Delete view_transformer.py

view_transformer.py

@@ -1,61 +0,0 @@
-from sports import MeasurementUnit
-from sports.basketball import CourtConfiguration, League, draw_court, draw_points_on_court
-import numpy as np
-import supervision as sv
-import cv2
-
-CONFIG = CourtConfiguration(league=League.NBA, measurement_unit=MeasurementUnit.FEET).vertices
-
-def frame_xy_to_court_xy(frame_xy: np.ndarray, H: np.ndarray):
-
-    assert frame_xy.shape[1] == 2
-    n_points = frame_xy.shape[0]
-
-    court_xy = np.hstack((frame_xy, np.ones(shape=(n_points, 1)))) @ H.T
-    court_xy_norm = court_xy[:, :2] / court_xy[:, [-1]]
-    return court_xy_norm
-
-def get_players_court_xy(frame, detections, model, use_bottom_center=True, normalize=False):
-    KEYPOINT_DETECTION_MODEL_CONFIDENCE = 0.3
-    KEYPOINT_DETECTION_MODEL_ANCHOR_CONFIDENCE = 0.5
-
-    # Locate court keypoints (or reference points)
-    result = model.infer(frame, confidence=KEYPOINT_DETECTION_MODEL_CONFIDENCE)[0]
-    key_points = sv.KeyPoints.from_inference(result)
-    filter_mask = key_points.confidence[0] > KEYPOINT_DETECTION_MODEL_ANCHOR_CONFIDENCE
-
-    # Compute homography matrix H
-    court_landmarks = np.array(CONFIG)[filter_mask]
-    frame_landmarks = key_points[:, filter_mask].xy[0]
-    H, _ = cv2.findHomography(frame_landmarks, court_landmarks)
-
-    # From the player detections, retrieve their position on the court
-    x1 = detections.xyxy[:, 0]
-    x2 = detections.xyxy[:, 2]
-    y1 = detections.xyxy[:, 1]
-    y2 = detections.xyxy[:, 3]
-    if use_bottom_center:
-        # Take the bottom center of the bounding box as the (x,y) coordinate
-        frame_xy = np.vstack(
-        (x1 + (x2 - x1) / 2, y2)
-        ).T
-    else:
-        frame_xy = np.vstack(
-        (x1 + (x2 - x1) / 2, y1 + (y2 - y1) / 2)
-        ).T
-    # apply homographic transformation
-    court_xy = frame_xy_to_court_xy(frame_xy, H)
-
-    if normalize:
-        court_xy = court_xy / np.array([94.0, 50.0])
-
-    return court_xy
-
-def show_positions_on_court(court_xy):
-    court = draw_court(config=CONFIG)
-    court = draw_points_on_court(
-        config=CONFIG,
-        xy=court_xy,
-        court=court
-    )
-    sv.plot_image(court)