", markers = "python_version < \"3.10\""}
 jinja2 = ">=2.11.1"
-markdown = ">=3.2.1"
+markdown = ">=3.3.6"
 markupsafe = ">=2.0.1"
 mergedeep = ">=1.3.4"
+mkdocs-get-deps = ">=0.2.0"
 packaging = ">=20.5"
 pathspec = ">=0.11.1"
-platformdirs = ">=2.2.0"
 pyyaml = ">=5.1"
 pyyaml-env-tag = ">=0.1"
 watchdog = ">=2.0"
 
 [package.extras]
 i18n = ["babel (>=2.9.0)"]
-min-versions = ["babel (==2.9.0)", "click (==7.0)", "colorama (==0.4)", "ghp-import (==1.0)", "importlib-metadata (==4.3)", "jinja2 (==2.11.1)", "markdown (==3.2.1)", "markupsafe (==2.0.1)", "mergedeep (==1.3.4)", "packaging (==20.5)", "pathspec (==0.11.1)", "platformdirs (==2.2.0)", "pyyaml (==5.1)", "pyyaml-env-tag (==0.1)", "typing-extensions (==3.10)", "watchdog (==2.0)"]
+min-versions = ["babel (==2.9.0)", "click (==7.0)", "colorama (==0.4)", "ghp-import (==1.0)", "importlib-metadata (==4.4)", "jinja2 (==2.11.1)", "markdown (==3.3.6)", "markupsafe (==2.0.1)", "mergedeep (==1.3.4)", "mkdocs-get-deps (==0.2.0)", "packaging (==20.5)", "pathspec (==0.11.1)", "pyyaml (==5.1)", "pyyaml-env-tag (==0.1)", "watchdog (==2.0)"]
 
 [[package]]
 name = "mkdocs-autorefs"
@@ -2127,6 +2127,23 @@ files = [
 Markdown = ">=3.3"
 mkdocs = ">=1.1"
 
+[[package]]
+name = "mkdocs-get-deps"
+version = "0.2.0"
+description = "MkDocs extension that lists all dependencies according to a mkdocs.yml file"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "mkdocs_get_deps-0.2.0-py3-none-any.whl", hash = "sha256:2bf11d0b133e77a0dd036abeeb06dec8775e46efa526dc70667d8863eefc6134"},
+    {file = "mkdocs_get_deps-0.2.0.tar.gz", hash = "sha256:162b3d129c7fad9b19abfdcb9c1458a651628e4b1dea628ac68790fb3061c60c"},
+]
+
+[package.dependencies]
+importlib-metadata = {version = ">=4.3", markers = "python_version < \"3.10\""}
+mergedeep = ">=1.3.4"
+platformdirs = ">=2.2.0"
+pyyaml = ">=5.1"
+
 [[package]]
 name = "mkdocs-git-committers-plugin-2"
 version = "2.3.0"
@@ -2180,13 +2197,13 @@ pygments = ">2.12.0"
 
 [[package]]
 name = "mkdocs-material"
-version = "9.5.18"
+version = "9.5.19"
 description = "Documentation that simply works"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mkdocs_material-9.5.18-py3-none-any.whl", hash = "sha256:1e0e27fc9fe239f9064318acf548771a4629d5fd5dfd45444fd80a953fe21eb4"},
-    {file = "mkdocs_material-9.5.18.tar.gz", hash = "sha256:a43f470947053fa2405c33995f282d24992c752a50114f23f30da9d8d0c57e62"},
+    {file = "mkdocs_material-9.5.19-py3-none-any.whl", hash = "sha256:ea96e150b6c95f5e4ffe47d78bb712c7bacdd91d2a0bec47f46b6fa0705a86ec"},
+    {file = "mkdocs_material-9.5.19.tar.gz", hash = "sha256:7473e06e17e23af608a30ef583fdde8f36389dd3ef56b1d503eed54c89c9618c"},
 ]
 
 [package.dependencies]
@@ -2195,7 +2212,7 @@ cairosvg = {version = ">=2.6,<3.0", optional = true, markers = "extra == \"imagi
 colorama = ">=0.4,<1.0"
 jinja2 = ">=3.0,<4.0"
 markdown = ">=3.2,<4.0"
-mkdocs = ">=1.5.3,<1.6.0"
+mkdocs = ">=1.6,<2.0"
 mkdocs-material-extensions = ">=1.3,<2.0"
 paginate = ">=0.5,<1.0"
 pillow = {version = ">=10.2,<11.0", optional = true, markers = "extra == \"imaging\""}
@@ -2222,13 +2239,13 @@ files = [
 
 [[package]]
 name = "mkdocstrings"
-version = "0.24.3"
+version = "0.25.0"
 description = "Automatic documentation from sources, for MkDocs."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mkdocstrings-0.24.3-py3-none-any.whl", hash = "sha256:5c9cf2a32958cd161d5428699b79c8b0988856b0d4a8c5baf8395fc1bf4087c3"},
-    {file = "mkdocstrings-0.24.3.tar.gz", hash = "sha256:f327b234eb8d2551a306735436e157d0a22d45f79963c60a8b585d5f7a94c1d2"},
+    {file = "mkdocstrings-0.25.0-py3-none-any.whl", hash = "sha256:df1b63f26675fcde8c1b77e7ea996cd2f93220b148e06455428f676f5dc838f1"},
+    {file = "mkdocstrings-0.25.0.tar.gz", hash = "sha256:066986b3fb5b9ef2d37c4417255a808f7e63b40ff8f67f6cab8054d903fbc91d"},
 ]
 
 [package.dependencies]
@@ -2277,38 +2294,38 @@ files = [
 
 [[package]]
 name = "mypy"
-version = "1.9.0"
+version = "1.10.0"
 description = "Optional static typing for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "mypy-1.9.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:f8a67616990062232ee4c3952f41c779afac41405806042a8126fe96e098419f"},
-    {file = "mypy-1.9.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d357423fa57a489e8c47b7c85dfb96698caba13d66e086b412298a1a0ea3b0ed"},
-    {file = "mypy-1.9.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:49c87c15aed320de9b438ae7b00c1ac91cd393c1b854c2ce538e2a72d55df150"},
-    {file = "mypy-1.9.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:48533cdd345c3c2e5ef48ba3b0d3880b257b423e7995dada04248725c6f77374"},
-    {file = "mypy-1.9.0-cp310-cp310-win_amd64.whl", hash = "sha256:4d3dbd346cfec7cb98e6cbb6e0f3c23618af826316188d587d1c1bc34f0ede03"},
-    {file = "mypy-1.9.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:653265f9a2784db65bfca694d1edd23093ce49740b2244cde583aeb134c008f3"},
-    {file = "mypy-1.9.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:3a3c007ff3ee90f69cf0a15cbcdf0995749569b86b6d2f327af01fd1b8aee9dc"},
-    {file = "mypy-1.9.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2418488264eb41f69cc64a69a745fad4a8f86649af4b1041a4c64ee61fc61129"},
-    {file = "mypy-1.9.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:68edad3dc7d70f2f17ae4c6c1b9471a56138ca22722487eebacfd1eb5321d612"},
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 [package.dependencies]
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 [[package]]
 name = "pluggy"
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 description = "plugin and hook calling mechanisms for python"
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 python-versions = ">=3.8"
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 [package.extras]
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 [[package]]
 name = "pytest"
-version = "8.1.1"
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 iniconfig = "*"
 packaging = "*"
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 [package.extras]
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+dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
 
 [[package]]
 name = "python-dateutil"
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 [[package]]
@@ -3940,13 +3957,13 @@ files = [
 
 [[package]]
 name = "tox"
-version = "4.14.2"
+version = "4.15.0"
 description = "tox is a generic virtualenv management and test command line tool"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -4250,4 +4267,4 @@ desktop = ["opencv-python"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.8"
-content-hash = "56ddae6824a9f28c9954badd4c642c57f687b099c6169f97fa0372e294500c17"
+content-hash = "a2019dd5d779d7fe9ae684d9b133bceb519c87123fd9917b42a86984bc2a7d3b"

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "supervision"
-version = "0.20.0"
+version = "0.21.0rc2"
 description = "A set of easy-to-use utils that will come in handy in any Computer Vision project"
 authors = ["Piotr Skalski <piotr.skalski92@gmail.com>"]
 maintainers = ["Piotr Skalski <piotr.skalski92@gmail.com>"]
@@ -67,7 +67,7 @@ nbconvert = "^7.14.2"
 
 [tool.poetry.group.docs.dependencies]
 mkdocs-material = {extras = ["imaging"], version = "^9.5.5"}
-mkdocstrings = {extras = ["python"], version = ">=0.20,<0.25"}
+mkdocstrings = {extras = ["python"], version = ">=0.20,<0.26"}
 mike = "^2.0.0"
 # For Documentation Development use Python 3.10 or above
 # Use Latest mkdocs-jupyter min 0.24.6 for Jupyter Notebook Theme support

supervision/keypoint/core.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+from contextlib import suppress
 from dataclasses import dataclass, field
 from typing import Any, Dict, Iterator, List, Optional, Tuple, Union
 
@@ -100,6 +101,90 @@ class KeyPoints:
             ]
         )
 
+    @classmethod
+    def from_inference(cls, inference_result: Union[dict, Any]) -> KeyPoints:
+        """
+        Create a `sv.KeyPoints` object from the [Roboflow](https://roboflow.com/)
+        API inference result or the [Inference](https://inference.roboflow.com/)
+        package results. When a keypoint detection model is used, this method
+        extracts the keypoint coordinates, class IDs, confidences, and class names.
+
+        Args:
+            inference_result (dict, any): The result from the
+                Roboflow API or Inference package containing predictions with keypoints.
+
+        Returns:
+            (KeyPoints): A KeyPoints object containing the keypoint coordinates,
+                class IDs, and confidences of each keypoint.
+
+        Example:
+            ```python
+            import cv2
+            import supervision as sv
+            from inference import get_model
+
+            image = cv2.imread(<SOURCE_IMAGE_PATH>)
+            model = get_model(model_id=<POSE_MODEL_ID>, api_key=<ROBOFLOW_API_KEY>)
+
+            result = model.infer(image)[0]
+            key_points = sv.KeyPoints.from_inference(result)
+            ```
+
+            ```python
+            import cv2
+            import supervision as sv
+            from inference_sdk import InferenceHTTPClient
+
+            image = cv2.imread(<SOURCE_IMAGE_PATH>)
+            client = InferenceHTTPClient(
+                api_url="https://detect.roboflow.com",
+                api_key=<ROBOFLOW_API_KEY>
+            )
+
+            result = client.infer(image, model_id=<POSE_MODEL_ID>)
+            key_points = sv.KeyPoints.from_inference(result)
+            ```
+        """
+        if isinstance(inference_result, list):
+            raise ValueError(
+                "from_inference() operates on a single result at a time."
+                "You can retrieve it like so:  inference_result = model.infer(image)[0]"
+            )
+
+        # Unpack the result if received from inference.get_model,
+        # rather than inference_sdk.InferenceHTTPClient
+        with suppress(AttributeError):
+            inference_result = inference_result.dict(exclude_none=True, by_alias=True)
+
+        if not inference_result.get("predictions"):
+            return cls.empty()
+
+        xy = []
+        confidence = []
+        class_id = []
+        class_names = []
+
+        for prediction in inference_result["predictions"]:
+            prediction_xy = []
+            prediction_confidence = []
+            for keypoint in prediction["keypoints"]:
+                prediction_xy.append([keypoint["x"], keypoint["y"]])
+                prediction_confidence.append(keypoint["confidence"])
+            xy.append(prediction_xy)
+            confidence.append(prediction_confidence)
+
+            class_id.append(prediction["class_id"])
+            class_names.append(prediction["class"])
+
+        data = {CLASS_NAME_DATA_FIELD: np.array(class_names)}
+
+        return cls(
+            xy=np.array(xy, dtype=np.float32),
+            confidence=np.array(confidence, dtype=np.float32),
+            class_id=np.array(class_id, dtype=int),
+            data=data,
+        )
+
     @classmethod
     def from_ultralytics(cls, ultralytics_results) -> KeyPoints:
         """

supervision/tracker/byte_tracker/core.py

@@ -12,8 +12,9 @@ from supervision.utils.internal import deprecated_parameter
 
 class STrack(BaseTrack):
     shared_kalman = KalmanFilter()
+    _external_count = 0
 
-    def __init__(self, tlwh, score, class_ids):
+    def __init__(self, tlwh, score, class_ids, minimum_consecutive_frames):
         # wait activate
         self._tlwh = np.asarray(tlwh, dtype=np.float32)
         self.kalman_filter = None
@@ -24,6 +25,10 @@ class STrack(BaseTrack):
         self.class_ids = class_ids
         self.tracklet_len = 0
 
+        self.external_track_id = -1
+
+        self.minimum_consecutive_frames = minimum_consecutive_frames
+
     def predict(self):
         mean_state = self.mean.copy()
         if self.state != TrackState.Tracked:
@@ -53,7 +58,7 @@ class STrack(BaseTrack):
     def activate(self, kalman_filter, frame_id):
         """Start a new tracklet"""
         self.kalman_filter = kalman_filter
-        self.track_id = self.next_id()
+        self.internal_track_id = self.next_id()
         self.mean, self.covariance = self.kalman_filter.initiate(
             self.tlwh_to_xyah(self._tlwh)
         )
@@ -62,6 +67,10 @@ class STrack(BaseTrack):
         self.state = TrackState.Tracked
         if frame_id == 1:
             self.is_activated = True
+
+        if self.minimum_consecutive_frames == 1:
+            self.external_track_id = self.next_external_id()
+
         self.frame_id = frame_id
         self.start_frame = frame_id
 
@@ -71,10 +80,10 @@ class STrack(BaseTrack):
         )
         self.tracklet_len = 0
         self.state = TrackState.Tracked
-        self.is_activated = True
+
         self.frame_id = frame_id
         if new_id:
-            self.track_id = self.next_id()
+            self.internal_track_id = self.next_id()
         self.score = new_track.score
 
     def update(self, new_track, frame_id):
@@ -93,7 +102,10 @@ class STrack(BaseTrack):
             self.mean, self.covariance, self.tlwh_to_xyah(new_tlwh)
         )
         self.state = TrackState.Tracked
-        self.is_activated = True
+        if self.tracklet_len == self.minimum_consecutive_frames:
+            self.is_activated = True
+            if self.external_track_id == -1:
+                self.external_track_id = self.next_external_id()
 
         self.score = new_track.score
 
@@ -131,6 +143,15 @@ class STrack(BaseTrack):
     def to_xyah(self):
         return self.tlwh_to_xyah(self.tlwh)
 
+    @staticmethod
+    def next_external_id():
+        STrack._external_count += 1
+        return STrack._external_count
+
+    @staticmethod
+    def reset_external_counter():
+        STrack._external_count = 0
+
     @staticmethod
     def tlbr_to_tlwh(tlbr):
         ret = np.asarray(tlbr).copy()
@@ -144,7 +165,9 @@ class STrack(BaseTrack):
         return ret
 
     def __repr__(self):
-        return "OT_{}_({}-{})".format(self.track_id, self.start_frame, self.end_frame)
+        return "OT_{}_({}-{})".format(
+            self.internal_track_id, self.start_frame, self.end_frame
+        )
 
 
 def detections2boxes(detections: Detections) -> np.ndarray:
@@ -186,6 +209,10 @@ class ByteTrack:
             Increasing minimum_matching_threshold improves accuracy but risks fragmentation.
             Decreasing it improves completeness but risks false positives and drift.
         frame_rate (int, optional): The frame rate of the video.
+        minimum_consecutive_frames (int, optional): Number of consecutive frames that an object must
+            be tracked before it is considered a 'valid' track.
+            Increasing minimum_consecutive_frames prevents the creation of accidental tracks from
+            false detection or double detection, but risks missing shorter tracks.
     """  # noqa: E501 // docs
 
     @deprecated_parameter(
@@ -218,6 +245,7 @@ class ByteTrack:
         lost_track_buffer: int = 30,
         minimum_matching_threshold: float = 0.8,
         frame_rate: int = 30,
+        minimum_consecutive_frames: int = 1,
     ):
         self.track_activation_threshold = track_activation_threshold
         self.minimum_matching_threshold = minimum_matching_threshold
@@ -225,6 +253,7 @@ class ByteTrack:
         self.frame_id = 0
         self.det_thresh = self.track_activation_threshold + 0.1
         self.max_time_lost = int(frame_rate / 30.0 * lost_track_buffer)
+        self.minimum_consecutive_frames = minimum_consecutive_frames
         self.kalman_filter = KalmanFilter()
 
         self.tracked_tracks: List[STrack] = []
@@ -285,11 +314,14 @@ class ByteTrack:
             matches, _, _ = matching.linear_assignment(iou_costs, 0.5)
             detections.tracker_id = np.full(len(detections), -1, dtype=int)
             for i_detection, i_track in matches:
-                detections.tracker_id[i_detection] = int(tracks[i_track].track_id)
+                detections.tracker_id[i_detection] = int(
+                    tracks[i_track].external_track_id
+                )
 
             return detections[detections.tracker_id != -1]
 
         else:
+            detections = Detections.empty()
             detections.tracker_id = np.array([], dtype=int)
 
             return detections
@@ -308,6 +340,7 @@ class ByteTrack:
         self.lost_tracks: List[STrack] = []
         self.removed_tracks: List[STrack] = []
         BaseTrack.reset_counter()
+        STrack.reset_external_counter()
 
     def update_with_tensors(self, tensors: np.ndarray) -> List[STrack]:
         """
@@ -345,7 +378,7 @@ class ByteTrack:
         if len(dets) > 0:
             """Detections"""
             detections = [
-                STrack(STrack.tlbr_to_tlwh(tlbr), s, c)
+                STrack(STrack.tlbr_to_tlwh(tlbr), s, c, self.minimum_consecutive_frames)
                 for (tlbr, s, c) in zip(dets, scores_keep, class_ids_keep)
             ]
         else:
@@ -387,7 +420,7 @@ class ByteTrack:
         if len(dets_second) > 0:
             """Detections"""
             detections_second = [
-                STrack(STrack.tlbr_to_tlwh(tlbr), s, c)
+                STrack(STrack.tlbr_to_tlwh(tlbr), s, c, self.minimum_consecutive_frames)
                 for (tlbr, s, c) in zip(dets_second, scores_second, class_ids_second)
             ]
         else:
@@ -468,22 +501,22 @@ def joint_tracks(
 ) -> List[STrack]:
     """
     Joins two lists of tracks, ensuring that the resulting list does not
-    contain tracks with duplicate track_id values.
+    contain tracks with duplicate internal_track_id values.
 
     Parameters:
-        track_list_a: First list of tracks (with track_id attribute).
-        track_list_b: Second list of tracks (with track_id attribute).
+        track_list_a: First list of tracks (with internal_track_id attribute).
+        track_list_b: Second list of tracks (with internal_track_id attribute).
 
     Returns:
         Combined list of tracks from track_list_a and track_list_b
-            without duplicate track_id values.
+            without duplicate internal_track_id values.
     """
     seen_track_ids = set()
     result = []
 
     for track in track_list_a + track_list_b:
-        if track.track_id not in seen_track_ids:
-            seen_track_ids.add(track.track_id)
+        if track.internal_track_id not in seen_track_ids:
+            seen_track_ids.add(track.internal_track_id)
             result.append(track)
 
     return result
@@ -492,17 +525,17 @@ def joint_tracks(
 def sub_tracks(track_list_a: List, track_list_b: List) -> List[int]:
     """
     Returns a list of tracks from track_list_a after removing any tracks
-    that share the same track_id with tracks in track_list_b.
+    that share the same internal_track_id with tracks in track_list_b.
 
     Parameters:
-        track_list_a: List of tracks (with track_id attribute).
-        track_list_b: List of tracks (with track_id attribute) to
+        track_list_a: List of tracks (with internal_track_id attribute).
+        track_list_b: List of tracks (with internal_track_id attribute) to
             be subtracted from track_list_a.
     Returns:
         List of remaining tracks from track_list_a after subtraction.
     """
-    tracks = {track.track_id: track for track in track_list_a}
-    track_ids_b = {track.track_id for track in track_list_b}
+    tracks = {track.internal_track_id: track for track in track_list_a}
+    track_ids_b = {track.internal_track_id for track in track_list_b}
 
     for track_id in track_ids_b:
         tracks.pop(track_id, None)