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feat(import): correctly handle simulation imports #56

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Feb 25, 2025
Merged

feat(import): correctly handle simulation imports #56

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12 changes: 10 additions & 2 deletions ddlitlab2024/dataset/cli/run.py
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Original file line number Diff line number Diff line change
Expand Up @@ -61,12 +61,20 @@ def main():
from ddlitlab2024.dataset.imports.strategies.bitbots import BitBotsImportStrategy

logger.info(f"Trying to import file '{args.file}' to database...")

simulated = False
location = "RoboCup2024"

if "simulation" in str(args.file) or "simulated" in str(args.file):
simulated = True
location = "Webots Simulator"

metadata = ImportMetadata(
allow_public=True,
team_name="Bit-Bots",
robot_type="Wolfgang-OP",
location="RoboCup2024",
simulated=False,
location=location,
simulated=simulated,
)
image_converter = ImageConverter(MaxRateResampler(IMAGE_MAX_RESAMPLE_RATE_HZ))
game_state_converter = GameStateConverter(OriginalRateResampler())
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10 changes: 9 additions & 1 deletion ddlitlab2024/dataset/converters/image_converter.py
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Expand Up @@ -37,7 +37,7 @@ def convert_to_model(self, data: InputData, relative_timestamp: float, recording
return models

def _create_image(self, data, sampling_timestamp: float, recording: Recording) -> Image:
img_array = np.frombuffer(data.data, np.uint8).reshape((data.height, data.width, 3))
img_array = np.frombuffer(data.data, np.uint8).reshape((data.height, data.width, -1))

will_img_be_upscaled = recording.img_width_scaling > 1.0 or recording.img_height_scaling > 1.0
interpolation = cv2.INTER_AREA
Expand All @@ -50,9 +50,17 @@ def _create_image(self, data, sampling_timestamp: float, recording: Recording) -
resized_rgb_img = resized_img
case "bgr8":
resized_rgb_img = cv2.cvtColor(resized_img, cv2.COLOR_BGR2RGB)
case "bgra8":
resized_rgb_img = cv2.cvtColor(resized_img, cv2.COLOR_BGRA2RGB)
case _:
raise AssertionError(f"Unsupported image encoding: {data.encoding}")

assert resized_rgb_img.shape == (
recording.img_height,
recording.img_width,
3,
), "Converted image does not have the expected dimensions"

return Image(
stamp=sampling_timestamp,
recording=recording,
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