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December 16, 2025 20:02
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A small Python script that reads dice rolls out loud. See https://golsteyn.com/projects/dice/ for more info!
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| import cv2 | |
| import numpy as np | |
| from sklearn import cluster | |
| params = cv2.SimpleBlobDetector_Params() | |
| params.filterByInertia | |
| params.minInertiaRatio = 0.6 | |
| detector = cv2.SimpleBlobDetector_create(params) | |
| def get_blobs(frame): | |
| frame_blurred = cv2.medianBlur(frame, 7) | |
| frame_gray = cv2.cvtColor(frame_blurred, cv2.COLOR_BGR2GRAY) | |
| blobs = detector.detect(frame_gray) | |
| return blobs | |
| def get_dice_from_blobs(blobs): | |
| # Get centroids of all blobs | |
| X = [] | |
| for b in blobs: | |
| pos = b.pt | |
| if pos != None: | |
| X.append(pos) | |
| X = np.asarray(X) | |
| if len(X) > 0: | |
| # Important to set min_sample to 0, as a dice may only have one dot | |
| clustering = cluster.DBSCAN(eps=40, min_samples=0).fit(X) | |
| # Find the largest label assigned + 1, that's the number of dice found | |
| num_dice = max(clustering.labels_) + 1 | |
| dice = [] | |
| # Calculate centroid of each dice, the average between all a dice's dots | |
| for i in range(num_dice): | |
| X_dice = X[clustering.labels_ == i] | |
| centroid_dice = np.mean(X_dice, axis=0) | |
| dice.append([len(X_dice), *centroid_dice]) | |
| return dice | |
| else: | |
| return [] | |
| def overlay_info(frame, dice, blobs): | |
| # Overlay blobs | |
| for b in blobs: | |
| pos = b.pt | |
| r = b.size / 2 | |
| cv2.circle(frame, (int(pos[0]), int(pos[1])), | |
| int(r), (255, 0, 0), 2) | |
| # Overlay dice number | |
| for d in dice: | |
| # Get textsize for text centering | |
| textsize = cv2.getTextSize( | |
| str(d[0]), cv2.FONT_HERSHEY_PLAIN, 3, 2)[0] | |
| cv2.putText(frame, str(d[0]), | |
| (int(d[1] - textsize[0] / 2), | |
| int(d[2] + textsize[1] / 2)), | |
| cv2.FONT_HERSHEY_PLAIN, 3, (0, 255, 0), 2) | |
| # Initialize a video feed | |
| cap = cv2.VideoCapture(0) | |
| while(True): | |
| # Grab the latest image from the video feed | |
| ret, frame = cap.read() | |
| # We'll define these later | |
| blobs = get_blobs(frame) | |
| dice = get_dice_from_blobs(blobs) | |
| out_frame = overlay_info(frame, dice, blobs) | |
| cv2.imshow("frame", frame) | |
| res = cv2.waitKey(1) | |
| # Stop if the user presses "q" | |
| if res & 0xFF == ord('q'): | |
| break | |
| # When everything is done, release the capture | |
| cap.release() | |
| cv2.destroyAllWindows() |
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Thanks for this, it has pointed me in the right direction for my project.