remove vp everywhere (#2122)
* remove vp everywhere * wrong dimension * useful disclaimer * switcheroo * imcomplete switcheroo * did it wrong again * difference look small enough * fix comment
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@ -1,4 +1,10 @@
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#!/usr/bin/env python3
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'''
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This process finds calibration values. More info on what these calibration values
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are can be found here https://github.com/commaai/openpilot/tree/master/common/transformations
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While the roll calibration is a real value that can be estimated, here we assume it zero,
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and the image input into the neural network is not corrected for roll.
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'''
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import os
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import copy
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@ -10,8 +16,8 @@ from selfdrive.locationd.calibration_helpers import Calibration
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from selfdrive.swaglog import cloudlog
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from common.params import Params, put_nonblocking
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from common.transformations.model import model_height
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from common.transformations.camera import view_frame_from_device_frame, get_view_frame_from_road_frame, \
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get_calib_from_vp, vp_from_rpy, H, W, FOCAL
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from common.transformations.camera import get_view_frame_from_road_frame
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from common.transformations.orientation import rot_from_euler, euler_from_rot
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MIN_SPEED_FILTER = 15 * CV.MPH_TO_MS
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MAX_VEL_ANGLE_STD = np.radians(0.25)
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@ -19,40 +25,34 @@ MAX_YAW_RATE_FILTER = np.radians(2) # per second
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# This is all 20Hz, blocks needed for efficiency
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BLOCK_SIZE = 100
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INPUTS_NEEDED = 5 # allow to update VP every so many frames
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INPUTS_NEEDED = 5 # Minimum blocks needed for valid calibration
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INPUTS_WANTED = 50 # We want a little bit more than we need for stability
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WRITE_CYCLES = 10 # write every 1000 cycles
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VP_INIT = np.array([W/2., H/2.])
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RPY_INIT = np.array([0,0,0])
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# These values are needed to accomodate biggest modelframe
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VP_VALIDITY_CORNERS = np.array([[W//2 - 63, 300], [W//2 + 63, 520]])
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PITCH_LIMITS = np.array([-0.09074112085129739, 0.14907572052989657])
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YAW_LIMITS = np.array([-0.06912048084718224, 0.06912048084718235])
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DEBUG = os.getenv("DEBUG") is not None
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def is_calibration_valid(vp):
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return vp[0] > VP_VALIDITY_CORNERS[0, 0] and vp[0] < VP_VALIDITY_CORNERS[1, 0] and \
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vp[1] > VP_VALIDITY_CORNERS[0, 1] and vp[1] < VP_VALIDITY_CORNERS[1, 1]
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def is_calibration_valid(rpy):
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return (PITCH_LIMITS[0] < rpy[1] < PITCH_LIMITS[1]) and (YAW_LIMITS[0] < rpy[2] < YAW_LIMITS[1])
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def sanity_clip(vp):
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if np.isnan(vp).any():
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vp = VP_INIT
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return np.array([np.clip(vp[0], VP_VALIDITY_CORNERS[0, 0] - 5, VP_VALIDITY_CORNERS[1, 0] + 5),
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np.clip(vp[1], VP_VALIDITY_CORNERS[0, 1] - 5, VP_VALIDITY_CORNERS[1, 1] + 5)])
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def sanity_clip(rpy):
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if np.isnan(rpy).any():
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rpy = RPY_INIT
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return np.array([rpy[0],
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np.clip(rpy[1], PITCH_LIMITS[0] - .005, PITCH_LIMITS[1] + .005),
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np.clip(rpy[2], YAW_LIMITS[0] - .005, YAW_LIMITS[1] + .005)])
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def intrinsics_from_vp(vp):
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return np.array([
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[FOCAL, 0., vp[0]],
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[ 0., FOCAL, vp[1]],
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[ 0., 0., 1.]])
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class Calibrator():
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def __init__(self, param_put=False):
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self.param_put = param_put
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self.vp = copy.copy(VP_INIT)
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self.vps = np.zeros((INPUTS_WANTED, 2))
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self.rpy = copy.copy(RPY_INIT)
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self.rpys = np.zeros((INPUTS_WANTED, 3))
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self.idx = 0
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self.block_idx = 0
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self.valid_blocks = 0
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@ -68,10 +68,10 @@ class Calibrator():
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if calibration_params:
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try:
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calibration_params = json.loads(calibration_params)
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self.vp = vp_from_rpy(calibration_params["calib_radians"])
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if not np.isfinite(self.vp).all():
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self.vp = copy.copy(VP_INIT)
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self.vps = np.tile(self.vp, (INPUTS_WANTED, 1))
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self.rpy = calibration_params["calib_radians"]
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if not np.isfinite(self.rpy).all():
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self.rpy = copy.copy(RPY_INIT)
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self.rpys = np.tile(self.rpy, (INPUTS_WANTED, 1))
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self.valid_blocks = calibration_params['valid_blocks']
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if not np.isfinite(self.valid_blocks) or self.valid_blocks < 0:
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self.valid_blocks = 0
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@ -84,7 +84,7 @@ class Calibrator():
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if self.valid_blocks < INPUTS_NEEDED:
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self.cal_status = Calibration.UNCALIBRATED
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else:
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self.cal_status = Calibration.CALIBRATED if is_calibration_valid(self.vp) else Calibration.INVALID
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self.cal_status = Calibration.CALIBRATED if is_calibration_valid(self.rpy) else Calibration.INVALID
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end_status = self.cal_status
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self.just_calibrated = False
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@ -99,47 +99,45 @@ class Calibrator():
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certain_if_calib = ((np.arctan2(trans_std[1], trans[0]) < MAX_VEL_ANGLE_STD) or
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(self.valid_blocks < INPUTS_NEEDED))
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if straight_and_fast and certain_if_calib:
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# intrinsics are not eon intrinsics, since this is calibrated frame
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intrinsics = intrinsics_from_vp(self.vp)
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new_vp = intrinsics.dot(view_frame_from_device_frame.dot(trans))
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new_vp = new_vp[:2]/new_vp[2]
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new_vp = sanity_clip(new_vp)
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observed_rpy = np.array([0,
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-np.arctan2(trans[2], trans[0]),
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np.arctan2(trans[1], trans[0])])
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new_rpy = euler_from_rot(rot_from_euler(self.rpy).dot(rot_from_euler(observed_rpy)))
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new_rpy = sanity_clip(new_rpy)
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self.vps[self.block_idx] = (self.idx*self.vps[self.block_idx] + (BLOCK_SIZE - self.idx) * new_vp) / float(BLOCK_SIZE)
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self.rpys[self.block_idx] = (self.idx*self.rpys[self.block_idx] + (BLOCK_SIZE - self.idx) * new_rpy) / float(BLOCK_SIZE)
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self.idx = (self.idx + 1) % BLOCK_SIZE
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if self.idx == 0:
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self.block_idx += 1
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self.valid_blocks = max(self.block_idx, self.valid_blocks)
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self.block_idx = self.block_idx % INPUTS_WANTED
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if self.valid_blocks > 0:
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self.vp = np.mean(self.vps[:self.valid_blocks], axis=0)
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self.rpy = np.mean(self.rpys[:self.valid_blocks], axis=0)
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self.update_status()
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if self.param_put and ((self.idx == 0 and self.block_idx == 0) or self.just_calibrated):
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calib = get_calib_from_vp(self.vp)
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cal_params = {"calib_radians": list(calib),
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cal_params = {"calib_radians": list(self.rpy),
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"valid_blocks": self.valid_blocks}
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put_nonblocking("CalibrationParams", json.dumps(cal_params).encode('utf8'))
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return new_vp
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return new_rpy
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else:
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return None
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def send_data(self, pm):
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calib = get_calib_from_vp(self.vp)
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if self.valid_blocks > 0:
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max_vp_calib = np.array(get_calib_from_vp(np.max(self.vps[:self.valid_blocks], axis=0)))
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min_vp_calib = np.array(get_calib_from_vp(np.min(self.vps[:self.valid_blocks], axis=0)))
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calib_spread = np.abs(max_vp_calib - min_vp_calib)
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max_rpy_calib = np.array(np.max(self.rpys[:self.valid_blocks], axis=0))
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min_rpy_calib = np.array(np.min(self.rpys[:self.valid_blocks], axis=0))
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calib_spread = np.abs(max_rpy_calib - min_rpy_calib)
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else:
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calib_spread = np.zeros(3)
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extrinsic_matrix = get_view_frame_from_road_frame(0, calib[1], calib[2], model_height)
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extrinsic_matrix = get_view_frame_from_road_frame(0, self.rpy[1], self.rpy[2], model_height)
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cal_send = messaging.new_message('liveCalibration')
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cal_send.liveCalibration.validBlocks = self.valid_blocks
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cal_send.liveCalibration.calStatus = self.cal_status
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cal_send.liveCalibration.calPerc = min(100 * (self.valid_blocks * BLOCK_SIZE + self.idx) // (INPUTS_NEEDED * BLOCK_SIZE), 100)
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cal_send.liveCalibration.extrinsicMatrix = [float(x) for x in extrinsic_matrix.flatten()]
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cal_send.liveCalibration.rpyCalib = [float(x) for x in calib]
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cal_send.liveCalibration.rpyCalib = [float(x) for x in self.rpy]
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cal_send.liveCalibration.rpyCalibSpread = [float(x) for x in calib_spread]
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pm.send('liveCalibration', cal_send)
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@ -170,13 +168,13 @@ def calibrationd_thread(sm=None, pm=None):
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send_counter += 1
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if sm.updated['cameraOdometry']:
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new_vp = calibrator.handle_cam_odom(sm['cameraOdometry'].trans,
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new_rpy = calibrator.handle_cam_odom(sm['cameraOdometry'].trans,
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sm['cameraOdometry'].rot,
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sm['cameraOdometry'].transStd,
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sm['cameraOdometry'].rotStd)
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if DEBUG and new_vp is not None:
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print('got new vp', new_vp)
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if DEBUG and new_rpy is not None:
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print('got new rpy', new_rpy)
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def main(sm=None, pm=None):
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@ -1 +1 @@
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eac7f0ebb37c2a8a0cf70d3d25d32ecd160d6cac
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24d46601f18d23f18e5152ce649fd0e37e2159a9
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