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| | example2 - person height.aligned_stream = rs.align(rs.stream.color) |
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| tuple | example2 - person height.bbox = (int(left), int(top), int(width), int(height)) |
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| | example2 - person height.bottom = box[2]*H |
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| tuple | example2 - person height.bottomLeftCornerOfText = (p1[0], p1[1] + 20) |
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| | example2 - person height.box = boxes[idx] |
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| | example2 - person height.boxes = np.squeeze(boxes) |
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| | example2 - person height.class_ = classes[idx] |
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| | example2 - person height.classes = np.squeeze(classes).astype(np.int32) |
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| | example2 - person height.color_frame = frames.get_color_frame() |
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| | example2 - person height.color_image = np.asanyarray(color_frame.get_data()) |
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| | example2 - person height.config = rs.config() |
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| | example2 - person height.depth_frame = frames.get_depth_frame() |
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| | example2 - person height.detection_boxes = detection_graph.get_tensor_by_name('detection_boxes:0') |
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| | example2 - person height.detection_classes = detection_graph.get_tensor_by_name('detection_classes:0') |
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| | example2 - person height.detection_graph = tf.Graph() |
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| | example2 - person height.detection_scores = detection_graph.get_tensor_by_name('detection_scores:0') |
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| | example2 - person height.feed_dict |
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| | example2 - person height.font = cv2.FONT_HERSHEY_SIMPLEX |
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| tuple | example2 - person height.fontColor = (255, 255, 255) |
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| int | example2 - person height.fontScale = 1 |
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| | example2 - person height.frames = pipeline.wait_for_frames() |
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| int | example2 - person height.H = 480 |
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| | example2 - person height.height = bottom-top |
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| string | example2 - person height.height_txt = str(height)+"[m]" |
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| | example2 - person height.image_expanded = np.expand_dims(color_image, axis=0) |
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| | example2 - person height.image_tensor = detection_graph.get_tensor_by_name('image_tensor:0') |
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| | example2 - person height.left = box[1]*W |
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| int | example2 - person height.lineType = 2 |
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| | example2 - person height.my = np.amin(ys, initial=1) |
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| | example2 - person height.My = np.amax(ys, initial=-1) |
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| | example2 - person height.name |
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| | example2 - person height.num |
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| | example2 - person height.num_detections = detection_graph.get_tensor_by_name('num_detections:0') |
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| | example2 - person height.obj_points = verts[int(bbox[1]):int(bbox[1] + bbox[3]), int(bbox[0]):int(bbox[0] + bbox[2])].reshape(-1, 3) |
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| | example2 - person height.od_graph_def = tf.compat.v1.GraphDef() |
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| tuple | example2 - person height.p1 = (int(bbox[0]), int(bbox[1])) |
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| tuple | example2 - person height.p2 = (int(bbox[0] + bbox[2]), int(bbox[1] + bbox[3])) |
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| string | example2 - person height.PATH_TO_CKPT = r"frozen_inference_graph.pb" |
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| | example2 - person height.pipeline = rs.pipeline() |
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| | example2 - person height.point_cloud = rs.pointcloud() |
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| | example2 - person height.points = point_cloud.calculate(depth_frame) |
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| | example2 - person height.right = box[3]*W |
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| tuple | example2 - person height.scaled_size = (int(W), int(H)) |
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| | example2 - person height.score = scores[idx] |
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| | example2 - person height.scores = np.squeeze(scores) |
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| | example2 - person height.serialized_graph = fid.read() |
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| | example2 - person height.sess = tf.compat.v1.Session(graph=detection_graph) |
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| | example2 - person height.top = box[0]*H |
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| | example2 - person height.verts = np.asanyarray(points.get_vertices()).view(np.float32).reshape(-1, W, 3) |
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| int | example2 - person height.W = 848 |
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| | example2 - person height.width = right-left |
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| | example2 - person height.ys = obj_points[:, 1] |
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| | example2 - person height.z = np.median(zs) |
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| | example2 - person height.zs = obj_points[:, 2] |
| |