From 4e88e26d912d230cc49d26fb319a18cc3fbf46e2 Mon Sep 17 00:00:00 2001 From: Onuralp SEZER Date: Thu, 21 Sep 2023 15:43:07 +0300 Subject: [PATCH] chore(formatting): pre-commit fixes Signed-off-by: Onuralp SEZER --- supervision/annotators/composable.py | 6 ++- supervision/annotators/core.py | 55 +++++++++++++++++++--------- 2 files changed, 41 insertions(+), 20 deletions(-) diff --git a/supervision/annotators/composable.py b/supervision/annotators/composable.py index 060ab654..d1ecb48a 100644 --- a/supervision/annotators/composable.py +++ b/supervision/annotators/composable.py @@ -33,7 +33,8 @@ class ComposableAnnotator(ABC): class DetectionAnnotator(ComposableAnnotator): """ - Highlevel API for drawing Object Detection output. This will use Box and Label Annotators + Highlevel API for drawing Object Detection output. + This will use Box and Label Annotators Example: ```python >>> import supervision as sv @@ -63,7 +64,8 @@ class DetectionAnnotator(ComposableAnnotator): class SegmentationAnnotator(ComposableAnnotator): """ - High level API for drawing segmentation mask, bounding box and labels on an image using provided detections. + High level API for drawing segmentation mask, bounding box and labels on an + image using provided detections. Example: ```python >>> import supervision as sv diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py index 1a8456d1..3e4fa0ed 100644 --- a/supervision/annotators/core.py +++ b/supervision/annotators/core.py @@ -28,7 +28,8 @@ def resolve_color_idx( ) -> int: if detection_idx >= len(detections): raise ValueError( - f"Detection index {detection_idx} is out of bounds for detections of length {len(detections)}" + f"Detection index {detection_idx}" + f"is out of bounds for detections of length {len(detections)}" ) if color_map == ColorMap.INDEX: @@ -36,13 +37,15 @@ def resolve_color_idx( elif color_map == ColorMap.CLASS: if detections.class_id is None: raise ValueError( - "Could not resolve color by class because Detections do not have class_id" + "Could not resolve color by class because" + "Detections do not have class_id" ) return detections.class_id[detection_idx] elif color_map == ColorMap.TRACK: if detections.tracker_id is None: raise ValueError( - "Could not resolve color by track because Detections do not have tracker_id" + "Could not resolve color by track because" + "Detections do not have tracker_id" ) return detections.tracker_id[detection_idx] @@ -73,7 +76,8 @@ class BoxLineAnnotator(BaseAnnotator): ): """ Parameters: - color (Union[Color, ColorPalette]): The color to use for annotating detections. + color (Union[Color, ColorPalette]): The color to use for + annotating detections. thickness (int): The thickness of the bounding box lines. color_map (ColorMap): The color mapping to use for annotating detections. """ @@ -87,7 +91,8 @@ class BoxLineAnnotator(BaseAnnotator): Args: scene (np.ndarray): The image on which the bounding boxes will be drawn - detections (Detections): The detections for which the bounding boxes will be drawn + detections (Detections): The detections for which + the bounding boxes will be drawn Returns: np.ndarray: The image with the bounding boxes drawn on it. @@ -128,7 +133,8 @@ class MaskAnnotator(BaseAnnotator): A class for overlaying masks on an image using detections provided. Attributes: - color (Union[Color, ColorPalette]): The color to fill the mask, can be a single color or a color palette + color (Union[Color, ColorPalette]): The color to fill the mask, + can be a single color or a color palette opacity (float): The opacity of the masks, between 0 and 1. """ @@ -146,7 +152,8 @@ class MaskAnnotator(BaseAnnotator): self, scene: np.ndarray, detections: Detections, **kwargs ) -> np.ndarray: """ - Overlays the masks on the given image based on the provided detections, with a specified opacity. + Overlays the masks on the given image based on the provided detections, + with a specified opacity. Args: scene (np.ndarray): The image on which the masks will be overlaid @@ -223,7 +230,8 @@ class LabelAnnotator(BaseAnnotator): A class for putting text on an image using provided detections. Attributes: - color (Union[Color, ColorPalette]): The color to text on the image, can be a single color or a color palette + color (Union[Color, ColorPalette]): The color to text on the image, + can be a single color or a color palette """ def __init__( @@ -243,7 +251,8 @@ class LabelAnnotator(BaseAnnotator): Args: color_by_track: pick color by tracker id classes: Optional list of class name - label_formatter: Optional callback function for label generator, avoided if classes is provided + label_formatter: Optional callback function for label generator, + avoided if classes is provided """ self.color: Union[Color, ColorPalette] = color self.text_color: Color = text_color @@ -264,7 +273,8 @@ class LabelAnnotator(BaseAnnotator): Args: scene (np.ndarray): The image on which the bounding boxes will be drawn - detections (Detections): The detections for which the bounding boxes will be drawn + detections (Detections): The detections for which + the bounding boxes will be drawn Returns: np.ndarray: The image with the bounding boxes drawn on it @@ -377,7 +387,8 @@ class BoxMaskAnnotator(BaseAnnotator): detections: Detections, ) -> np.ndarray: """ - Overlays the rectangle masks on the given image based on the provided detections, with a specified opacity. + Overlays the rectangle masks on the given image based on the + provided detections, with a specified opacity. Args: scene (np.ndarray): The image on which the masks will be overlaid @@ -468,8 +479,11 @@ class LabelAdvancedAnnotator(BaseAnnotator): Args: scene (np.ndarray): The image on which the bounding boxes will be drawn - detections (Detections): The detections for which the bounding boxes will be drawn - labels (Optional[List[str]]): An optional list of labels corresponding to each detection. If `labels` are not provided, corresponding `class_id` will be used as label. + detections (Detections): The detections for which + the bounding boxes will be drawn + labels (Optional[List[str]]): An optional list of labels corresponding + to each detection. If `labels` are not provided, + corresponding `class_id` will be used as label. Returns: np.ndarray: The image with the bounding boxes drawn on it @@ -574,7 +588,8 @@ class BoxCornerAnnotator(BaseAnnotator): Draws cornered bounding boxes on the frame using the detections provided. Args: scene (np.ndarray): The image on which the bounding boxes will be drawn - detections (Detections): The detections for which the bounding boxes will be drawn + detections (Detections): The detections for which + the bounding boxes will be drawn Returns: np.ndarray: The image with the bounding boxes drawn on it Example: @@ -700,10 +715,12 @@ class EllipseAnnotator(BaseAnnotator): detections: Detections, ): """ - Draws ellipse at bottom of the objects on the frame using the detections provided. + Draws ellipse at bottom of the objects on the frame using the detections + provided. Args: scene (np.ndarray): The image on which the bounding boxes will be drawn - detections (Detections): The detections for which the bounding boxes will be drawn + detections (Detections): The detections for which + the bounding boxes will be drawn Returns: np.ndarray: The image with the bounding boxes drawn on it Example: @@ -764,9 +781,11 @@ class TraceAnnotator(BaseAnnotator): A class for drawing trajectory of a tracker on an image using detections provided. Attributes: - color (Union[Color, ColorPalette]): The color to draw the trajectory, can be a single color or a color palette + color (Union[Color, ColorPalette]): The color to draw the trajectory, + can be a single color or a color palette color_by_track (bool): Whther to use tracker id to pick the color - position (Optional[Position]): Choose position of trajectory such as center position, top left corner, etc + position (Optional[Position]): Choose position of trajectory such as + center position, top left corner, etc trace_length (int): Length of the previous points thickness (int): thickness of the line """