RCLane release model (17-09-2026)

Model artifacts used with the RCLane source release at Git commit 833455bf0046986531913ae7abcbc0dc1fd3e38f.

Files

File	Purpose	SHA-256
rclane_b0_e19_fp16.engine	Exact FP16 TensorRT engine used by the deployed lane-detection service	1dd1ea149559dd5694e450067cd1d34a2299c49973eb91fb06a07bce78037e72
rclane_b0_e19_trt85.onnx	Portable ONNX graph prepared for TensorRT 8.5	8847f7da77c5bcdb67c166e119f9817f68aa2d420acbd333128a10826ce363cd
rclane_b0_e19.pth	PyTorch training checkpoint, CARLA B0 epoch 19	ef3eb57a7064cb89783144a05344635e1be3a7527dd69a2022b0240782908866
manifest.json	Artifact metadata and checksums	—

Interface

• Input: images, shape N x 3 x 320 x 800
• Outputs: seg_map, up_arrow, down_arrow, up_bound, down_bound
• ONNX opset: 17

TensorRT engines are environment-specific. The included engine is the exact deployed artifact and was used on an NVIDIA GeForce RTX 3050 6GB Laptop GPU (compute capability 8.6). Rebuild the engine from the ONNX file when using a different GPU, TensorRT, CUDA, or driver stack.