jonas_he's profile - activity

Hello I am currently working on creating a python software that tracks players on a soccer field. I got the player detection working with YoloV3 and was able to output quite a nice result with players centroids and boxes drawn. What i want to do now is translate the players position and project their centroids onto a png/jpg of a soccerfield. For this I inteded to use two arrays with refrence points one for the soccerfield-image and one for the source video. But my question now is how do I translate the coordinates of the centroids to the soccerfield image.

Similiar example:

How the boxes and Markers are drawn:

def draw_labels_and_boxes(img, boxes, confidences, classids, idxs, colors, labels):
# If there are any detections
if len(idxs) > 0:
    for i in idxs.flatten():
        # Get the bounding box coordinates
        x, y = boxes[i][0], boxes[i][1]
        w, h = boxes[i][2], boxes[i][3]

        # Draw the bounding box rectangle and label on the image
        cv.rectangle(img, (x, y), (x + w, y + h), (255, 255, 255), 2)
        cv.drawMarker (img, (int(x + w / 2), int(y + h / 2)), (x, y), 0, 20, 3)
return img

Boxes generated like this:

def generate_boxes_confidences_classids(outs, height, width, tconf):
    boxes = []
    confidences = []
    classids = []

    for out in outs:
        for detection in out:
            # print (detection)
            # a = input('GO!')

            # Get the scores, classid, and the confidence of the prediction
            scores = detection[5:]
            classid = np.argmax(scores)
            confidence = scores[classid]

            # Consider only the predictions that are above a certain confidence level
            if confidence > tconf:
                # TODO Check detection
                box = detection[0:4] * np.array([width, height, width, height])
                centerX, centerY, bwidth, bheight = box.astype('int')

                # Using the center x, y coordinates to derive the top
                # and the left corner of the bounding box
                x = int(centerX - (bwidth / 2))
                y = int(centerY - (bheight / 2))

                # Append to list
                boxes.append([x, y, int(bwidth), int(bheight)])
                confidences.append(float(confidence))
                classids.append(classid)

    return boxes, confidences, classids

Birdseye transform with getPerspectiveTransform Hello I am currently working on creating a python software that tracks p