diff --git a/.vscode/launch.json b/.vscode/launch.json
index f090061c42..151b757dab 100644
--- a/.vscode/launch.json
+++ b/.vscode/launch.json
@@ -52,6 +52,9 @@
       "type": "lldb",
       "request": "attach",
       "pid": "${command:pickMyProcess}",
+      "sourceMap": {
+        ".": "${workspaceFolder}/opendbc/safety"
+      },
       "initCommands": [
         "script import time; time.sleep(3)"
       ]
diff --git a/RELEASES.md b/RELEASES.md
index a3a95ae6a8..55141710d0 100644
--- a/RELEASES.md
+++ b/RELEASES.md
@@ -1,7 +1,8 @@
-Version 0.11.1 (2026-04-08)
+Version 0.11.1 (2026-04-22)
 ========================
 * New driver monitoring model
 * Improved image processing pipeline for driver camera
+* Rivian R1S and R1T 2025 support thanks to lukasloetkolben!
 
 Version 0.11.0 (2026-03-17)
 ========================
diff --git a/cereal/log.capnp b/cereal/log.capnp
index d8e9f56316..7e47ab171d 100644
--- a/cereal/log.capnp
+++ b/cereal/log.capnp
@@ -613,6 +613,11 @@ struct PandaState @0xa7649e2575e4591e {
   voltage @0 :UInt32;
   current @1 :UInt32;
 
+  # these fields are not used by openpilot, but they're
+  # reserved for forks building alternate experiences.
+  controlsAllowedRESERVED1 @38 :Bool;
+  controlsAllowedRESERVED2 @39 :Bool;
+
   enum FaultStatus {
     none @0;
     faultTemp @1;
@@ -2176,12 +2181,14 @@ struct DriverStateV2 {
     facePosition @2 :List(Float32);
     facePositionStd @3 :List(Float32);
     faceProb @4 :Float32;
-    leftEyeProb @5 :Float32;
-    rightEyeProb @6 :Float32;
-    leftBlinkProb @7 :Float32;
-    rightBlinkProb @8 :Float32;
-    sunglassesProb @9 :Float32;
+    eyesVisibleProb @14 :Float32;
+    eyesClosedProb @15 :Float32;
     phoneProb @13 :Float32;
+    leftEyeProbDEPRECATED @5 :Float32;
+    rightEyeProbDEPRECATED @6 :Float32;
+    leftBlinkProbDEPRECATED @7 :Float32;
+    rightBlinkProbDEPRECATED @8 :Float32;
+    sunglassesProbDEPRECATED @9 :Float32;
     notReadyProbDEPRECATED @12 :List(Float32);
     occludedProbDEPRECATED @10 :Float32;
     readyProbDEPRECATED @11 :List(Float32);
diff --git a/opendbc_repo b/opendbc_repo
index d0c76cb17e..c59bdd3f33 160000
--- a/opendbc_repo
+++ b/opendbc_repo
@@ -1 +1 @@
-Subproject commit d0c76cb17e8e141d1bbae41480b03b2c8f64fe26
+Subproject commit c59bdd3f33fff239054c33e32abaa0b73cc73799
diff --git a/scripts/reporter.py b/scripts/reporter.py
index d894b8af48..64f6cb99b8 100755
--- a/scripts/reporter.py
+++ b/scripts/reporter.py
@@ -38,6 +38,11 @@ if __name__ == "__main__":
       continue
 
     fn = os.path.basename(f)
-    master = get_checkpoint(MASTER_PATH + MODEL_PATH + fn)
+    master_path = MASTER_PATH + MODEL_PATH + fn
+    if os.path.exists(master_path):
+      master = get_checkpoint(master_path)
+      master_col = f"[{master}](https://reporter.comma.life/experiment/{master})"
+    else:
+      master_col = "N/A (new model)"
     pr = get_checkpoint(BASEDIR + MODEL_PATH + fn)
-    print("|", fn, "|", f"[{master}](https://reporter.comma.life/experiment/{master})", "|", f"[{pr}](https://reporter.comma.life/experiment/{pr})", "|")
+    print("|", fn, "|", master_col, "|", f"[{pr}](https://reporter.comma.life/experiment/{pr})", "|")
diff --git a/selfdrive/assets/icons_mici/onroad/glasses.png b/selfdrive/assets/icons_mici/onroad/glasses.png
deleted file mode 100644
index 006972fd39..0000000000
--- a/selfdrive/assets/icons_mici/onroad/glasses.png
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:56de402482b5987ed9a0ff3f793a1c89f857304b34fbb8a3deb5b5d4a332be1c
-size 3688
diff --git a/selfdrive/modeld/SConscript b/selfdrive/modeld/SConscript
index 3f38324a6e..bad1cdd500 100644
--- a/selfdrive/modeld/SConscript
+++ b/selfdrive/modeld/SConscript
@@ -18,10 +18,10 @@ def estimate_pickle_max_size(onnx_size):
 tg_flags = {
     'larch64': 'DEV=QCOM FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0',
     'Darwin': f'DEV=CPU THREADS=0 HOME={os.path.expanduser("~")}', # tinygrad calls brew which needs a $HOME in the env
-}.get(arch, 'DEV=CPU CPU_LLVM=1 THREADS=0')
+}.get(arch, 'DEV=CPU:LLVM THREADS=0')
 
 # Get model metadata
-for model_name in ['driving_vision', 'driving_policy', 'dmonitoring_model']:
+for model_name in ['driving_vision', 'driving_off_policy', 'driving_on_policy', 'dmonitoring_model']:
   fn = File(f"models/{model_name}").abspath
   script_files = [File(Dir("#selfdrive/modeld").File("get_model_metadata.py").abspath)]
   cmd = f'{tg_flags} python3 {Dir("#selfdrive/modeld").abspath}/get_model_metadata.py {fn}.onnx'
@@ -59,19 +59,5 @@ def tg_compile(flags, model_name):
   )
 
 # Compile small models
-for model_name in ['driving_vision', 'driving_policy', 'dmonitoring_model']:
+for model_name in ['driving_vision', 'driving_off_policy', 'driving_on_policy', 'dmonitoring_model']:
   tg_compile(tg_flags, model_name)
-
-# Compile BIG model if USB GPU is available
-if "USBGPU" in os.environ:
-  import subprocess
-  # because tg doesn't support multi-process
-  devs = subprocess.check_output('python3 -c "from tinygrad import Device; print(list(Device.get_available_devices()))"', shell=True, cwd=env.Dir('#').abspath)
-  if b"AMD" in devs:
-    print("USB GPU detected... building")
-    flags = "DEV=AMD AMD_IFACE=USB AMD_LLVM=1 NOLOCALS=0 IMAGE=0"
-    bp = tg_compile(flags, "big_driving_policy")
-    bv = tg_compile(flags, "big_driving_vision")
-    lenv.SideEffect('lock', [bp, bv])  # tg doesn't support multi-process so build serially
-  else:
-    print("USB GPU not detected... skipping")
diff --git a/selfdrive/modeld/compile_warp.py b/selfdrive/modeld/compile_warp.py
index 75cc65f84c..47511f2a2b 100755
--- a/selfdrive/modeld/compile_warp.py
+++ b/selfdrive/modeld/compile_warp.py
@@ -94,11 +94,11 @@ def make_frame_prepare(cam_w, cam_h, model_w, model_h):
 
 
 def make_update_img_input(frame_prepare, model_w, model_h):
-  def update_img_input_tinygrad(tensor, frame, M_inv):
+  def update_img_input_tinygrad(frame_buffer, frame, M_inv):
     M_inv = M_inv.to(Device.DEFAULT)
     new_img = frame_prepare(frame, M_inv)
-    full_buffer = tensor[6:].cat(new_img, dim=0).contiguous()
-    return full_buffer, Tensor.cat(full_buffer[:6], full_buffer[-6:], dim=0).contiguous().reshape(1, 12, model_h//2, model_w//2)
+    frame_buffer.assign(frame_buffer[6:].cat(new_img, dim=0).contiguous())
+    return Tensor.cat(frame_buffer[:6], frame_buffer[-6:], dim=0).contiguous().reshape(1, 12, model_h//2, model_w//2)
   return update_img_input_tinygrad
 
 
@@ -107,9 +107,9 @@ def make_update_both_imgs(frame_prepare, model_w, model_h):
 
   def update_both_imgs_tinygrad(calib_img_buffer, new_img, M_inv,
                                 calib_big_img_buffer, new_big_img, M_inv_big):
-    calib_img_buffer, calib_img_pair = update_img(calib_img_buffer, new_img, M_inv)
-    calib_big_img_buffer, calib_big_img_pair = update_img(calib_big_img_buffer, new_big_img, M_inv_big)
-    return calib_img_buffer, calib_img_pair, calib_big_img_buffer, calib_big_img_pair
+    calib_img_pair = update_img(calib_img_buffer, new_img, M_inv)
+    calib_big_img_pair = update_img(calib_big_img_buffer, new_big_img, M_inv_big)
+    return calib_img_pair, calib_big_img_pair
   return update_both_imgs_tinygrad
 
 
@@ -136,29 +136,18 @@ def compile_modeld_warp(cam_w, cam_h):
 
   full_buffer = Tensor.zeros(IMG_BUFFER_SHAPE, dtype='uint8').contiguous().realize()
   big_full_buffer = Tensor.zeros(IMG_BUFFER_SHAPE, dtype='uint8').contiguous().realize()
-  full_buffer_np = np.zeros(IMG_BUFFER_SHAPE, dtype=np.uint8)
-  big_full_buffer_np = np.zeros(IMG_BUFFER_SHAPE, dtype=np.uint8)
-
   for i in range(10):
-    new_frame_np = (32 * np.random.randn(yuv_size).astype(np.float32) + 128).clip(0, 255).astype(np.uint8)
     img_inputs = [full_buffer,
-                  Tensor.from_blob(new_frame_np.ctypes.data, (yuv_size,), dtype='uint8').realize(),
+                  Tensor(np.random.randint(0, 256, yuv_size, dtype=np.uint8)).realize(),
                   Tensor(Tensor.randn(3, 3).mul(8).realize().numpy(), device='NPY')]
-    new_big_frame_np = (32 * np.random.randn(yuv_size).astype(np.float32) + 128).clip(0, 255).astype(np.uint8)
     big_img_inputs = [big_full_buffer,
-                      Tensor.from_blob(new_big_frame_np.ctypes.data, (yuv_size,), dtype='uint8').realize(),
+                      Tensor(np.random.randint(0, 256, yuv_size, dtype=np.uint8)).realize(),
                       Tensor(Tensor.randn(3, 3).mul(8).realize().numpy(), device='NPY')]
     inputs = img_inputs + big_img_inputs
     Device.default.synchronize()
 
-    inputs_np = [x.numpy() for x in inputs]
-    inputs_np[0] = full_buffer_np
-    inputs_np[3] = big_full_buffer_np
-
     st = time.perf_counter()
-    out = update_img_jit(*inputs)
-    full_buffer = out[0].contiguous().realize().clone()
-    big_full_buffer = out[2].contiguous().realize().clone()
+    _ = update_img_jit(*inputs)
     mt = time.perf_counter()
     Device.default.synchronize()
     et = time.perf_counter()
@@ -183,7 +172,7 @@ def compile_dm_warp(cam_w, cam_h):
   warp_dm_jit = TinyJit(warp_dm, prune=True)
 
   for i in range(10):
-    inputs = [Tensor.from_blob((32 * Tensor.randn(yuv_size,) + 128).cast(dtype='uint8').realize().numpy().ctypes.data, (yuv_size,), dtype='uint8'),
+    inputs = [Tensor(np.random.randint(0, 256, yuv_size, dtype=np.uint8)).realize(),
               Tensor(Tensor.randn(3, 3).mul(8).realize().numpy(), device='NPY')]
     Device.default.synchronize()
     st = time.perf_counter()
diff --git a/selfdrive/modeld/dmonitoringmodeld.py b/selfdrive/modeld/dmonitoringmodeld.py
index 28190db3e6..efd8214b9f 100755
--- a/selfdrive/modeld/dmonitoringmodeld.py
+++ b/selfdrive/modeld/dmonitoringmodeld.py
@@ -80,7 +80,7 @@ def parse_model_output(model_output):
     face_descs = model_output[f'face_descs_{ds_suffix}']
     parsed[f'face_descs_{ds_suffix}'] = face_descs[:, :-6]
     parsed[f'face_descs_{ds_suffix}_std'] = safe_exp(face_descs[:, -6:])
-    for key in ['face_prob', 'left_eye_prob', 'right_eye_prob','left_blink_prob', 'right_blink_prob', 'sunglasses_prob', 'using_phone_prob']:
+    for key in ['face_prob', 'eyes_visible_prob', 'eyes_closed_prob', 'using_phone_prob']:
       parsed[f'{key}_{ds_suffix}'] = sigmoid(model_output[f'{key}_{ds_suffix}'])
   return parsed
 
@@ -90,11 +90,8 @@ def fill_driver_data(msg, model_output, ds_suffix):
   msg.facePosition = model_output[f'face_descs_{ds_suffix}'][0, 3:5].tolist()
   msg.facePositionStd = model_output[f'face_descs_{ds_suffix}_std'][0, 3:5].tolist()
   msg.faceProb = model_output[f'face_prob_{ds_suffix}'][0, 0].item()
-  msg.leftEyeProb = model_output[f'left_eye_prob_{ds_suffix}'][0, 0].item()
-  msg.rightEyeProb = model_output[f'right_eye_prob_{ds_suffix}'][0, 0].item()
-  msg.leftBlinkProb = model_output[f'left_blink_prob_{ds_suffix}'][0, 0].item()
-  msg.rightBlinkProb = model_output[f'right_blink_prob_{ds_suffix}'][0, 0].item()
-  msg.sunglassesProb = model_output[f'sunglasses_prob_{ds_suffix}'][0, 0].item()
+  msg.eyesVisibleProb = model_output[f'eyes_visible_prob_{ds_suffix}'][0, 0].item()
+  msg.eyesClosedProb = model_output[f'eyes_closed_prob_{ds_suffix}'][0, 0].item()
   msg.phoneProb = model_output[f'using_phone_prob_{ds_suffix}'][0, 0].item()
 
 def get_driverstate_packet(model_output, frame_id: int, location_ts: int, exec_time: float, gpu_exec_time: float):
diff --git a/selfdrive/modeld/modeld.py b/selfdrive/modeld/modeld.py
index bff59366d6..82e750cf8b 100755
--- a/selfdrive/modeld/modeld.py
+++ b/selfdrive/modeld/modeld.py
@@ -34,11 +34,13 @@ from openpilot.selfdrive.modeld.constants import ModelConstants, Plan
 PROCESS_NAME = "selfdrive.modeld.modeld"
 SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
 
-VISION_PKL_PATH = Path(__file__).parent / 'models/driving_vision_tinygrad.pkl'
-POLICY_PKL_PATH = Path(__file__).parent / 'models/driving_policy_tinygrad.pkl'
-VISION_METADATA_PATH = Path(__file__).parent / 'models/driving_vision_metadata.pkl'
-POLICY_METADATA_PATH = Path(__file__).parent / 'models/driving_policy_metadata.pkl'
 MODELS_DIR = Path(__file__).parent / 'models'
+VISION_PKL_PATH = MODELS_DIR / 'driving_vision_tinygrad.pkl'
+VISION_METADATA_PATH = MODELS_DIR / 'driving_vision_metadata.pkl'
+ON_POLICY_PKL_PATH = MODELS_DIR / 'driving_on_policy_tinygrad.pkl'
+ON_POLICY_METADATA_PATH = MODELS_DIR / 'driving_on_policy_metadata.pkl'
+OFF_POLICY_PKL_PATH = MODELS_DIR / 'driving_off_policy_tinygrad.pkl'
+OFF_POLICY_METADATA_PATH = MODELS_DIR / 'driving_off_policy_metadata.pkl'
 
 LAT_SMOOTH_SECONDS = 0.0
 LONG_SMOOTH_SECONDS = 0.3
@@ -151,7 +153,13 @@ class ModelState:
       self.vision_output_slices = vision_metadata['output_slices']
       vision_output_size = vision_metadata['output_shapes']['outputs'][1]
 
-    with open(POLICY_METADATA_PATH, 'rb') as f:
+    with open(OFF_POLICY_METADATA_PATH, 'rb') as f:
+      off_policy_metadata = pickle.load(f)
+      self.off_policy_input_shapes =  off_policy_metadata['input_shapes']
+      self.off_policy_output_slices = off_policy_metadata['output_slices']
+      off_policy_output_size = off_policy_metadata['output_shapes']['outputs'][1]
+
+    with open(ON_POLICY_METADATA_PATH, 'rb') as f:
       policy_metadata = pickle.load(f)
       self.policy_input_shapes =  policy_metadata['input_shapes']
       self.policy_output_slices = policy_metadata['output_slices']
@@ -175,11 +183,13 @@ class ModelState:
     self.vision_output = np.zeros(vision_output_size, dtype=np.float32)
     self.policy_inputs = {k: Tensor(v, device='NPY').realize() for k,v in self.numpy_inputs.items()}
     self.policy_output = np.zeros(policy_output_size, dtype=np.float32)
+    self.off_policy_output = np.zeros(off_policy_output_size, dtype=np.float32)
     self.parser = Parser()
     self.frame_buf_params : dict[str, tuple[int, int, int, int]] = {}
     self.update_imgs = None
     self.vision_run = pickle.loads(read_file_chunked(str(VISION_PKL_PATH)))
-    self.policy_run = pickle.loads(read_file_chunked(str(POLICY_PKL_PATH)))
+    self.policy_run = pickle.loads(read_file_chunked(str(ON_POLICY_PKL_PATH)))
+    self.off_policy_run = pickle.loads(read_file_chunked(str(OFF_POLICY_PKL_PATH)))
 
   def slice_outputs(self, model_outputs: np.ndarray, output_slices: dict[str, slice]) -> dict[str, np.ndarray]:
     parsed_model_outputs = {k: model_outputs[np.newaxis, v] for k,v in output_slices.items()}
@@ -212,8 +222,7 @@ class ModelState:
 
     out = self.update_imgs(self.img_queues['img'], self.full_frames['img'], self.transforms['img'],
                            self.img_queues['big_img'], self.full_frames['big_img'], self.transforms['big_img'])
-    self.img_queues['img'], self.img_queues['big_img'] = out[0].realize(), out[2].realize()
-    vision_inputs = {'img': out[1], 'big_img': out[3]}
+    vision_inputs = {'img': out[0], 'big_img': out[1]}
 
     if prepare_only:
       return None
@@ -228,9 +237,17 @@ class ModelState:
 
     self.policy_output = self.policy_run(**self.policy_inputs).contiguous().realize().uop.base.buffer.numpy().flatten()
     policy_outputs_dict = self.parser.parse_policy_outputs(self.slice_outputs(self.policy_output, self.policy_output_slices))
-    combined_outputs_dict = {**vision_outputs_dict, **policy_outputs_dict}
+
+    self.off_policy_output = self.off_policy_run(**self.policy_inputs).contiguous().realize().uop.base.buffer.numpy()
+    off_policy_outputs_dict = self.parser.parse_off_policy_outputs(self.slice_outputs(self.off_policy_output, self.off_policy_output_slices))
+    off_policy_outputs_dict.pop('plan')
+
+
+    combined_outputs_dict = {**vision_outputs_dict, **off_policy_outputs_dict, **policy_outputs_dict}
+    if 'planplus' in combined_outputs_dict and 'plan' in combined_outputs_dict:
+      combined_outputs_dict['plan'] = combined_outputs_dict['plan'] + combined_outputs_dict['planplus']
     if SEND_RAW_PRED:
-      combined_outputs_dict['raw_pred'] = np.concatenate([self.vision_output.copy(), self.policy_output.copy()])
+      combined_outputs_dict['raw_pred'] = np.concatenate([self.vision_output.copy(), self.policy_output.copy(), self.off_policy_output.copy()])
 
     return combined_outputs_dict
 
@@ -388,7 +405,9 @@ def main(demo=False):
       drivingdata_send = messaging.new_message('drivingModelData')
       posenet_send = messaging.new_message('cameraOdometry')
 
-      action = get_action_from_model(model_output, prev_action, lat_delay + DT_MDL, long_delay + DT_MDL, v_ego)
+      frame_delay = DT_MDL # compensate for time passed since the frame was captured: current_time - timestamp_eof is 50ms on average
+      action_delay = DT_MDL / 2 # middle of the interval between model output (current state) and next frame (expected state)
+      action = get_action_from_model(model_output, prev_action, lat_delay + frame_delay + action_delay, long_delay + frame_delay + action_delay, v_ego)
       prev_action = action
       fill_model_msg(drivingdata_send, modelv2_send, model_output, action,
                      publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id,
diff --git a/selfdrive/modeld/models/big_driving_policy.onnx b/selfdrive/modeld/models/big_driving_policy.onnx
deleted file mode 120000
index e1b653a14a..0000000000
--- a/selfdrive/modeld/models/big_driving_policy.onnx
+++ /dev/null
@@ -1 +0,0 @@
-driving_policy.onnx
\ No newline at end of file
diff --git a/selfdrive/modeld/models/big_driving_vision.onnx b/selfdrive/modeld/models/big_driving_vision.onnx
deleted file mode 120000
index 28ee71dd74..0000000000
--- a/selfdrive/modeld/models/big_driving_vision.onnx
+++ /dev/null
@@ -1 +0,0 @@
-driving_vision.onnx
\ No newline at end of file
diff --git a/selfdrive/modeld/models/dmonitoring_model.onnx b/selfdrive/modeld/models/dmonitoring_model.onnx
index dc621bed03..628f385796 100644
--- a/selfdrive/modeld/models/dmonitoring_model.onnx
+++ b/selfdrive/modeld/models/dmonitoring_model.onnx
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7aff7ff1dc08bbaf562a8f77380ab5e5914f8557dba2f760d87e4d953f5604b0
-size 7307246
+oid sha256:2fd471febb6e973313ac0d0c6755f6410c1937ba92230b58a433761e8c883072
+size 7364290
diff --git a/selfdrive/modeld/models/driving_off_policy.onnx b/selfdrive/modeld/models/driving_off_policy.onnx
new file mode 100644
index 0000000000..5b0effc100
--- /dev/null
+++ b/selfdrive/modeld/models/driving_off_policy.onnx
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e53f4e0527766082ba7bde38e275def0fe3c14f6c59ae2854439e239884d3ecc
+size 13393365
diff --git a/selfdrive/modeld/models/driving_on_policy.onnx b/selfdrive/modeld/models/driving_on_policy.onnx
new file mode 100644
index 0000000000..bfe10ca185
--- /dev/null
+++ b/selfdrive/modeld/models/driving_on_policy.onnx
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ea89c50da3a16e710da292f97c81b083a982cfdee5c28eca0d37ed2fb99af6c5
+size 13022642
diff --git a/selfdrive/modeld/models/driving_policy.onnx b/selfdrive/modeld/models/driving_policy.onnx
deleted file mode 100644
index 7c71bc9471..0000000000
--- a/selfdrive/modeld/models/driving_policy.onnx
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:853c6634746ff439a848349d00e4d5581cd941f13f7c1862c31b72a31cc24858
-size 14061595
diff --git a/selfdrive/modeld/models/driving_vision.onnx b/selfdrive/modeld/models/driving_vision.onnx
index afd617667c..335e9dbcf8 100644
--- a/selfdrive/modeld/models/driving_vision.onnx
+++ b/selfdrive/modeld/models/driving_vision.onnx
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:940e9006a25f27f0b6e85da798e6a8fd1f6dd492dd7d0b9ff1a9436460f46129
-size 46887794
+oid sha256:6263aa3fbb44cde6c68a34cdb7cd8c389789dbc02b15c1911afdac4e018281ae
+size 23267151
diff --git a/selfdrive/modeld/parse_model_outputs.py b/selfdrive/modeld/parse_model_outputs.py
index 5c11e8ca18..802f0ad859 100644
--- a/selfdrive/modeld/parse_model_outputs.py
+++ b/selfdrive/modeld/parse_model_outputs.py
@@ -96,11 +96,17 @@ class Parser:
     self.parse_mdn('pose', outs, in_N=0, out_N=0, out_shape=(ModelConstants.POSE_WIDTH,))
     self.parse_mdn('wide_from_device_euler', outs, in_N=0, out_N=0, out_shape=(ModelConstants.WIDE_FROM_DEVICE_WIDTH,))
     self.parse_mdn('road_transform', outs, in_N=0, out_N=0, out_shape=(ModelConstants.POSE_WIDTH,))
+    self.parse_categorical_crossentropy('desire_pred', outs, out_shape=(ModelConstants.DESIRE_PRED_LEN,ModelConstants.DESIRE_PRED_WIDTH))
+    self.parse_binary_crossentropy('meta', outs)
+    return outs
+
+  def parse_off_policy_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
+    plan_mhp = self.is_mhp(outs, 'plan',  ModelConstants.IDX_N * ModelConstants.PLAN_WIDTH)
+    plan_in_N, plan_out_N = (ModelConstants.PLAN_MHP_N, ModelConstants.PLAN_MHP_SELECTION) if plan_mhp else (0, 0)
+    self.parse_mdn('plan', outs, in_N=plan_in_N, out_N=plan_out_N, out_shape=(ModelConstants.IDX_N, ModelConstants.PLAN_WIDTH))
     self.parse_mdn('lane_lines', outs, in_N=0, out_N=0, out_shape=(ModelConstants.NUM_LANE_LINES,ModelConstants.IDX_N,ModelConstants.LANE_LINES_WIDTH))
     self.parse_mdn('road_edges', outs, in_N=0, out_N=0, out_shape=(ModelConstants.NUM_ROAD_EDGES,ModelConstants.IDX_N,ModelConstants.LANE_LINES_WIDTH))
     self.parse_binary_crossentropy('lane_lines_prob', outs)
-    self.parse_categorical_crossentropy('desire_pred', outs, out_shape=(ModelConstants.DESIRE_PRED_LEN,ModelConstants.DESIRE_PRED_WIDTH))
-    self.parse_binary_crossentropy('meta', outs)
     self.parse_binary_crossentropy('lead_prob', outs)
     lead_mhp = self.is_mhp(outs, 'lead', ModelConstants.LEAD_MHP_SELECTION * ModelConstants.LEAD_TRAJ_LEN * ModelConstants.LEAD_WIDTH)
     lead_in_N, lead_out_N = (ModelConstants.LEAD_MHP_N, ModelConstants.LEAD_MHP_SELECTION) if lead_mhp else (0, 0)
@@ -120,5 +126,6 @@ class Parser:
 
   def parse_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
     outs = self.parse_vision_outputs(outs)
+    outs = self.parse_off_policy_outputs(outs)
     outs = self.parse_policy_outputs(outs)
     return outs
diff --git a/selfdrive/monitoring/helpers.py b/selfdrive/monitoring/helpers.py
index 0b54504b64..90cc565802 100644
--- a/selfdrive/monitoring/helpers.py
+++ b/selfdrive/monitoring/helpers.py
@@ -1,4 +1,4 @@
-from math import atan2
+from math import atan2, radians
 import numpy as np
 
 from cereal import car, log
@@ -32,9 +32,8 @@ class DRIVER_MONITOR_SETTINGS:
     self._DISTRACTED_PROMPT_TIME_TILL_TERMINAL = 6.
 
     self._FACE_THRESHOLD = 0.7
-    self._EYE_THRESHOLD = 0.65
-    self._SG_THRESHOLD = 0.9
-    self._BLINK_THRESHOLD = 0.865
+    self._EYE_THRESHOLD = 0.5
+    self._BLINK_THRESHOLD = 0.5
     self._PHONE_THRESH = 0.5
 
     self._POSE_PITCH_THRESHOLD = 0.3133
@@ -43,6 +42,9 @@ class DRIVER_MONITOR_SETTINGS:
     self._POSE_YAW_THRESHOLD = 0.4020
     self._POSE_YAW_THRESHOLD_SLACK = 0.5042
     self._POSE_YAW_THRESHOLD_STRICT = self._POSE_YAW_THRESHOLD
+    self._POSE_YAW_MIN_STEER_DEG = 30
+    self._POSE_YAW_STEER_FACTOR = 0.15
+    self._POSE_YAW_STEER_MAX_OFFSET = 0.3927
     self._PITCH_NATURAL_OFFSET = 0.011 # initial value before offset is learned
     self._PITCH_NATURAL_THRESHOLD = 0.449
     self._YAW_NATURAL_OFFSET = 0.075 # initial value before offset is learned
@@ -59,7 +61,6 @@ class DRIVER_MONITOR_SETTINGS:
     self._POSESTD_THRESHOLD = 0.3
     self._HI_STD_FALLBACK_TIME = int(10  / self._DT_DMON)  # fall back to wheel touch if model is uncertain for 10s
     self._DISTRACTED_FILTER_TS = 0.25  # 0.6Hz
-    self._ALWAYS_ON_ALERT_MIN_SPEED = 11
 
     self._POSE_CALIB_MIN_SPEED = 13  # 30 mph
     self._POSE_OFFSET_MIN_COUNT = int(60 / self._DT_DMON)  # valid data counts before calibration completes, 1min cumulative
@@ -101,6 +102,7 @@ class DriverPose:
     self.low_std = True
     self.cfactor_pitch = 1.
     self.cfactor_yaw = 1.
+    self.steer_yaw_offset = 0.
 
 class DriverProb:
   def __init__(self, raw_priors, max_trackable):
@@ -108,11 +110,6 @@ class DriverProb:
     self.prob_offseter = RunningStatFilter(raw_priors=raw_priors, max_trackable=max_trackable)
     self.prob_calibrated = False
 
-class DriverBlink:
-  def __init__(self):
-    self.left = 0.
-    self.right = 0.
-
 
 # model output refers to center of undistorted+leveled image
 EFL = 598.0 # focal length in K
@@ -147,7 +144,7 @@ class DriverMonitoring:
     wheelpos_filter_raw_priors = (self.settings._WHEELPOS_DATA_AVG, self.settings._WHEELPOS_DATA_VAR, 2)
     self.wheelpos = DriverProb(raw_priors=wheelpos_filter_raw_priors, max_trackable=self.settings._WHEELPOS_MAX_COUNT)
     self.pose = DriverPose(settings=self.settings)
-    self.blink = DriverBlink()
+    self.blink_prob = 0.
     self.phone_prob = 0.
 
     self.always_on = always_on
@@ -238,7 +235,11 @@ class DriverMonitoring:
       yaw_error = self.pose.yaw - min(max(self.pose.yaw_offseter.filtered_stat.mean(),
                                                     self.settings._YAW_MIN_OFFSET), self.settings._YAW_MAX_OFFSET)
     pitch_error = 0 if pitch_error > 0 else abs(pitch_error) # no positive pitch limit
-    yaw_error = abs(yaw_error)
+
+    if yaw_error * self.pose.steer_yaw_offset > 0: # unidirectional
+      yaw_error = max(abs(yaw_error) - min(abs(self.pose.steer_yaw_offset), self.settings._POSE_YAW_STEER_MAX_OFFSET), 0.)
+    else:
+      yaw_error = abs(yaw_error)
 
     pitch_threshold = self.settings._POSE_PITCH_THRESHOLD * self.pose.cfactor_pitch if self.pose.calibrated else self.settings._PITCH_NATURAL_THRESHOLD
     yaw_threshold = self.settings._POSE_YAW_THRESHOLD * self.pose.cfactor_yaw
@@ -246,7 +247,7 @@ class DriverMonitoring:
     if pitch_error > pitch_threshold or yaw_error > yaw_threshold:
       distracted_types.append(DistractedType.DISTRACTED_POSE)
 
-    if (self.blink.left + self.blink.right)*0.5 > self.settings._BLINK_THRESHOLD:
+    if self.blink_prob > self.settings._BLINK_THRESHOLD:
       distracted_types.append(DistractedType.DISTRACTED_BLINK)
 
     if self.phone_prob > self.settings._PHONE_THRESH:
@@ -254,7 +255,7 @@ class DriverMonitoring:
 
     return distracted_types
 
-  def _update_states(self, driver_state, cal_rpy, car_speed, op_engaged, standstill, demo_mode=False):
+  def _update_states(self, driver_state, cal_rpy, car_speed, op_engaged, standstill, demo_mode=False, steering_angle_deg=0.):
     rhd_pred = driver_state.wheelOnRightProb
     # calibrates only when there's movement and either face detected
     if car_speed > self.settings._WHEELPOS_CALIB_MIN_SPEED and (driver_state.leftDriverData.faceProb > self.settings._FACE_THRESHOLD or
@@ -277,17 +278,17 @@ class DriverMonitoring:
 
     self.face_detected = driver_data.faceProb > self.settings._FACE_THRESHOLD
     self.pose.roll, self.pose.pitch, self.pose.yaw = face_orientation_from_net(driver_data.faceOrientation, driver_data.facePosition, cal_rpy)
+    steer_d = max(abs(steering_angle_deg) - self.settings._POSE_YAW_MIN_STEER_DEG, 0.)
+    self.pose.steer_yaw_offset = radians(steer_d) * -np.sign(steering_angle_deg) * self.settings._POSE_YAW_STEER_FACTOR
     if self.wheel_on_right:
       self.pose.yaw *= -1
+      self.pose.steer_yaw_offset *= -1
     self.wheel_on_right_last = self.wheel_on_right
     self.pose.pitch_std = driver_data.faceOrientationStd[0]
     self.pose.yaw_std = driver_data.faceOrientationStd[1]
     model_std_max = max(self.pose.pitch_std, self.pose.yaw_std)
     self.pose.low_std = model_std_max < self.settings._POSESTD_THRESHOLD
-    self.blink.left = driver_data.leftBlinkProb * (driver_data.leftEyeProb > self.settings._EYE_THRESHOLD) \
-                      * (driver_data.sunglassesProb < self.settings._SG_THRESHOLD)
-    self.blink.right = driver_data.rightBlinkProb * (driver_data.rightEyeProb > self.settings._EYE_THRESHOLD) \
-                      * (driver_data.sunglassesProb < self.settings._SG_THRESHOLD)
+    self.blink_prob = driver_data.eyesClosedProb * (driver_data.eyesVisibleProb > self.settings._EYE_THRESHOLD)
     self.phone_prob = driver_data.phoneProb
 
     self.distracted_types = self._get_distracted_types()
@@ -360,19 +361,19 @@ class DriverMonitoring:
       if self.awareness > self.threshold_prompt:
         return
 
+    _reaching_pre = self.awareness - self.step_change <= self.threshold_pre
     _reaching_audible = self.awareness - self.step_change <= self.threshold_prompt
     _reaching_terminal = self.awareness - self.step_change <= 0
-    standstill_orange_exemption = standstill and _reaching_audible
+    standstill_exemption = standstill and _reaching_pre
     always_on_red_exemption = always_on_valid and not op_engaged and _reaching_terminal
-    always_on_lowspeed_exemption = always_on_valid and not op_engaged and car_speed < self.settings._ALWAYS_ON_ALERT_MIN_SPEED
 
     certainly_distracted = self.driver_distraction_filter.x > 0.63 and self.driver_distracted and self.face_detected
     maybe_distracted = self.hi_stds > self.settings._HI_STD_FALLBACK_TIME or not self.face_detected
 
     if certainly_distracted or maybe_distracted:
-      # should always be counting if distracted unless at standstill (lowspeed for always-on) and reaching orange
+      # should always be counting if distracted unless at standstill and reaching green
       # also will not be reaching 0 if DM is active when not engaged
-      if not (standstill_orange_exemption or always_on_red_exemption or (always_on_lowspeed_exemption and _reaching_audible)):
+      if not (standstill_exemption or always_on_red_exemption):
         self.awareness = max(self.awareness - self.step_change, -0.1)
 
     alert = None
@@ -385,7 +386,7 @@ class DriverMonitoring:
     elif self.awareness <= self.threshold_prompt:
       # prompt orange alert
       alert = EventName.promptDriverDistracted if self.active_monitoring_mode else EventName.promptDriverUnresponsive
-    elif self.awareness <= self.threshold_pre and not always_on_lowspeed_exemption:
+    elif self.awareness <= self.threshold_pre:
       # pre green alert
       alert = EventName.preDriverDistracted if self.active_monitoring_mode else EventName.preDriverUnresponsive
 
@@ -451,6 +452,7 @@ class DriverMonitoring:
       op_engaged=enabled,
       standstill=standstill,
       demo_mode=demo,
+      steering_angle_deg=sm['carState'].steeringAngleDeg,
     )
 
     # Update distraction events
diff --git a/selfdrive/monitoring/test_monitoring.py b/selfdrive/monitoring/test_monitoring.py
index 6ea9b80283..733ea85bc0 100644
--- a/selfdrive/monitoring/test_monitoring.py
+++ b/selfdrive/monitoring/test_monitoring.py
@@ -19,10 +19,8 @@ def make_msg(face_detected, distracted=False, model_uncertain=False):
   ds.leftDriverData.faceOrientation = [0., 0., 0.]
   ds.leftDriverData.facePosition = [0., 0.]
   ds.leftDriverData.faceProb = 1. * face_detected
-  ds.leftDriverData.leftEyeProb = 1.
-  ds.leftDriverData.rightEyeProb = 1.
-  ds.leftDriverData.leftBlinkProb = 1. * distracted
-  ds.leftDriverData.rightBlinkProb = 1. * distracted
+  ds.leftDriverData.eyesVisibleProb = 1.
+  ds.leftDriverData.eyesClosedProb = 1. * distracted
   ds.leftDriverData.faceOrientationStd = [1.*model_uncertain, 1.*model_uncertain, 1.*model_uncertain]
   ds.leftDriverData.facePositionStd = [1.*model_uncertain, 1.*model_uncertain]
   # TODO: test both separately when e2e is used
@@ -186,10 +184,10 @@ class TestMonitoring:
     standstill_vector = always_true[:]
     standstill_vector[int(_redlight_time/DT_DMON):] = [False] * int((TEST_TIMESPAN-_redlight_time)/DT_DMON)
     events, d_status = self._run_seq(always_distracted, always_false, always_true, standstill_vector)
-    assert events[int((d_status.settings._DISTRACTED_TIME-d_status.settings._DISTRACTED_PRE_TIME_TILL_TERMINAL+1)/DT_DMON)].names[0] == \
-                                                                                                                    EventName.preDriverDistracted
-    assert events[int((_redlight_time-0.1)/DT_DMON)].names[0] == EventName.preDriverDistracted
-    assert events[int((_redlight_time+0.5)/DT_DMON)].names[0] == EventName.promptDriverDistracted
+    assert len(events[int((_redlight_time-0.1)/DT_DMON)]) == 0
+    _pre_to_prompt = d_status.settings._DISTRACTED_PRE_TIME_TILL_TERMINAL - d_status.settings._DISTRACTED_PROMPT_TIME_TILL_TERMINAL
+    assert events[int((_redlight_time+0.5)/DT_DMON)].names[0] == EventName.preDriverDistracted
+    assert events[int((_redlight_time+_pre_to_prompt+0.5)/DT_DMON)].names[0] == EventName.promptDriverDistracted
 
   # engaged, model is somehow uncertain and driver is distracted
   #  - should fall back to wheel touch after uncertain alert
diff --git a/selfdrive/test/process_replay/model_replay.py b/selfdrive/test/process_replay/model_replay.py
index a6ccaa1047..eb7cdbe34a 100755
--- a/selfdrive/test/process_replay/model_replay.py
+++ b/selfdrive/test/process_replay/model_replay.py
@@ -76,7 +76,7 @@ def generate_report(proposed, master, tmp, commit):
                      (lambda x: get_idx_if_non_empty(x.wheelOnRightProb), "wheelOnRightProb"),
                      (lambda x: get_idx_if_non_empty(x.leftDriverData.faceProb), "leftDriverData.faceProb"),
                      (lambda x: get_idx_if_non_empty(x.leftDriverData.faceOrientation, 0), "leftDriverData.faceOrientation0"),
-                     (lambda x: get_idx_if_non_empty(x.leftDriverData.leftBlinkProb), "leftDriverData.leftBlinkProb"),
+                     (lambda x: get_idx_if_non_empty(x.leftDriverData.eyesClosedProb), "leftDriverData.eyesClosedProb"),
                      (lambda x: get_idx_if_non_empty(x.leftDriverData.phoneProb), "leftDriverData.phoneProb"),
                      (lambda x: get_idx_if_non_empty(x.rightDriverData.faceProb), "rightDriverData.faceProb"),
                     ], "driverStateV2")
diff --git a/selfdrive/ui/mici/onroad/driver_camera_dialog.py b/selfdrive/ui/mici/onroad/driver_camera_dialog.py
index e8321b099c..e8b8abb7f5 100644
--- a/selfdrive/ui/mici/onroad/driver_camera_dialog.py
+++ b/selfdrive/ui/mici/onroad/driver_camera_dialog.py
@@ -39,8 +39,6 @@ class BaseDriverCameraDialog(Widget):
     self._eye_fill_texture = None
     self._eye_orange_texture = None
     self._eye_size = 74
-    self._glasses_texture = None
-    self._glasses_size = 171
 
     self._load_eye_textures()
 
@@ -154,8 +152,6 @@ class BaseDriverCameraDialog(Widget):
       self._eye_fill_texture = gui_app.texture("icons_mici/onroad/eye_fill.png", self._eye_size, self._eye_size)
     if self._eye_orange_texture is None:
       self._eye_orange_texture = gui_app.texture("icons_mici/onroad/eye_orange.png", self._eye_size, self._eye_size)
-    if self._glasses_texture is None:
-      self._glasses_texture = gui_app.texture("icons_mici/onroad/glasses.png", self._glasses_size, self._glasses_size)
 
   def _draw_face_detection(self, rect: rl.Rectangle):
     dm_state = ui_state.sm["driverMonitoringState"]
@@ -202,31 +198,21 @@ class BaseDriverCameraDialog(Widget):
     eye_offset_x = 10
     eye_offset_y = 10
     eye_spacing = self._eye_size + 15
+    eyes_prob = driver_data.eyesVisibleProb
 
     left_eye_x = rect.x + eye_offset_x
     left_eye_y = rect.y + eye_offset_y
-    left_eye_prob = driver_data.leftEyeProb
 
     right_eye_x = rect.x + eye_offset_x + eye_spacing
     right_eye_y = rect.y + eye_offset_y
-    right_eye_prob = driver_data.rightEyeProb
 
     # Draw eyes with opacity based on probability
-    for eye_x, eye_y, eye_prob in [(left_eye_x, left_eye_y, left_eye_prob), (right_eye_x, right_eye_y, right_eye_prob)]:
-      fill_opacity = eye_prob
-      orange_opacity = 1.0 - eye_prob
-
+    fill_opacity = eyes_prob
+    orange_opacity = 1.0 - eyes_prob
+    for eye_x, eye_y in [(left_eye_x, left_eye_y), (right_eye_x, right_eye_y)]:
       rl.draw_texture_v(self._eye_orange_texture, (eye_x, eye_y), rl.Color(255, 255, 255, int(255 * orange_opacity)))
       rl.draw_texture_v(self._eye_fill_texture, (eye_x, eye_y), rl.Color(255, 255, 255, int(255 * fill_opacity)))
 
-    # Draw sunglasses indicator based on sunglasses probability
-    # Position glasses centered between the two eyes at top left
-    glasses_x = rect.x + eye_offset_x - 4
-    glasses_y = rect.y
-    glasses_pos = rl.Vector2(glasses_x, glasses_y)
-    glasses_prob = driver_data.sunglassesProb
-    rl.draw_texture_v(self._glasses_texture, glasses_pos, rl.Color(70, 80, 161, int(255 * glasses_prob)))
-
 
 class DriverCameraDialog(NavWidget, BaseDriverCameraDialog):
   def __init__(self):
diff --git a/selfdrive/ui/mici/onroad/hud_renderer.py b/selfdrive/ui/mici/onroad/hud_renderer.py
index 35d04fe702..56d83992ff 100644
--- a/selfdrive/ui/mici/onroad/hud_renderer.py
+++ b/selfdrive/ui/mici/onroad/hud_renderer.py
@@ -120,7 +120,7 @@ class HudRenderer(Widget):
 
     self._txt_wheel: rl.Texture = gui_app.texture('icons_mici/wheel.png', 50, 50)
     self._txt_wheel_critical: rl.Texture = gui_app.texture('icons_mici/wheel_critical.png', 50, 50)
-    self._txt_exclamation_point: rl.Texture = gui_app.texture('icons_mici/exclamation_point.png', 44, 44)
+    self._txt_exclamation_point: rl.Texture = gui_app.texture('icons_mici/exclamation_point.png', 9, 44)
 
     self._wheel_alpha_filter = FirstOrderFilter(0, 0.05, 1 / gui_app.target_fps)
     self._wheel_y_filter = FirstOrderFilter(0, 0.1, 1 / gui_app.target_fps)
diff --git a/tinygrad_repo b/tinygrad_repo
index 2f55005ad9..1aa04eab08 160000
--- a/tinygrad_repo
+++ b/tinygrad_repo
@@ -1 +1 @@
-Subproject commit 2f55005ad93c777cca69b20dddc28c7f02f0eb01
+Subproject commit 1aa04eab086d9c22855cfe50f746235200d28867
diff --git a/tools/jotpluggler/plot.cc b/tools/jotpluggler/plot.cc
index a3c68ddcef..5d9d644808 100644
--- a/tools/jotpluggler/plot.cc
+++ b/tools/jotpluggler/plot.cc
@@ -6,7 +6,6 @@
 #include <cmath>
 #include <cstdio>
 #include <limits>
-#include <unordered_set>
 
 constexpr double PLOT_Y_PAD_FRACTION = 0.4;
 
@@ -74,10 +73,6 @@ struct StateBlock {
   std::string label;
 };
 
-struct PaneEnumContext {
-  std::vector<const EnumInfo *> enums;
-};
-
 struct PaneValueFormatContext {
   SeriesFormat format;
   bool valid = false;
@@ -106,38 +101,6 @@ bool curves_are_bool_like(const std::vector<PreparedCurve> &prepared_curves) {
   return true;
 }
 
-bool curve_is_state_like(const PreparedCurve &curve) {
-  if (!curve.display_info.integer_like || curve.xs.size() < 2 || curve.xs.size() != curve.ys.size()) {
-    return false;
-  }
-  if (curve.enum_info != nullptr) {
-    return true;
-  }
-  std::unordered_set<int> distinct_values;
-  for (double value : curve.ys) {
-    if (!std::isfinite(value)) {
-      continue;
-    }
-    distinct_values.insert(static_cast<int>(std::llround(value)));
-    if (distinct_values.size() > 12) {
-      return false;
-    }
-  }
-  return !distinct_values.empty();
-}
-
-bool curves_use_state_blocks(const std::vector<PreparedCurve> &prepared_curves) {
-  if (prepared_curves.empty()) {
-    return false;
-  }
-  for (const PreparedCurve &curve : prepared_curves) {
-    if (!curve_is_state_like(curve)) {
-      return false;
-    }
-  }
-  return true;
-}
-
 ImU32 state_block_color(int value, float alpha = 1.0f) {
   static constexpr std::array<std::array<uint8_t, 3>, 8> kPalette = {{
     {{111, 143, 175}},
@@ -307,36 +270,6 @@ std::optional<double> app_sample_xy_value_at_time(const std::vector<double> &xs,
   return y0 + (y1 - y0) * alpha;
 }
 
-int format_enum_axis_tick(double value, char *buf, int size, void *user_data) {
-  const auto *ctx = static_cast<const PaneEnumContext *>(user_data);
-  const int idx = static_cast<int>(std::llround(value));
-  if (ctx != nullptr && idx >= 0 && std::abs(value - static_cast<double>(idx)) < 0.01) {
-    std::vector<std::string_view> names;
-    names.reserve(ctx->enums.size());
-    for (const EnumInfo *info : ctx->enums) {
-      if (info == nullptr || static_cast<size_t>(idx) >= info->names.size()) {
-        continue;
-      }
-      const std::string &name = info->names[static_cast<size_t>(idx)];
-      if (name.empty()) continue;
-      if (std::find(names.begin(), names.end(), std::string_view(name)) == names.end()) {
-        names.emplace_back(name);
-      }
-    }
-    if (!names.empty()) {
-      std::string joined;
-      for (size_t i = 0; i < names.size(); ++i) {
-        if (i != 0) {
-          joined += ", ";
-        }
-        joined += names[i];
-      }
-      return std::snprintf(buf, size, "%d (%s)", idx, joined.c_str());
-    }
-  }
-  return std::snprintf(buf, size, "%.6g", value);
-}
-
 int format_numeric_axis_tick(double value, char *buf, int size, void *user_data) {
   const auto *ctx = static_cast<const PaneValueFormatContext *>(user_data);
   if (ctx == nullptr || !ctx->valid) {
@@ -831,23 +764,16 @@ void draw_plot(const AppSession &session, Pane *pane, UiState *state) {
   }
 
   const PlotBounds bounds = compute_plot_bounds(*pane, prepared_curves, *state);
-  PaneEnumContext enum_context;
   PaneValueFormatContext pane_value_format;
-  const bool state_block_mode = curves_use_state_blocks(prepared_curves);
-  bool all_enum_curves = !prepared_curves.empty();
+  bool state_block_mode = !prepared_curves.empty();
   size_t max_legend_label_width = 0;
   for (const PreparedCurve &curve : prepared_curves) {
     max_legend_label_width = std::max(max_legend_label_width, curve.label.size());
-    if (curve.enum_info != nullptr) {
-      enum_context.enums.push_back(curve.enum_info);
-    } else {
-      all_enum_curves = false;
+    if (curve.enum_info == nullptr) {
+      state_block_mode = false;
       merge_pane_value_format(&pane_value_format, curve.display_info);
     }
   }
-  if (prepared_curves.empty()) {
-    all_enum_curves = false;
-  }
   const int supported_count = static_cast<int>(prepared_curves.size());
   const ImVec2 plot_size = ImGui::GetContentRegionAvail();
   const bool has_cursor_time = state->has_tracker_time;
@@ -895,8 +821,6 @@ void draw_plot(const AppSession &session, Pane *pane, UiState *state) {
     ImPlot::SetupAxisFormat(ImAxis_X1, "%.1f");
     if (state_block_mode) {
       ImPlot::SetupAxisLimits(ImAxis_Y1, 0.0, 1.0, ImPlotCond_Always);
-    } else if (all_enum_curves && !enum_context.enums.empty()) {
-      ImPlot::SetupAxisFormat(ImAxis_Y1, format_enum_axis_tick, &enum_context);
     } else if (pane_value_format.valid) {
       ImPlot::SetupAxisFormat(ImAxis_Y1, format_numeric_axis_tick, &pane_value_format);
     } else {
diff --git a/tools/replay/lib/ui_helpers.py b/tools/replay/lib/ui_helpers.py
index 7c95e9cad4..039dd4f235 100644
--- a/tools/replay/lib/ui_helpers.py
+++ b/tools/replay/lib/ui_helpers.py
@@ -5,6 +5,7 @@ import numpy as np
 import pyray as rl
 
 from matplotlib.backends.backend_agg import FigureCanvasAgg
+from matplotlib.offsetbox import AnchoredOffsetbox, HPacker, TextArea
 
 from openpilot.common.transformations.camera import get_view_frame_from_calib_frame
 from openpilot.selfdrive.controls.radard import RADAR_TO_CAMERA
@@ -94,6 +95,7 @@ def draw_path(path, color, img, calibration, top_down, lid_color=None, z_off=0):
 
 def init_plots(arr, name_to_arr_idx, plot_xlims, plot_ylims, plot_names, plot_colors, plot_styles):
   color_palette = {"r": (1, 0, 0), "g": (0, 1, 0), "b": (0, 0, 1), "k": (0, 0, 0), "y": (1, 1, 0), "p": (0, 1, 1), "m": (1, 0, 1)}
+  label_palette = {**color_palette, "b": (43/255, 114/255, 1.0)}
 
   dpi = 90
   fig = plt.figure(figsize=(575 / dpi, 600 / dpi), dpi=dpi)
@@ -116,10 +118,18 @@ def init_plots(arr, name_to_arr_idx, plot_xlims, plot_ylims, plot_names, plot_co
       plots.append(plot)
       idxs.append(name_to_arr_idx[item])
       plot_select.append(i)
-    axs[i].set_title(", ".join(f"{nm} ({cl})" for (nm, cl) in zip(pl_list, plot_colors[i], strict=False)), fontsize=10)
+    # Build colored title: each label colored to match its plot line
+    title_texts = []
+    for j2, (nm, cl) in enumerate(zip(pl_list, plot_colors[i], strict=False)):
+      if j2 > 0:
+        title_texts.append(TextArea(", ", textprops=dict(color="white", fontsize=10)))
+      title_texts.append(TextArea(nm, textprops=dict(color=label_palette[cl], fontsize=10)))
+    packed = HPacker(children=title_texts, pad=0, sep=0)
+    ab = AnchoredOffsetbox(loc='lower center', child=packed, bbox_to_anchor=(0.5, 1.0),
+                           bbox_transform=axs[i].transAxes, frameon=False, pad=0)
+    axs[i].add_artist(ab)
     axs[i].tick_params(axis="x", colors="white")
     axs[i].tick_params(axis="y", colors="white")
-    axs[i].title.set_color("white")
 
     if i < len(plot_ylims) - 1:
       axs[i].set_xticks([])
diff --git a/tools/replay/ui.py b/tools/replay/ui.py
index 7fe2f405a1..405c79f425 100755
--- a/tools/replay/ui.py
+++ b/tools/replay/ui.py
@@ -3,7 +3,6 @@ import argparse
 import os
 import sys
 
-import cv2
 import numpy as np
 import pyray as rl
 
@@ -22,7 +21,8 @@ from openpilot.tools.replay.lib.ui_helpers import (
   plot_lead,
   plot_model,
 )
-from msgq.visionipc import VisionIpcClient, VisionStreamType
+from msgq.visionipc import VisionStreamType
+from openpilot.selfdrive.ui.mici.onroad.cameraview import CameraView
 
 os.environ['BASEDIR'] = BASEDIR
 
@@ -30,8 +30,6 @@ ANGLE_SCALE = 5.0
 
 
 def ui_thread(addr):
-  cv2.setNumThreads(1)
-
   # Get monitor info before creating window
   rl.set_config_flags(rl.ConfigFlags.FLAG_MSAA_4X_HINT)
   rl.init_window(1, 1, "")
@@ -59,14 +57,15 @@ def ui_thread(addr):
   font_path = os.path.join(BASEDIR, "selfdrive/assets/fonts/JetBrainsMono-Medium.ttf")
   font = rl.load_font_ex(font_path, 32, None, 0)
 
-  # Create textures for camera and top-down view
-  camera_image = rl.gen_image_color(640, 480, rl.BLACK)
-  camera_texture = rl.load_texture_from_image(camera_image)
-  rl.unload_image(camera_image)
+  camera_view = CameraView("camerad", VisionStreamType.VISION_STREAM_ROAD)
+
+  # Overlay texture for model/lane line drawing
+  overlay_img = np.zeros((480, 640, 4), dtype='uint8')
+  overlay_image = rl.gen_image_color(640, 480, rl.BLANK)
+  overlay_texture = rl.load_texture_from_image(overlay_image)
+  rl.unload_image(overlay_image)
 
   # lid_overlay array is (lidar_x, lidar_y) = (384, 960)
-  # pygame treats first axis as width, so texture is 384 wide x 960 tall
-  # For raylib, we need to transpose to get (height, width) = (960, 384) for the RGBA array
   top_down_image = rl.gen_image_color(UP.lidar_x, UP.lidar_y, rl.BLACK)
   top_down_texture = rl.load_texture_from_image(top_down_image)
   rl.unload_image(top_down_image)
@@ -89,7 +88,6 @@ def ui_thread(addr):
   )
 
   img = np.zeros((480, 640, 3), dtype='uint8')
-  imgff = None
   num_px = 0
   calibration = None
 
@@ -116,7 +114,7 @@ def ui_thread(addr):
   plot_arr = np.zeros((100, len(name_to_arr_idx.values())))
 
   plot_xlims = [(0, plot_arr.shape[0]), (0, plot_arr.shape[0]), (0, plot_arr.shape[0]), (0, plot_arr.shape[0])]
-  plot_ylims = [(-0.1, 1.1), (-ANGLE_SCALE, ANGLE_SCALE), (0.0, 75.0), (-3.0, 2.0)]
+  plot_ylims = [(-0.1, 1.1), (-ANGLE_SCALE, ANGLE_SCALE), (0.0, 75.0), (-3.5, 2.0)]
   plot_names = [
     ["gas", "computer_gas", "user_brake", "computer_brake"],
     ["angle_steers", "angle_steers_des", "angle_steers_k", "steer_torque"],
@@ -138,20 +136,16 @@ def ui_thread(addr):
   palette[110] = [110, 110, 110, 255]  # car_color (gray)
   palette[255] = [255, 255, 255, 255]  # WHITE
 
-  vipc_client = VisionIpcClient("camerad", VisionStreamType.VISION_STREAM_ROAD, True)
   while not rl.window_should_close():
-    # ***** frame *****
-    if not vipc_client.is_connected():
-      vipc_client.connect(False)
-
     rl.begin_drawing()
     rl.clear_background(rl.Color(64, 64, 64, 255))
 
-    yuv_img_raw = vipc_client.recv()
-    if yuv_img_raw is None or not yuv_img_raw.data.any():
-      rl.draw_text_ex(font, "waiting for frames", rl.Vector2(200, 200), 30, 0, rl.WHITE)
-      rl.end_drawing()
-      continue
+    # Render camera (NV12->RGB on GPU via shader)
+    if camera_view.frame:
+      cam_h = 640.0 * camera_view.frame.height / camera_view.frame.width
+    else:
+      cam_h = 480.0
+    camera_view.render(rl.Rectangle(0, 0, 640, cam_h))
 
     lid_overlay = lid_overlay_blank.copy()
     top_down = top_down_texture, lid_overlay
@@ -159,19 +153,10 @@ def ui_thread(addr):
     sm.update(0)
 
     camera = DEVICE_CAMERAS[("tici", str(sm['roadCameraState'].sensor))]
-
-    # Use received buffer dimensions (full HEVC can have stride != buffer_len/rows due to VENUS padding)
-    h, w, stride = yuv_img_raw.height, yuv_img_raw.width, yuv_img_raw.stride
-    nv12_size = h * 3 // 2 * stride
-    imgff = np.frombuffer(yuv_img_raw.data, dtype=np.uint8, count=nv12_size).reshape((h * 3 // 2, stride))
-    num_px = w * h
-    rgb = cv2.cvtColor(imgff[: h * 3 // 2, : w], cv2.COLOR_YUV2RGB_NV12)
-
-    qcam = "QCAM" in os.environ
-    bb_scale = (528 if qcam else camera.fcam.width) / 640.0
     calib_scale = camera.fcam.width / 640.0
-    zoom_matrix = np.asarray([[bb_scale, 0.0, 0.0], [0.0, bb_scale, 0.0], [0.0, 0.0, 1.0]])
-    cv2.warpAffine(rgb, zoom_matrix[:2], (img.shape[1], img.shape[0]), dst=img, flags=cv2.WARP_INVERSE_MAP)
+
+    if camera_view.frame:
+      num_px = camera_view.frame.width * camera_view.frame.height
 
     intrinsic_matrix = camera.fcam.intrinsics
 
@@ -183,7 +168,8 @@ def ui_thread(addr):
     else:
       angle_steers_k = np.inf
 
-    plot_arr[:-1] = plot_arr[1:]
+    if sm.updated['carState']:
+      plot_arr[:-1] = plot_arr[1:]
     plot_arr[-1, name_to_arr_idx['angle_steers']] = sm['carState'].steeringAngleDeg
     plot_arr[-1, name_to_arr_idx['angle_steers_des']] = sm['carControl'].actuators.steeringAngleDeg
     plot_arr[-1, name_to_arr_idx['angle_steers_k']] = angle_steers_k
@@ -198,9 +184,10 @@ def ui_thread(addr):
     plot_arr[-1, name_to_arr_idx['v_cruise']] = sm['carState'].cruiseState.speed
     plot_arr[-1, name_to_arr_idx['a_ego']] = sm['carState'].aEgo
 
-    if len(sm['longitudinalPlan'].accels):
-      plot_arr[-1, name_to_arr_idx['a_target']] = sm['longitudinalPlan'].accels[0]
+    plot_arr[-1, name_to_arr_idx['a_target']] = sm['longitudinalPlan'].aTarget
 
+    # Draw model overlays onto img, then blit as transparent overlay
+    img[:] = 0
     if sm.recv_frame['modelV2']:
       plot_model(sm['modelV2'], img, calibration, top_down)
 
@@ -214,11 +201,12 @@ def ui_thread(addr):
       rpyCalib = np.asarray(sm['liveCalibration'].rpyCalib)
       calibration = Calibration(num_px, rpyCalib, intrinsic_matrix, calib_scale)
 
-    # *** blits ***
-    # Update camera texture from numpy array
-    img_rgba = cv2.cvtColor(img, cv2.COLOR_RGB2RGBA)
-    rl.update_texture(camera_texture, rl.ffi.cast("void *", img_rgba.ctypes.data))
-    rl.draw_texture(camera_texture, 0, 0, rl.WHITE)  # noqa: TID251
+    # Update overlay texture (RGB img -> RGBA with non-black pixels visible)
+    mask = np.any(img > 0, axis=2)
+    overlay_img[:, :, :3] = img
+    overlay_img[:, :, 3] = mask * 255
+    rl.update_texture(overlay_texture, rl.ffi.cast("void *", overlay_img.ctypes.data))
+    rl.draw_texture(overlay_texture, 0, 0, rl.WHITE)  # noqa: TID251
 
     # display alerts
     rl.draw_text_ex(font, sm['selfdriveState'].alertText1, rl.Vector2(180, 150), 30, 0, rl.RED)
@@ -257,9 +245,10 @@ def ui_thread(addr):
 
     rl.end_drawing()
 
-  rl.unload_texture(camera_texture)
+  rl.unload_texture(overlay_texture)
   rl.unload_texture(top_down_texture)
   rl.unload_font(font)
+  camera_view.close()
   rl.close_window()