simple_LaneNet OptimizedLaneNet — Lightweight Real-time Lane Segmentation Model Overview Backbone: Depthwise Separable Convolutions Attention: SE Block (reduction=8) Residual Blocks: 2 stages Decoder: Bilinear upsampling + conv layers Input: 270×480 RGB Output: 270×480 binary lane mask Performance Latency (End-to-End, pre+infer+post, batch=1): 25.05 ms/image (≈ 39.9 FPS) Pure Inference (forward only, batch=1): 1.88 ms/image (≈ 532 FPS) Model size: ~1 MB (PyTorch)
