Merge pull request #100 from icmma/cherrypick

Cherrypick

CONTRIBUTING.md

@@ -2,11 +2,11 @@
 
 Our software is open source so you can solve your own problems without needing help from others. And if you solve a problem and are so kind, you can upstream it for the rest of the world to use.
 
-Most open source development activity is coordinated through our [slack](https://slack.comma.ai). A lot of documentation is available on our [medium](https://medium.com/@comma_ai/)
+Most open source development activity is coordinated through our [Discord](https://discord.comma.ai). A lot of documentation is available on our [medium](https://medium.com/@comma_ai/)
 
 ## Getting Started
 
- * Join our slack [slack.comma.ai](https://slack.comma.ai)
+ * Join our [Discord](https://discord.comma.ai)
  * Make sure you have a [GitHub account](https://github.com/signup/free)
  * Fork [our repositories](https://github.com/commaai) on GitHub
 

Dockerfile.openpilot

@@ -1,7 +1,26 @@
 FROM ubuntu:16.04
 ENV PYTHONUNBUFFERED 1
 
-RUN apt-get update && apt-get install -y build-essential clang vim screen wget bzip2 git libglib2.0-0 python-pip capnproto libcapnp-dev libzmq5-dev libffi-dev libusb-1.0-0
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    clang \
+    vim \
+    screen \
+    wget \
+    bzip2 \
+    git \
+    libglib2.0-0 \
+    python-pip \
+    capnproto \
+    libcapnp-dev \
+    libzmq5-dev \
+    libffi-dev \
+    libusb-1.0-0 \
+    libssl-dev \
+    ocl-icd-libopencl1 \
+    ocl-icd-opencl-dev \
+    opencl-headers
+
 RUN pip install numpy==1.11.2 scipy==0.18.1 matplotlib==2.1.2
 
 COPY requirements_openpilot.txt /tmp/

RELEASES.md

@@ -1,3 +1,23 @@
+Version 0.5.8 (2019-01-17)
+========================
+ * Open sourced visiond
+ * Auto-slowdown for upcoming turns
+ * Chrysler/Jeep/Fiat support thanks to adhintz!
+ * Honda Civic 2019 support thanks to csouers!
+ * Improved use of car display in Toyota thanks to arne182!
+ * No data upload when connected to Android or iOS hotspots and "Enable Upload Over Cellular" setting is off
+ * EON stops charging when 12V battery drops below 11.8V
+
+Version 0.5.7 (2018-12-06)
+========================
+ * Speed limit from OpenStreetMap added to UI
+ * Highlight speed limit when speed exceeds road speed limit plus a delta
+ * Option to limit openpilot max speed to road speed limit plus a delta
+ * Cadillac ATS support thanks to vntarasov!
+ * GMC Acadia support thanks to CryptoKylan!
+ * Decrease GPU power consumption
+ * NEOSv8 autoupdate
+
 Version 0.5.6 (2018-11-16)
 ========================
  * Refresh settings layout and add feature descriptions
@@ -7,6 +27,7 @@ Version 0.5.6 (2018-11-16)
  * More tuning to Honda positive accelerations
  * Reduce brake pump use on Hondas
  * Chevrolet Malibu support thanks to tylergets!
+ * Holden Astra support thanks to AlexHill!
 
 Version 0.5.5 (2018-10-20)
 ========================

cereal/Makefile

@@ -6,13 +6,16 @@ GENS := gen/cpp/car.capnp.c++ gen/cpp/log.capnp.c++
 JS := gen/js/car.capnp.js gen/js/log.capnp.js
 
 UNAME_M ?= $(shell uname -m)
-
 # only generate C++ for docker tests
 ifneq ($(OPTEST),1)
 	GENS += gen/c/car.capnp.c gen/c/log.capnp.c gen/c/include/c++.capnp.h gen/c/include/java.capnp.h
 
 	ifeq ($(UNAME_M),x86_64)
-		GENS += gen/java/Car.java gen/java/Log.java
+		ifneq (, $(shell which capnpc-java))
+			GENS += gen/java/Car.java gen/java/Log.java
+    else
+      $(warning capnpc-java not found, skipping java build)
+		endif
 	endif
 
 endif

cereal/car.capnp

@@ -244,6 +244,8 @@ struct CarControl {
     leadVisible @3: Bool;
     visualAlert @4: VisualAlert;
     audibleAlert @5: AudibleAlert;
+    rightLaneVisible @6: Bool;
+    leftLaneVisible @7: Bool;
 
     enum VisualAlert {
       # these are the choices from the Honda
@@ -355,6 +357,7 @@ struct CarParams {
   radarOffCan @47 :Bool; # True when radar objects aren't visible on CAN
 
   steerActuatorDelay @48 :Float32; # Steering wheel actuator delay in seconds
+  openpilotLongitudinalControl @50 :Bool; # is openpilot doing the longitudinal control?
 
   enum SteerControlType {
     torque @0;

cereal/log.capnp

@@ -187,10 +187,10 @@ struct SensorEventData {
     iOS @1;
     fiber @2;
     velodyne @3;  # Velodyne IMU
-    # c3 sensors below
-    bno055 @4;
-    lsm6ds3 @5;
-    bmp280 @6;
+    bno055 @4;    # Bosch accelerometer
+    lsm6ds3 @5;   # accelerometer (c2)
+    bmp280 @6;    # barometer (c2)
+    mmc3416x @7;  # magnetometer (c2)
   }
 }
 
@@ -276,7 +276,8 @@ struct ThermalData {
   startedTs @13 :UInt64;
 
   thermalStatus @14 :ThermalStatus;
-  chargerDisabled @17 :Bool;
+  chargingError @17 :Bool;
+  chargingDisabled @18 :Bool;
 
   enum ThermalStatus {
     green @0;   # all processes run
@@ -344,6 +345,7 @@ struct LiveCalibrationData {
   warpMatrix @0 :List(Float32);
   # camera_frame_from_model_frame
   warpMatrix2 @5 :List(Float32);
+  warpMatrixBig @6 :List(Float32);
   calStatus @1 :Int8;
   calCycle @2 :Int32;
   calPerc @3 :Int8;
@@ -397,6 +399,8 @@ struct Live100Data {
   curvature @37 :Float32;       # path curvature from vehicle model
   hudLeadDEPRECATED @14 :Int32;
   cumLagMs @15 :Float32;
+  startMonoTime @48 :UInt64;
+  mapValid @49 :Bool;
 
   enabled @19 :Bool;
   active @36 :Bool;
@@ -418,6 +422,10 @@ struct Live100Data {
   engageable @41 :Bool;  # can OP be engaged?
   driverMonitoringOn @43 :Bool;
 
+  # maps
+  vCurvature @46 :Float32;
+  decelForTurn @47 :Bool;
+
   enum ControlState {
     disabled @0;
     preEnabled @1;
@@ -554,6 +562,8 @@ struct Plan {
   aTarget @18 :Float32;
   jerkFactor @6 :Float32;
   hasLead @7 :Bool;
+  hasLeftLane @23 :Bool;
+  hasRightLane @24 :Bool;
   fcw @8 :Bool;
   longitudinalPlanSource @15 :LongitudinalPlanSource;
 
@@ -562,6 +572,11 @@ struct Plan {
 
   gpsPlannerActive @19 :Bool;
 
+  # maps
+  vCurvature @21 :Float32;
+  decelForTurn @22 :Bool;
+  mapValid @25 :Bool;
+
   struct GpsTrajectory {
     x @0 :List(Float32);
     y @1 :List(Float32);
@@ -1567,10 +1582,26 @@ struct LiveParametersData {
 }
 
 struct LiveMapData {
-  valid @0 :Bool;
+  speedLimitValid @0 :Bool;
   speedLimit @1 :Float32;
+  curvatureValid @2 :Bool;
+  curvature @3 :Float32;
+  wayId @4 :UInt64;
+  roadX @5 :List(Float32);
+  roadY @6 :List(Float32);
+  lastGps @7: GpsLocationData;
+  roadCurvatureX @8 :List(Float32);
+  roadCurvature @9 :List(Float32);
+  distToTurn @10 :Float32;
+  mapValid @11 :Bool;
 }
 
+struct CameraOdometry {
+  trans @0 :List(Float32); # m/s in device frame
+  rot @1 :List(Float32); # rad/s in device frame
+  transStd @2 :List(Float32); # std m/s in device frame
+  rotStd @3 :List(Float32); # std rad/s in device frame
+}
 
 struct Event {
   # in nanoseconds?
@@ -1639,5 +1670,6 @@ struct Event {
     boot @60 :Boot;
     liveParameters @61 :LiveParametersData;
     liveMapData @62 :LiveMapData;
+    cameraOdometry @63 :CameraOdometry;
   }
 }

common/params.py

@@ -63,6 +63,7 @@ class UnknownKeyName(Exception):
   "IsUploadVideoOverCellularEnabled": TxType.PERSISTENT,
   "IsDriverMonitoringEnabled": TxType.PERSISTENT,
   "IsGeofenceEnabled": TxType.PERSISTENT,
+  "SpeedLimitOffset": TxType.PERSISTENT,
 # written: visiond
 # read:    visiond, controlsd
   "CalibrationParams": TxType.PERSISTENT,
@@ -74,6 +75,8 @@ class UnknownKeyName(Exception):
   "DoUninstall": TxType.CLEAR_ON_MANAGER_START,
   "ShouldDoUpdate": TxType.CLEAR_ON_MANAGER_START,
   "IsUpdateAvailable": TxType.PERSISTENT,
+  "LongitudinalControl": TxType.PERSISTENT,
+  "LimitSetSpeed": TxType.PERSISTENT,
 
   "RecordFront": TxType.PERSISTENT,
 }

common/transformations/camera.py

@@ -1,5 +1,6 @@
 import numpy as np
 import common.transformations.orientation as orient
+import cv2
 
 FULL_FRAME_SIZE = (1164, 874)
 W, H = FULL_FRAME_SIZE[0], FULL_FRAME_SIZE[1]
@@ -62,31 +63,35 @@ def roll_from_ke(m):
   return np.arctan2(-(m[1, 0] - m[1, 1] * m[2, 0] / m[2, 1]),
                     -(m[0, 0] - m[0, 1] * m[2, 0] / m[2, 1]))
 
-def normalize(img_pts):
+
+def normalize(img_pts, intrinsics=eon_intrinsics):
   # normalizes image coordinates
   # accepts single pt or array of pts
+  intrinsics_inv = np.linalg.inv(intrinsics)
   img_pts = np.array(img_pts)
   input_shape = img_pts.shape
   img_pts = np.atleast_2d(img_pts)
   img_pts = np.hstack((img_pts, np.ones((img_pts.shape[0],1))))
-  img_pts_normalized = eon_intrinsics_inv.dot(img_pts.T).T
+  img_pts_normalized = intrinsics_inv.dot(img_pts.T).T
   img_pts_normalized[(img_pts < 0).any(axis=1)] = np.nan
   return img_pts_normalized[:,:2].reshape(input_shape)
 
-def denormalize(img_pts):
+
+def denormalize(img_pts, intrinsics=eon_intrinsics):
   # denormalizes image coordinates
   # accepts single pt or array of pts
   img_pts = np.array(img_pts)
   input_shape = img_pts.shape
   img_pts = np.atleast_2d(img_pts)
   img_pts = np.hstack((img_pts, np.ones((img_pts.shape[0],1))))
-  img_pts_denormalized = eon_intrinsics.dot(img_pts.T).T
+  img_pts_denormalized = intrinsics.dot(img_pts.T).T
   img_pts_denormalized[img_pts_denormalized[:,0] > W] = np.nan
   img_pts_denormalized[img_pts_denormalized[:,0] < 0] = np.nan
   img_pts_denormalized[img_pts_denormalized[:,1] > H] = np.nan
   img_pts_denormalized[img_pts_denormalized[:,1] < 0] = np.nan
   return img_pts_denormalized[:,:2].reshape(input_shape)
 
+
 def device_from_ecef(pos_ecef, orientation_ecef, pt_ecef):
   # device from ecef frame
   # device frame is x -> forward, y-> right, z -> down
@@ -99,6 +104,7 @@ def device_from_ecef(pos_ecef, orientation_ecef, pt_ecef):
   pt_device = np.einsum('jk,ik->ij', device_from_ecef_rot, pt_ecef_rel)
   return pt_device.reshape(input_shape)
 
+
 def img_from_device(pt_device):
   # img coordinates from pts in device frame
   # first transforms to view frame, then to img coords
@@ -113,3 +119,30 @@ def img_from_device(pt_device):
   pt_img = pt_view/pt_view[:,2:3]
   return pt_img.reshape(input_shape)[:,:2]
 
+
+def rotate_img(img, eulers, crop=None, intrinsics=eon_intrinsics):
+  size = img.shape[:2]
+  rot = orient.rot_from_euler(eulers)
+  quadrangle = np.array([[0, 0],
+                         [size[1]-1, 0],
+                         [0, size[0]-1],
+                         [size[1]-1, size[0]-1]], dtype=np.float32)
+  quadrangle_norm = np.hstack((normalize(quadrangle, intrinsics=intrinsics), np.ones((4,1))))
+  warped_quadrangle_full = np.einsum('ij, kj->ki', intrinsics.dot(rot), quadrangle_norm)
+  warped_quadrangle = np.column_stack((warped_quadrangle_full[:,0]/warped_quadrangle_full[:,2],
+                                       warped_quadrangle_full[:,1]/warped_quadrangle_full[:,2])).astype(np.float32)
+  if crop:
+    W_border = (size[1] - crop[0])/2
+    H_border = (size[0] - crop[1])/2
+    outside_crop = (((warped_quadrangle[:,0] < W_border) |
+                     (warped_quadrangle[:,0] >= size[1] - W_border)) &
+                    ((warped_quadrangle[:,1] < H_border) |
+                     (warped_quadrangle[:,1] >= size[0] - H_border)))
+    if not outside_crop.all():
+      raise ValueError("warped image not contained inside crop")
+  else:
+    H_border, W_border = 0, 0
+  M = cv2.getPerspectiveTransform(quadrangle, warped_quadrangle)
+  img_warped = cv2.warpPerspective(img, M, size[::-1])
+  return img_warped[H_border: size[0] - H_border,
+                    W_border: size[1] - W_border]

common/transformations/model.py

@@ -83,7 +83,7 @@ def get_model_height_transform(camera_frame_from_road_frame, height):
 
 # camera_frame_from_model_frame aka 'warp matrix'
 # was: calibration.h/CalibrationTransform
-def get_camera_frame_from_model_frame(camera_frame_from_road_frame, height):
+def get_camera_frame_from_model_frame(camera_frame_from_road_frame, height=model_height):
   vp = vp_from_ke(camera_frame_from_road_frame)
 
   model_camera_from_model_frame = np.array([

common/transformations/orientation.py

@@ -221,6 +221,8 @@ def ned_euler_from_ecef(ned_ecef_init, ecef_poses):
   ecef_poses = array(ecef_poses)
   output_shape = ecef_poses.shape
   ned_ecef_init = np.atleast_2d(ned_ecef_init)
+  if ned_ecef_init.shape[0] == 1:
+    ned_ecef_init = np.tile(ned_ecef_init[0], (output_shape[0], 1))
   ecef_poses = np.atleast_2d(ecef_poses)
 
   ned_poses = np.zeros(ecef_poses.shape)