Update README.md

README.md

@@ -1,3 +1,57 @@
 ---
+language: en
+tags:
+  - crowd-counting
+  - density-estimation
+  - computer-vision
+  - pytorch
+  - csrnet
+  - indian-metro
 license: mit
 ---
+
+# CSRNet Fine-tuned — Indian Metro Crowd Density Estimation
+
+Fine-tuned CSRNet for real-time crowd density estimation on Indian metro platforms.
+
+**MAE = 12.36** on held-out Indian metro test set.
+95.6% more accurate than YOLOv8 on the same data.
+
+## Model Details
+- Architecture: CSRNet (VGG-16 frontend + dilated conv backend, dilation rate r=2)
+- Training data: ShanghaiTech Part A + B (700 images) + Custom Indian Metro (88 images)
+- Custom dataset: 5,030 head-point annotations across 111 images from Delhi Metro
+  (Rajiv Chowk), Hyderabad Metro (Ameerpet), and Mumbai Central
+- Best epoch: 14 | MAE: 11.30 | MSE: 13.99
+- Inference: < 0.5 seconds on CPU
+
+## Results
+
+| Approach | MAE | Density Map | Verdict |
+|---|---|---|---|
+| CNN Classifier (ResNet-18) | ~55 | No | Failed |
+| YOLOv8 (pretrained COCO) | 283.23 | No | Failed |
+| CSRNet Pretrained | ~50 | Yes | Baseline |
+| **CSRNet Fine-tuned (this)** | **12.36** | Yes | Best |
+
+## Usage
+
+```python
+import torch
+from huggingface_hub import hf_hub_download
+from model import CSRNet
+
+weights_path = hf_hub_download(
+    repo_id  = "YOUR_HF_USERNAME/csrnet-indian-metro-crowd-density",
+    filename = "csrnet_v3_best.pth"
+)
+
+model = CSRNet()
+model.load_state_dict(torch.load(weights_path, map_location="cpu"))
+model.eval()
+```
+
+## Author
+Abdur Rahman Qasim — B.Tech CSE 2025–26  
+Methodist College of Engineering and Technology, Hyderabad  
+Guide: Dr. Shivani Yadao