fix(robodojo): decode JPEG frames with the recorder's channel order

openwam/dataloader/robodojo.py

@@ -22,14 +22,14 @@
 
 import bisect
 import hashlib
-import io
 import json
 import os
 import time
 from collections.abc import Mapping, Sequence
 from pathlib import Path
 from typing import Any
 
+import cv2
 import h5py
 import numpy as np
 import torch
@@ -357,14 +357,28 @@ def _jpeg_bytes(value: Any) -> bytes:
 
 
 def _decode_jpeg(value: Any, *, source: str) -> Image.Image:
+    """Decode JPEG bytes from HDF5 to a PIL RGB image.
+
+    RoboDojo encodes frames by passing RGB arrays directly to ``cv2.imencode``
+    (which expects BGR), so R and B channels are swapped inside the JPEG. Using
+    ``cv2.imdecode`` reverses this swap, giving back the original RGB order — no
+    further conversion needed. This is the same convention ``robotwin.py``
+    documents for the RoboTwin corpus.
+
+    Decoding with PIL instead returns the stored order, i.e. R and B swapped,
+    which is what this reader did until this was caught: the model trained on
+    channel-swapped frames while the deploy path (which decodes whatever the
+    eval client encodes, and every in-repo client encodes true RGB) served
+    correct ones. Confirmed against the corpora's own ``preview_video/*.mp4``,
+    which match this decoder and not PIL's, on both the sim and real corpora.
+    """
     encoded = _jpeg_bytes(value)
     if not encoded:
         raise ValueError(f"{source}: JPEG entry is empty")
-    try:
-        with Image.open(io.BytesIO(encoded)) as image:
-            return image.convert("RGB").copy()
-    except Exception as error:
-        raise ValueError(f"{source}: could not decode JPEG") from error
+    array = cv2.imdecode(np.frombuffer(encoded, np.uint8), cv2.IMREAD_COLOR)
+    if array is None:
+        raise ValueError(f"{source}: could not decode JPEG")
+    return Image.fromarray(array)
 
 
 def discover_robodojo_tasks(

tests/test_robodojo_dataloader.py

@@ -5,6 +5,7 @@
 import io
 from pathlib import Path
 
+import cv2
 import h5py
 import numpy as np
 import pytest
@@ -59,10 +60,18 @@ def write_calibration(root: Path) -> Path:
 
 
 def encode_jpeg(color: tuple[int, int, int], height: int = 18, width: int = 20) -> bytes:
-    image = Image.new("RGB", (width, height), color)
-    buffer = io.BytesIO()
-    image.save(buffer, format="JPEG", quality=100, subsampling=0)
-    return buffer.getvalue()
+    """Encode ``color`` (RGB) the way the RoboDojo recorder does.
+
+    It hands an RGB array straight to ``cv2.imencode``, which expects BGR, so R
+    and B end up swapped inside the file. Fixtures have to reproduce that or the
+    reader's ``cv2.imdecode`` — which exists to undo it — looks wrong under test
+    while being right on real data.
+    """
+    rgb = np.zeros((height, width, 3), dtype=np.uint8)
+    rgb[:, :] = color
+    ok, buffer = cv2.imencode(".jpg", rgb, [int(cv2.IMWRITE_JPEG_QUALITY), 100])
+    assert ok, "cv2.imencode failed"
+    return buffer.tobytes()
 
 
 def source_arrays(T: int) -> tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
@@ -856,3 +865,25 @@ def test_registry_constructs_robodojo_and_exports_classes(tmp_path: Path):
     assert isinstance(dataset, MultiTaskRoboDojoDataset)
     assert isinstance(dataset._sub_datasets[0], RoboDojoDataset)
     assert dataset[0]["action"].shape == (2, 80)
+
+
+def test_decode_jpeg_undoes_the_recorder_channel_swap():
+    """The reader must return true RGB, not the stored order.
+
+    RoboDojo writes its JPEGs with ``cv2.imencode`` fed an RGB array, so the file
+    holds R and B swapped. Decoding with PIL returns that stored order and feeds
+    the model channel-swapped frames, which is what this reader did until it was
+    caught against the corpora's own preview videos. Pinned here because CI never
+    sees a real episode.
+    """
+    from openwam.dataloader.robodojo import _decode_jpeg
+
+    red = (230, 20, 15)
+    frame = np.asarray(_decode_jpeg(encode_jpeg(red), source="test"))
+
+    assert frame[0, 0, 0] > 200, "red must come back in channel 0"
+    assert frame[0, 0, 2] < 60, "blue must not have been swapped into channel 0"
+
+    # And the PIL reading of the very same bytes is the swap this guards against.
+    stored = np.asarray(Image.open(io.BytesIO(encode_jpeg(red))).convert("RGB"))
+    assert stored[0, 0, 2] > 200 and stored[0, 0, 0] < 60