Update README.md


README.md

@@ -29,39 +29,7 @@ This model demonstrates a road segmentation implemented using **deep learning**
  - **rs1-high.pth**: The highest performer model with a loss of **0.07%**.
 
 ## Model Structure
-
-===============================================================================================
-Layer (type:depth-idx)                        Output Shape              Param #
-===============================================================================================
-RoadSegmentationModel                         [16, 1, 256, 256]         --
-├─FeatureListNet: 1-1                         [16, 64, 128, 128]        --
-│    └─Conv2d: 2-1                            [16, 64, 128, 128]        9,408
-│    └─BatchNorm2d: 2-2                       [16, 64, 128, 128]        128
-│    └─ReLU: 2-3                              [16, 64, 128, 128]        --
-│    └─MaxPool2d: 2-4                         [16, 64, 64, 64]          --
-│    └─Sequential: 2-5                        [16, 256, 64, 64]         --
-│    │    └─Bottleneck: 3-1                   [16, 256, 64, 64]         75,008
-│    │    └─Bottleneck: 3-2                   [16, 256, 64, 64]         70,400
-│    │    └─Bottleneck: 3-3                   [16, 256, 64, 64]         70,400
-│    └─Sequential: 2-6                        [16, 512, 32, 32]         --
-│    │    └─Bottleneck: 3-4                   [16, 512, 32, 32]         379,392
-│    │    └─Bottleneck: 3-5                   [16, 512, 32, 32]         280,064
-│    │    └─Bottleneck: 3-6                   [16, 512, 32, 32]         280,064
-│    │    └─Bottleneck: 3-7                   [16, 512, 32, 32]         280,064
-│    └─Sequential: 2-7                        [16, 1024, 16, 16]        --
-│    │    └─Bottleneck: 3-8                   [16, 1024, 16, 16]        1,512,448
-│    │    └─Bottleneck: 3-9                   [16, 1024, 16, 16]        1,117,184
-│    │    └─Bottleneck: 3-10                  [16, 1024, 16, 16]        1,117,184
-│    │    └─Bottleneck: 3-11                  [16, 1024, 16, 16]        1,117,184
-│    │    └─Bottleneck: 3-12                  [16, 1024, 16, 16]        1,117,184
-│    │    └─Bottleneck: 3-13                  [16, 1024, 16, 16]        1,117,184
-...
-Input size (MB): 12.58
-Forward/backward pass size (MB): 4731.17
-Params size (MB): 272.32
-Estimated Total Size (MB): 5016.08
-===============================================================================================
-
+![Screenshot 2025-03-29 at 5.49.40 PM.png](https://cdn-uploads.huggingface.co/production/uploads/6787e9bb4151553bf9307186/dCLpzMaW7tZpbn2jJci5_.png)
 ## Features
 1. ### Architecture
     - Basic **Resnet50** model with few upsampling and batch normalisation layers.