bounding_box.py

import cv2
import numpy as np
import supervision as sv
from roboflow import Roboflow

# use https://roboflow.github.io/polygonzone/ to get the points for your line
polygon = np.array([
    # draw 50x50 box in top left corner
    [0, 0],
    [50, 0],
    [50, 50],
    [0, 50]
])

rf = Roboflow(api_key="l3NrjFPSGysLJZVieZdI")
project = rf.workspace().project("playing-cards-ow27d")
model = project.version(4).model

# create BYTETracker instance
byte_tracker = sv.ByteTrack(track_thresh=0.25, track_buffer=30, match_thresh=0.8, frame_rate=30)

# create PolygonZone instance
zone = sv.PolygonZone(polygon=polygon, frame_resolution_wh=(640, 480))  # adjust this to your image's resolution

# create bounding box annotator and label annotator
bounding_box_annotator = sv.BoundingBoxAnnotator(thickness=4)
label_annotator = sv.LabelAnnotator(text_thickness=4, text_scale=2)

colors = sv.ColorPalette.default()

# create instance of PolygonZoneAnnotator
zone_annotator = sv.PolygonZoneAnnotator(thickness=4, text_thickness=4, text_scale=2, zone=zone, color=colors.colors[0])

# define call back function to be used in image processing
def callback(frame: np.ndarray, index:int) -> np.ndarray:
    # model prediction on single frame and conversion to supervision Detections
    results = model.predict(frame).json()

    detections = sv.Detections.from_inference(results)

    # show detections in real time
    print(detections)

    # tracking detections
    detections = byte_tracker.update_with_detections(detections)

    labels = [
        f"#{tracker_id} {model.classes[class_id]} {confidence:0.2f}"
        for _, _, confidence, class_id, tracker_id, *_ in detections
    ]

    annotated_frame = bounding_box_annotator.annotate(scene=frame, detections=detections)
    annotated_frame = label_annotator.annotate(scene=annotated_frame, detections=detections, labels=labels)

    annotated_frame = zone_annotator.annotate(scene=annotated_frame)
    # return frame with box and line annotated result
    return annotated_frame

# Load the image
frame = cv2.imread('cards1.jpg')

# Check if the image is loaded correctly
if frame is None:
    raise IOError("Cannot open image")

# process the image
frame = callback(frame, 0)

# Display the resulting image
cv2.imshow('Image', frame)

# Wait for any key press and close the window
cv2.waitKey(0)
cv2.destroyAllWindows()