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import numpy as np |
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def box3d_iou(corners1, corners2): |
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''' Compute 3D bounding box IoU. |
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Input: |
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corners1: numpy array (8,3), assume up direction is Z |
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corners2: numpy array (8,3), assume up direction is Z |
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Output: |
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iou: 3D bounding box IoU |
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''' |
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x_min_1, x_max_1, y_min_1, y_max_1, z_min_1, z_max_1 = get_box3d_min_max(corners1) |
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x_min_2, x_max_2, y_min_2, y_max_2, z_min_2, z_max_2 = get_box3d_min_max(corners2) |
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xA = np.maximum(x_min_1, x_min_2) |
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yA = np.maximum(y_min_1, y_min_2) |
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zA = np.maximum(z_min_1, z_min_2) |
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xB = np.minimum(x_max_1, x_max_2) |
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yB = np.minimum(y_max_1, y_max_2) |
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zB = np.minimum(z_max_1, z_max_2) |
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inter_vol = np.maximum((xB - xA), 0) * np.maximum((yB - yA), 0) * np.maximum((zB - zA), 0) |
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box_vol_1 = (x_max_1 - x_min_1) * (y_max_1 - y_min_1) * (z_max_1 - z_min_1) |
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box_vol_2 = (x_max_2 - x_min_2) * (y_max_2 - y_min_2) * (z_max_2 - z_min_2) |
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iou = inter_vol / (box_vol_1 + box_vol_2 - inter_vol + 1e-8) |
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return iou |
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def get_box3d_min_max(corner): |
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''' Compute min and max coordinates for 3D bounding box |
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Note: only for axis-aligned bounding boxes |
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Input: |
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corners: numpy array (8,3), assume up direction is Z (batch of N samples) |
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Output: |
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box_min_max: an array for min and max coordinates of 3D bounding box IoU |
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''' |
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min_coord = corner.min(axis=0) |
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max_coord = corner.max(axis=0) |
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x_min, x_max = min_coord[0], max_coord[0] |
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y_min, y_max = min_coord[1], max_coord[1] |
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z_min, z_max = min_coord[2], max_coord[2] |
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return x_min, x_max, y_min, y_max, z_min, z_max |
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def get_3d_box(center, box_size): |
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''' box_size is array(l,w,h), heading_angle is radius clockwise from pos x axis, center is xyz of box center |
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output (8,3) array for 3D box cornders |
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Similar to utils/compute_orientation_3d |
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''' |
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l,w,h = box_size |
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x_corners = [l/2,l/2,-l/2,-l/2,l/2,l/2,-l/2,-l/2] |
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y_corners = [w/2,-w/2,-w/2,w/2,w/2,-w/2,-w/2,w/2] |
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z_corners = [h/2,h/2,h/2,h/2,-h/2,-h/2,-h/2,-h/2] |
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corners_3d = np.vstack([x_corners,y_corners,z_corners]) |
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corners_3d[0,:] = corners_3d[0,:] + center[0] |
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corners_3d[1,:] = corners_3d[1,:] + center[1] |
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corners_3d[2,:] = corners_3d[2,:] + center[2] |
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corners_3d = np.transpose(corners_3d) |
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return corners_3d |
