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| import numpy as np | |
| import cv2 | |
| class ViewTransformer(): | |
| def __init__(self): | |
| court_width = 68 | |
| court_length = 23.32 | |
| self.pixel_vertices = np.array([[110, 1035], | |
| [265, 275], | |
| [910, 260], | |
| [1640, 915]]) | |
| self.target_vertices = np.array([ | |
| [0,court_width], | |
| [0, 0], | |
| [court_length, 0], | |
| [court_length, court_width] | |
| ]) | |
| self.pixel_vertices = self.pixel_vertices.astype(np.float32) | |
| self.target_vertices = self.target_vertices.astype(np.float32) | |
| self.persepctive_trasnformer = cv2.getPerspectiveTransform(self.pixel_vertices, self.target_vertices) | |
| def transform_point(self,point): | |
| p = (int(point[0]),int(point[1])) | |
| is_inside = cv2.pointPolygonTest(self.pixel_vertices,p,False) >= 0 | |
| if not is_inside: | |
| return None | |
| reshaped_point = point.reshape(-1,1,2).astype(np.float32) | |
| tranform_point = cv2.perspectiveTransform(reshaped_point,self.persepctive_trasnformer) | |
| return tranform_point.reshape(-1,2) | |
| def add_transformed_position_to_tracks(self,tracks): | |
| for object, object_tracks in tracks.items(): | |
| for frame_num, track in enumerate(object_tracks): | |
| for track_id, track_info in track.items(): | |
| position = track_info['position_adjusted'] | |
| position = np.array(position) | |
| position_trasnformed = self.transform_point(position) | |
| if position_trasnformed is not None: | |
| position_trasnformed = position_trasnformed.squeeze().tolist() | |
| tracks[object][frame_num][track_id]['position_transformed'] = position_trasnformed |