I have the following package through which I am getting the screen size
from screeninfo import get_monitors
and then passing the screen size to the following function to get the full screen size while maintaining the aspect ratio
def ResizeWithAspectRatio(image, width=None, height=None, inter=cv2.INTER_AREA):
dim = None
(h, w) = image.shape[:2]
if width is None and height is None:
return image
if width is None:
r = height / float(h)
dim = (int(w * r), height)
else:
r = width / float(w)
dim = (width, int(h * r))
resized_image = cv2.resize(image, dim, interpolation=inter)
return resized_image,r
how do I scale the zone?
class CustomSink:
def __init__(self, weights_path: str, zone_configuration_path: str, classes: List[int]):
self._model = YOLO(weights_path)
self.classes = classes
self.tracker = sv.ByteTrack(minimum_matching_threshold=0.5)
self.fps_monitor = sv.FPSMonitor()
self.polygons = load_zones_config(file_path=zone_configuration_path)
self.timers = [ClockBasedTimer() for _ in self.polygons]
self.zones = [
sv.PolygonZone(
polygon=polygon,
triggering_anchors=(sv.Position.CENTER,),
)
for polygon in self.polygons
]
def infer(self, video_frames: List[VideoFrame]) -> List[any]:
# return self._model([v.image for v in video_frames], imgsz="800")
resized_frames = [ResizeWithAspectRatio(v.image, width=screen_width)[0] for v in video_frames]
results = self._model(resized_frames)
return results
def on_prediction(self, result: dict, frame: VideoFrame) -> None:
self.fps_monitor.tick()
fps = self.fps_monitor.fps
detections = sv.Detections.from_ultralytics(result)
detections = detections[find_in_list(detections.class_id, self.classes)]
detections = self.tracker.update_with_detections(detections)
// extracting the scale factor r
resized_frames, r = ResizeWithAspectRatio(frame.image, width=screen_width)
annotated_frame = resized_frames.copy()
annotated_frame = sv.draw_text(
scene=annotated_frame,
text=f"{fps:.1f}",
text_anchor=sv.Point(40, 30),
background_color=sv.Color.from_hex("#A351FB"),
text_color=sv.Color.from_hex("#000000"),
)
for idx, zone in enumerate(self.zones):
annotated_frame = sv.draw_polygon(
// if I multiply zone.polygon with r(scaling factor I get error
scene=annotated_frame, polygon=zone.polygon *r , color=COLORS.by_idx(idx)
)
detections_in_zone = detections[zone.trigger(detections)]
time_in_zone = self.timers[idx].tick(detections_in_zone)
custom_color_lookup = np.full(detections_in_zone.class_id.shape, idx)
annotated_frame = COLOR_ANNOTATOR.annotate(
scene=annotated_frame,
detections=detections_in_zone,
custom_color_lookup=custom_color_lookup,
)
labels = [
f"#{tracker_id} {int(time // 60):02d}:{int(time % 60):02d}"
for tracker_id, time in zip(detections_in_zone.tracker_id, time_in_zone)
]
annotated_frame = LABEL_ANNOTATOR.annotate(
scene=annotated_frame,
detections=detections_in_zone,
labels=labels,
custom_color_lookup=custom_color_lookup,
)
cv2.imshow("Processed Video", annotated_frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
cv2.destroyAllWindows()
raise SystemExit("Program terminated by user")
following error
WARNING Error in results dispatching - OpenCV(4.8.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\drawing.cpp:2463: error: inference_pipeline.py:905
(-215:Assertion failed) p.checkVector(2, CV_32S) >= 0 in function 'cv::polylines'